Most e-commerce platforms allow consumers to post product reviews, causing more and more consumers to get into the habit of reading reviews before they buy. These online reviews serve as an emotional feedback of consumers’ product experience and contain a lot of important information, but inevitably there are malicious or irrelevant reviews. It is especially important to discover and identify the real sentiment tendency in online reviews in a timely manner. Therefore, a deep learning-based real online consumer sentiment (...) classification model is proposed. First, the mapping relationship between online reviews of goods and sentiment features is established based on expert knowledge and using fuzzy mathematics, thus mapping the high-dimensional original text data into a continuous low-dimensional space. Secondly, after obtaining local contextual features using convolutional operations, the long-term dependencies between features are fully considered by a bidirectional long- and short-term memory network. Then, the degree of contribution of different words to the text is considered by introducing an attention mechanism, and a regular term constraint is introduced in the objective function. The experimental results show that the proposed convolutional attention–long and short-term memory network model has a higher test accuracy of 83.3% compared with other models, indicating that the model has better classification performance. (shrink)

Aspect-level sentiment classification is an interesting and challenging research task to identify the sentiment polarities of aspect words in sentences. Previous attention-based methods rarely consider the position information of aspect and contextual words. For an aspect word in a sentence, its adjacent words should be given more attention than the long distant words. Based on this consideration, this article designs a position influence vector to represent the position information between an aspect word and the context. By combining (...) the position influence vector, multi-head self-attention mechanism and bidirectional gated recurrent unit, a position-enhanced multi-head self-attention network based BiGRU model is proposed. To verify the effectiveness of the proposed model, this article makes a large number of experiments on SemEval2014 restaurant, SemEval2014 laptop, SemEval2015 restaurant, and SemEval2016 restaurant data sets. The experiment results show that the performance of the proposed PMHSAT-BiGRU model is obviously better than the baselines. Specially, compared with the original LSTM model, the Accuracy values of the proposed PMHSAT-BiGRU model on the four data sets are improved by 5.72, 6.06, 4.52, and 3.15%, respectively. (shrink)

Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. (...) After precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user’s post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately. (shrink)

The Covid-19 pandemic is forcing organizations to innovate and change their strategies for a new reality. This study collects online learning related tweets in Arabic language to perform a comprehensive emotion mining and sentiment analysis (SA) during the pandemic. The present study exploits Natural Language Processing (NLP) and Machine Learning (ML) algorithms to extract subjective information, determine polarity and detect the feeling. We begin with pulling out the tweets using Twitter APIs and then preparing for intensive preprocessing. Second, the (...) National Research Council Canada (NRC) Word-Emotion Lexicon was examined to calculate the presence of the eight emotions at their emotional weight. Third, Information Gain (IG) is used as a filtering technique. Fourth, the latent reasons behind the negative sentiments were recognized and analyzed. Finally, different classification algorithms including Naïve Bayes (NB), Multinomial Naïve Bayes (MNB), K Nearest Neighbor (KNN), Logistic Regression (LR), and Support Vector Machine (SVM) were examined. The experiments reveal that the proposed model performs well in analyzing the perception of people about coronavirus with a maximum accuracy of about 89.6% using SVM classifier. From a practical perspective, the method could be generalized to other topical domains, such as public health monitoring and crisis management. It would help public health officials identify the progression and peaks of concerns for a disease in space and time, which enables the implementation of appropriate preventive actions to mitigate these diseases. (shrink)

In order to solve the problem of the influence of feature word position in lyrics on music emotion classification, this paper designs a music classification and detection model in complex noise environment. Firstly, an intelligent detection algorithm for electronic music signals under complex noise scenes is proposed, which can solve the limitations existing in the current electronic music signal detection process. At the same time, denoising technology is introduced to eliminate the noise and extract the features from the (...) signal. Secondly, from the perspective of audio and lyrics of song sentiment analysis and the unique characteristics of lyrics text, a lyric sentiment analysis method based on text title and position weight is proposed. Finally, considering the influence of the weight of feature words in different positions on the classification of lyrics, the analytic hierarchy process is used to calculate the weight of feature words in different positions of text title and lyrics before, in, and after the text. The results show that in the complex noise environment, the accuracy of music classification and detection of the proposed model is more than 90%, which is far beyond the control range of the actual application of music processing. The effect of music classification and detection is better than that of the contrast model, which has a certain practical application value. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Hume's Moral Sentiments and the Structure of the Treatise LOUIS E. LOEB ACCORDING TO NORMAN KEMP SMITH and Thomas Hearn, Hume classified moral sentiments as direct passions.' According to Pb.II A,rdal, Hume classified the basic moral sentiments of approval and disapproval of persons as indirect passions. if either of these interpretations is correct, there is an intimate connection between Books II and 111 of Hume's Treatise. This is because (...) the direct and indirect passions (together with the will) are the subject of Book 11 and moral sentiments are discussed in Book 111. So if moral sentiments are special cases of either direct or indirect passions, the treatment of passions in Book Ii is central to the understanding of Book 111. 1 contend, on the contrary, that Hume's moral sentiments are neither direct nor indirect passions. Consequently, the connection between Books 11 and 111 of the Treatise is much less intimate than A,rdal and Hearn have recently suggested.' i. Hume's Classification of the Impressions of Reflection In the four paragraphs of II, i, I Hume provides an exhaustive "Division of the Subject"--the "subject" being "all the perceptions of the mind. ''4 Nowhere else in the Treatise is a complete "division" to be found. As A,rdal points out, such introductory chapters "are likely to be written after the bulk of the book has been completed, or at least to be carefully revised in the light of the main arguments in the book. ''~ For these reasons, there is a strong presumption that the "division" in!I, i, 1should be taken as canonical. Hume's "division" is straightforward. In the first paragraph, perceptions are divided into ideas and impressions; in the first and second paragraphs, impressions are divided into those of sensation and those of reflection; in the third paragraph, impressions of reflection are divided into the calm and the violent; in the fourth (as I am indebted to Wdham Frankena, Ronald Glossop, and Peter Jones for their most helpful comments. ' Norman Kemp Smith, The Philosophy of David Hume (New York: St. Martm'~ Press, 1966), pp. 167-168; and Thomas K. Hearn, Jr., "Ardal on the Moral Sentiments in Hume's rreattse," Phtlosophy 48 (1973):290. z Passton and Value m Hume's "Treatise" (Edinburgh: Edinburgh University Press, 1966), pp. I 1, 109-133. For a discussion heavily influenced by Ardal, see Stewart R. Sutherland, "Hume on Morality and the Emotions," Phllosophwal Quarterly 26 (1976) : 14-19 especially. ' See Ardal, pp. I-5, 109-133; and Hearn, pp. 288, 292. 9 A Treatise of Human Nature, ed. L. A. Selby-Bigge (Oxford: Clarendon Press, 1888), p. 275; hereafter cited as T followed by page number. 9 Ardal, p. 94. 13951 396 HISTORY OF PHILOSOPHY indicated by the last sentence of the third), the violent impressions of reflection are divided into the direct and the indirect. The structure is of a genus-species sort, and none of the distinctions cut across each other: J calm i sense of beauty and deformity (T, 276), moral sentiments impressions of reflection = emotions (secondary impressions) violent = passions direct indirect desire, aversion, grief, joy, pride, humility, love, hope, fear (T, 277, 439) hatred (T, 276-277) This classification is based upon the only natural reading of paragraph three and the first sentence of paragraph four of II, i, I. I quote this material, adding my own emphasis and deleting Hume's: The reflective impressions may be divided into two kinds, viz. the calm and the violent. Of the first kind is the sense of beauty and deformity in action, composition, and external objects. Of the second are the passions of love and hatred, grief and joy, pride and humility. This division is far from being exact. The raptures of poetry and music frequently rise to the greatest height; while those other impressions, properly called passions, may decay into so soft an emotion, as to become, in a manner, imperceptible. But as in general the passions are more violent than the emotions arising from beauty and deformity, these impressions have been commonly distinguish'd from each other. The subject of the human mind being so copious and various, I shall here take... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Hume's Classification of the Passions and Its Precursors James Fieser Hume's theory ofthe passions appears in book 2 ofhis Treatise (1739), and, in shorter form, in his "Dissertation on the Passions" originally from Four Dissertations (1757).1 When the "Dissertation" first appeared, two reviews criticized Hume's theory for being unoriginal. The first appearing review, which was in the Literary Magazine, says of the "Dissertation" that "we do not perceive (...) any thing new. This we should notmentionifwe were not talking ofan authorfond ofnovelty."2 The Critical Review opens its account noting similarly that "in our opinion [the "Dissertation"] contains nothing new or entertaining on the occasion." After presenting excerpts, the reviewer concludes: "This whole dissertation, to say the truth, appears to us very trite and superficial; and unworthy of so eminent a writer. But no authors are always equal to themselves."3 Hume, by contrast, believed that his account of the indirect passions, which dominates both book 2 and the "Dissertation," was unique.4 William Rose, in his review of the "Dissertation" in the Monthly Review, agrees with Hume, noting that "[h]is theory depends entirely on the double relations of sentiments and ideas, and the mutual assistance which these relations lend to each other. What he says upon the subject, is extremely ingenious, and deserves the philosophical reader's attentive perusal."5 Few today would dispute the uniqueness ofHume's account ofthe indirect passions. Why, though, did two reviewers consider Hume's theory unoriginal? Part of the answer rests in the degree to which Hume's general classification of the passions follows traditional classifications. By understanding how Hume was in line with tradition, his uniqueness may be better appreciated. I will first sketch the traditional classifications of the passions. Second, I will draw comparisons between aspects of Hume's classification and other Enlightenment accounts. Finally, I will criticize the interpretations of Hume's classification offered by Kemp Smith, Ardal, and Loeb, and suggestwhatIbelieve is the most textually soundclassification. In each of these sections, my focus is on taxonomy. However, since many divisions of the passions derive from the psychological mechanisms which produce various passions, some account will be given of these operations. Volume XVIII Number 1 JAMES FIESER Traditional Classifications ofthe Passions The passions have been traditionally understood as disturbances ofthe mind or soul, the key ones beinglove, hate,joy, grief, hope, fear, desire, and aversion.6At therisk ofover-simplification, afairlyunified account ofthe passions can be found beginning with Plato and lasting until the mid-nineteenth century. One feature of this tradition is that the passions fall into positive and negative classes. This is first noted by Aristotle who argues that the passions are "feelings that are accompanied by pleasure or pain."7 Following Aristotle, most accounts divide the passions in reference to good or bad objects and experiences. Good experiences, such as dining, are pleasing, whereas bad experiences, such as illness, are displeasing. Consequently, passions such as joy and griefare mirror images according to the good (pleasing) or bad (displeasing) nature of the experience. A second feature of most theories is that there is a small foundational class of passions which gives rise to others through variation. The most popular foundational set includes four:joy, sorrow, hope, and fear. Although the earliest reference to these four is by Plato (Laches 191C), Zeno of Citium and the Stoics are attributed with developing a theory of the passions based on these. The fullest surviving account ofthe Stoic theory is given by Cicero in his Tusculan Disputations.8 In Cicero's discussion, the four most primitive passions are joy (laetitia), grief (aegritudo), desire (cupiditas or libido), and fear (metus). Joy and desire are the result of good circumstances, whereas grief and fear are the result of evil. Further, joy and griefresult when a circumstance or object is actually present, in contrast to desire and fear which arise when one anticipates a future circumstance. The division is as follows: Present Anticipated Good Object joy desire Evil Object grief fear In Roman and medieval philosophy, the Stoic division of the passions was widely endorsed by writers such as Virgil, Augustine, and Boethius.9With Thomas Aquinas, though, an alternative classification arose. Thomasrecognized... (shrink)

This paper addresses the problem of Twitter sentiment analysis through a hybrid approach in which SentiWordNet (SWN)-based feature vector acts as input to the classification model Support Vector Machine. Our main focus is to handle lexical modifier negation during SWN score calculation for the improvement of classification performance. Thus, we present naive and novel shift approach in which negation acts as both sentiment-bearing word and modifier, and then we shift the score of words from SWN based (...) on their contextual semantic, inferred from neighbouring words. Additionally, we augment negation accounting procedure with a few heuristics for handling the cases in which negation presence does not necessarily mean negation. Experimental results show that the contextual-based SWN feature vector obtained through shift polarity approach alone led to an improved Twitter sentiment analysis system that outperforms the traditional reverse polarity approach by 2–6%. We validate the effectiveness of our hybrid approach considering negation on benchmark Twitter corpus from SemEval-2013 Task 2 competition. (shrink)

More and more tourists are sharing their travel feelings and posting their real experiences on the Internet, generating tourism big data. Online travel reviews can fully reflect tourists’ emotions, and mining and analyzing them can provide insight into the value of them. In order to analyze the potential value of online travel reviews by using big data technology and machine learning technology, this paper proposes an improved support vector machine algorithm based on travel consumer sentiment analysis and builds an (...) Hadoop Distributed File System system based on Map-Reduce model. Firstly, Internet travel reviews are pre-processed for sentiment analysis of the review text. Secondly, an improved SVM algorithm is proposed based on the main features of linear classification and kernel functions, so as to improve the accuracy of sentiment word classification. Then, HDFS data nodes are deployed on the basis of Hadoop platform with the actual tourism application context. And based on the Map-Reduce programming model, the map function and reduce function are designed and implemented, which greatly improves the possibility of parallel processing and reduces the time consumption at the same time. Finally, an improved SVM algorithm is implemented under the built Hadoop platform. The test results show that online travel reviews can be an important data source for travel big data recommendation, and the proposed method can quickly and accurately achieve travel sentiment classification. (shrink)

The number of comments/reviews for movies is enormous and cannot be processed manually. Therefore, machine learning techniques are used to efficiently process the user’s opinion. This research work proposes a deep neural network with seven layers for movie reviews’ sentiment analysis. The model consists of an input layer called the embedding layer, which represents the dataset as a sequence of numbers called vectors, and two consecutive layers of 1D-CNN for extracting features. A global max-pooling layer is used to reduce (...) dimensions. A dense layer for classification and a dropout layer are also used to reduce overfitting and improve generalization error in the neural network. A fully connected layer is the last layer to predict between two classes. Two movie review datasets are used and widely accepted by the research community. The first dataset contains 25,000 samples, half positive and half negative, whereas the second dataset contains 50,000 specimens of movie reviews. Our neural network model performs sentiment classification among positive and negative movie reviews called binary classification. The model achieves 92% accuracy on both datasets, which is more efficient than traditional machine learning models. (shrink)

Sentiment analysis has been widely used in text mining of social media to discover valuable information from user reviews. Sentiment lexicon is an essential tool for sentiment analysis. Recent research studies indicate that constructing sentiment lexicons for special domains can achieve better results in sentiment analysis. However, it is not easy to construct a sentiment lexicon for a specific domain because most current methods highly depend on general sentiment lexicons and complex linguistic rules. (...) In this paper, the construction of sentiment lexicon is transformed into a training-optimization process. In our scheme, the accuracy of sentiment classification is used as the optimization objective. The candidate sentiment lexicons are regarded as the individuals that need to be optimized. Then, two genetic algorithms are specially designed to adjust the values of sentiment words in lexicon. Finally, the best individual evolved in the presented genetic algorithms is selected as the sentiment lexicon. Our method only depends on some labelled texts and does not need any linguistic knowledge or prior knowledge. It provides a simple and easy way to construct a sentiment lexicon in a specific domain. Experiment results show that the proposed method has good flexibility and can generate high-quality sentiment lexicon in specific domains. (shrink)

THIS paper is an effort to bring together two issues bearing on the moral philosophy of Hume. First, an effort will be made to interpret and clarify the role of general rules in Hume’s account of moral judgment. Second, the proper classification of the moral sentiments according to categories made familiar by studies in the philosophy of mind will be offered. The collective bearing of these two matters on the analysis of Hume’s moral theory will then be explored.

Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. During the past years several techniques to detect unsolicited emails have been developed. This work provides means to validate the hypothesis that the identification of the email messages’ intention can be approached by sentiment analysis and personality recognition techniques. These techniques will provide new features that improve current spam classification techniques. We combine personality recognition and sentiment analysis techniques to analyse email (...) content. We enrich a publicly available dataset adding these features, first separately and after in combination, of each message to the dataset, creating new datasets. We apply several combinations of the best email spam classifiers and filters to each dataset in order to compare results. (shrink)

Emotion-based sentimental analysis has recently received a lot of interest, with an emphasis on automated identification of user behavior, such as emotional expressions, based on online social media texts. However, the majority of the prior attempts are based on traditional procedures that are insufficient to provide promising outcomes. In this study, we categorize emotional sentiments by recognizing them in the text. For that purpose, we present a deep learning model, bidirectional long-term short-term memory, for emotion recognition that takes into account (...) five main emotions. We use our experimental assessments on the emotion dataset to accomplish the emotion categorization job. The datasets were evaluated and the findings revealed that, when compared to state-of-the-art methodologies, the proposed model can successfully categorize user emotions into several classifications. Finally, we assess the efficacy of our strategy using statistical analysis. This research’s findings help firms to apply best practices in the selection, management, and optimization of policies, services, and product information. (shrink)

Millions of memes are created and shared every day on social media platforms. Memes are a great tool to spread humour. However, some people use it to target an individual or a group generating offensive content in a polite and sarcastic way. Lack of moderation of such memes spreads hatred and can lead to depression like psychological conditions. Many successful studies related to analysis of language such as sentiment analysis and analysis of images such as image classification have (...) been performed. However, most of these studies rely only upon either one of these components. As classifying meme is one problem which cannot be solved by relying upon only any one of these aspects, the present work identifies, addresses, and ensembles both the aspects for analyzing such data. In this research, we propose a solution to the problems in which the classification depends on more than one model. This paper proposes two different approaches to solve the problem of identifying hate memes. The first approach uses sentiment analysis based on image captioning and text written on the meme. The second approach is to combine features from different modalities. These approaches utilize a combination of glove, encoder-decoder, and OCR with Adamax optimizer deep learning algorithms. Facebook Challenge Hateful Meme Dataset is utilized which contains approximately 8500 meme images. Both the approaches are implemented on the live challenge competition by Facebook and predicted quite acceptable results. Both approaches are tested on the validation dataset, and results are found to be promising for both models. (shrink)

In this paper, a special type of polysemantic words, that is, words with multiple meanings for the same part of speech, are analyzed under the name of neutrosophic words. These words represent the most dif cult cases for the disambiguation algorithms as they represent the most ambiguous natural language utterances. For approximate their meanings, we developed a semantic representation framework made by means of concepts from neutrosophic theory and entropy measure in which we incorporate sense related data. We show the (...) advantages of the proposed framework in a sentiment classification task. (shrink)

This study mainly focuses on the emotion analysis method in the application of psychoanalysis based on sentiment recognition. The method is applied to the sentiment recognition module in the server, and the sentiment recognition function is effectively realized through the improved convolutional neural network and bidirectional long short-term memory model. First, the implementation difficulties of the C-BiL model and specific sentiment classification design are described. Then, the specific design process of the C-BiL model is introduced, (...) and the innovation of the C-BiL model is indicated. Finally, the experimental results of the models are compared and analyzed. Among the deep learning models, the accuracy of the C-BiL model designed in this study is relatively high irrespective of the binary classification, the three classification, or the five classification, with an average improvement of 2.47% in Diary data set, 2.16% in Weibo data set, and 2.08% in Fudan data set. Therefore, the C-BiL model designed in this study can not only successfully classify texts but also effectively improve the accuracy of text sentiment recognition. (shrink)

Linguistic communication is an important part of the cross-cultural perspective, and linguistic textual emotion recognition is a key massage in interpersonal communication. Spanish is the second largest language system in the world. The purpose of this paper is to identify the emotional features in Spanish texts. The improved BiLSTM framework is proposed. We select three widely used Spanish dictionaries as the datasets for our experiments, and then we finally obtain text sentiment classification results through text preprocessing, text emotion (...) feature extraction, text topic detection, and emotion classification. We inserted the attention mechanism in the improved BiLSTM framework. It enables the shared feature encoder to obtain weighted representation results in the extraction of emotion features, which enhances the generalization ability of the model for text emotion feature recognition. Experimental results demonstrate that our approach performs better for specialized Spanish dictionary datasets. In terms of emotion recognition accuracy, the average value is as high as 76.21%. The overall performance outperforms current comparable machine learning methods and convolutional neural network methods. (shrink)

This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. An evolutionary algorithm is applied to select the most informative features from an initial set of 2550 EEG statistical features. Optimisation of a Multilayer Perceptron is performed with an evolutionary approach before classification to estimate the best hyperparameters of the network. Deep learning and tuning with (...) Long Short-Term Memory are also explored, and Adaptive Boosting of the two types of models is tested for each problem. Three experiments are provided for comparison using different classifiers: one for attention state classification, one for emotional sentiment classification, and a third experiment in which the goal is to guess the number a subject is thinking of. The obtained results show that an Adaptive Boosted LSTM can achieve an accuracy of 84.44%, 97.06%, and 9.94% on the attentional, emotional, and number datasets, respectively. An evolutionary-optimised MLP achieves results close to the Adaptive Boosted LSTM for the two first experiments and significantly higher for the number-guessing experiment with an Adaptive Boosted DEvo MLP reaching 31.35%, while being significantly quicker to train and classify. In particular, the accuracy of the nonboosted DEvo MLP was of 79.81%, 96.11%, and 27.07% in the same benchmarks. Two datasets for the experiments were gathered using a Muse EEG headband with four electrodes corresponding to TP9, AF7, AF8, and TP10 locations of the international EEG placement standard. The EEG MindBigData digits dataset was gathered from the TP9, FP1, FP2, and TP10 locations. (shrink)

The electroencephalogram is the most common method used to study emotions and capture electrical brain activity changes. Long short-term memory processes the temporal characteristics of data and is mostly used for emotional text and speech recognition. Since an EEG involves a time series signal, this article mainly studied the introduction of LSTM for emotional EEG recognition. First, an ALL-LSTM model with a four-layered LSTM network was established in which the average accuracy rate for emotional classification reached 86.48%. Second, four (...) EEG characteristics were extracted via the wavelet transform using the LSTM-based sentiment classification network. The experimental results showed that the best average classification accuracy of these four features was 73.48%. This was 13% lower than in the ALL-LSTM model, indicating that inappropriate feature extraction methods could destroy the timing of EEG signals. LSTM can be used to thoroughly examine EEG signal timing and preprocessed EEG data. The accuracy and stability of the ALL-LSTM model are significantly superior to those of the WT-LSTM model. The result showed that the process of emotion generation based on EEG is sequential. Compared with EEG emotion extraction using WT, the raw EEG signal’s timing is more suitable for the LSTM network. (shrink)

Hume describes “mental geography” as the endeavor to know “the different operations of the mind, to separate them from each other, to class them under their proper heads, and to correct all that seeming disorder, in which they lie involved, when made the object of reflection and enquiry.” While much has been written about his geography of thought in Treatise Book 1, relatively little has been written about his geography of feeling in Books 2 and 3, with the result that (...) there has been considerable puzzlement and disagreement about the meaning and grounds of many of his central theses about the passions, action, and morals. My endeavor in this chapter is to remove some common sources of perplexity about his classification of the operations of feeling “under their proper heads” in that work. I begin by explaining his three highest-level distinctions bearing on this terrain: that between impressions and ideas; that between original impressions and secondary impressions; and that between the passions and the other emotions. In order to understand this third distinction, I explain his three different senses of the term ‘emotion’ and the relations among them. I ill then examine five different kinds of secondary impressions that he recognizes. These are: (1) sensible agitations; (2) feelings of or from mental operations; (3) volitions; (4) the passions (including motives); and (5) sentiments of taste. The broad outlines of the resulting geography are mapped out in a chart at the end. (shrink)

Dans sa Théorie des sentiments moraux (1759), Adam Smith classe les passions en trois catégories : passions sociales, asociales, égoïstes. Cette classification résulte directement de leur capacité à susciter ou non la sympathie. Les passions sociales apparaissent ainsi comme les plus propres à susciter un écho sympathique. La question à laquelle tente de répondre l'article est de savoir pourquoi ces mêmes passions sociales sont qualifiées par A. Smith de « naturellement musicales ». L'utilisation du concept de sympathie dans le (...) domaine musical est fréquente aux XVIIème et XVIIIème siècles, mais l'hypothèse avancée ici est que le lien est plus profond chez A. Smith. La sympathie met en effet en évidence une qualité d'ordre à la fois esthétique et morale inhérente à certaines passions, leur « convenance » (propriety) par opposition aux passions « discordantes ». Ces passions, produisant une superposition d'échos sympathiques comparables aux harmoniques d'un ton fondamental, sont les plus susceptibles d'être imitées par la musique, si l'on tient compte de la théorie esthétique originale formulée par A. Smith, pour qui la beauté des arts imitatifs ne tient pas à l'illusion mais au contraire à l'écart entre l'imitation et son objet. (shrink)

Dans sa Théorie des sentiments moraux (1759), Adam Smith classe les passions en trois catégories : passions sociales, asociales, égoïstes. Cette classification résulte directement de leur capacité à susciter ou non la sympathie. Les passions sociales apparaissent ainsi comme les plus propres à susciter un écho sympathique. La question à laquelle tente de répondre l'article est de savoir pourquoi ces mêmes passions sociales sont qualifiées par A. Smith de « naturellement musicales ». L'utilisation du concept de sympathie dans le (...) domaine musical est fréquente aux XVIIème et XVIIIème siècles, mais l'hypothèse avancée ici est que le lien est plus profond chez A. Smith. La sympathie met en effet en évidence une qualité d'ordre à la fois esthétique et morale inhérente à certaines passions, leur « convenance » (propriety) par opposition aux passions « discordantes ». Ces passions, produisant une superposition d'échos sympathiques comparables aux harmoniques d'un ton fondamental, sont les plus susceptibles d'être imitées par la musique, si l'on tient compte de la théorie esthétique originale formulée par A. Smith, pour qui la beauté des arts imitatifs ne tient pas à l'illusion mais au contraire à l'écart entre l'imitation et son objet. (shrink)

This is a brief review of the Rasa theory of Indian aesthetics and the works I have done on the same. A major source of the Indian system of classification of emotional states comes from the ‘Natyasastra’, the ancient Indian treatise on the performing arts, which dates back to the 2nd Century AD (or much earlier, pg. LXXXVI: Natyasastra, Ghosh, 1951). The ‘Natyasastra’ speaks about ‘sentiments’ or ‘Rasas’ (pg.102: Natyasastra, Ghosh, 1951) which are produced when certain ‘dominant states’ (sthayi (...) Bhava), ‘transitory states’ (vyabhicari Bhava) and ‘temperamental states’ (sattvika Bhava) of emotions come together (pgs.102, 105: Natyasastra, Ghosh, 1951). This Rasa theory, which is still widely followed in classical Indian performing arts, classifies eight Rasas or sentiments which are: Sringara (erotic), Hasya (comic), Karuna (pathetic), Raudra (furious), Vira (heroic), Bhayanaka (terrible), Bibhatsa (odious) and Adbhuta (marvellous). There was a later addition of the ninth sentiment or Rasa called Santa (peace) in later Sanskrit poetics (pg.102: Natyasastra, Ghosh, 1951). According to ancient Indian aesthetics (especially in the context of Bharatas’ ‘Natyasastra’, Anandavardhana’s ‘Dhvanyaloka’ and Abhinavagupta’s ‘Abhinavabharati’), ‘Rasa’ is the relishable state of elemental human emotions called ‘Bhavas’. Bharata’s ‘Natyasastra’ originally spoke of eight Rasas. The concept of the 9th Rasa was a later interpolation by the Kashmiri Shaivist Abhinavagupta (10th Century AD) and also his predecessor Anandavardhana (9th Century AD). Abhinavagupta extends the eight Rasas by adding the concept of the Santa Rasa which he regards as the essence of all Rasas. It is this 9th Rasa which according to Abhinavagupta lets the Rasika attain the aesthetic detachment and savour the essences of all other Rasas and therefore the true aesthetic delight. The introduction of 9th Rasa integrates the concepts of Bharata’s Rasasutra and Patanjali’s Yoga theory – the detachment necessary to introspect inwards into the inherent state of freedom and bliss (aesthetic consciousness). (shrink)

This is an 18,500 word bibliography of philosophical scholarship on Beauty which was published online in the Oxford Bibliographies Online. The entry includes an Introduction of 800 words, 21 x 400-word sub-themes and 168 annotated references. INTRODUCTION Philosophical interest in beauty began with the earliest recorded philosophers. Beauty was deemed to be an essential ingredient in a good life and so what it was, where it was to be found and how it was to be included in a life were (...) prime considerations. The way beauty has been conceived has been influenced by an author’s other philosophical commitments, metaphysical, epistemological and ethical and such commitments reflect the historical and cultural position of the author. For example, beauty is a manifestation of the divine on earth to which we respond with love and adoration; beauty is a harmony of the soul which we achieve through cultivating feeling in a rational and tempered way; beauty is an idea raised in us by certain objective features of the world; beauty is a sentiment which can nonetheless be cultivated to be appropriate to its object; beauty is the object of a judgment by which we exercise the social, comparative and inter-subjective elements of cognition and so on. Such views on beauty not only reveal underlying philosophical commitments but also reflect positive contributions to understanding the nature of value and the relation of mind and world. One way to distinguish between beauty theories is according to the conception of the human being that they assume or imply, for example, where they fall on the continuum from determinism to free will, ungrounded notions of compatibilism notwithstanding. For example, theories at the latter end might carve out a sense of genuine innovation and creativity in human endeavours while at the other end of the spectrum authors may conceive of beauty as an environmental trigger for consumption, procreation or preservation in the interests of the individual. Treating beauty experiences as in some respect intentional, characterises beauty theory prior to the twentieth century and since, mainly in historically inspired writing on beauty. On the other hand, treating beauty as affect or sensation has always had its representatives and is most visible today in evolutionary inspired accounts of beauty (though not all evolutionary accounts fit this classification). Beauty theory falls under some combination of metaphysics, epistemology, meta-ethics, aesthetics and psychology. While in the twentieth century beauty was more likely to be conceived as an evaluative concept for art, recent philosophical interest in beauty can again be seen to exercise arguments pertaining to metaphysics, epistemology, meta-ethics, philosophy of meaning and language in addition to philosophy of art and environmental aesthetics. (shrink)

There seems to be a strong sentiment in pre-philosophical moral thought that actions can be morally valuable without at the same time being morally required. Yet Kant, who takes great pride in developing an ethical system firmly grounded in common moral thought, makes no provision for any such extraordinary acts of virtue. Rather, he supports a classification of actions as either obligatory, permissible or prohibited, which in the eyes of his critics makes it totally inadequate to the facts (...) of morality. The related idea of uncommonly grand and noble deeds is frequently dismissed by Kant as high-.own emotional nonsense. Such considerations give rise to the fear that actions intuitively classed as morally commendable but not required must be re-classified as commands of duty by Kant, making his ethical theory as unbearably demanding as direct utilitarianism. The paper divides into three sections: (1) an examination of the nature of moral goodness from a meta-ethical angle that introduces some passages from Kant's writings presenting strong theoretical evidence against the case for supererogatory action; (2) a critique of Thomas Hill's suggestion that within the category of wide duty we can accommodate some of the main features of actions classified as supererogatory in other ethical systems; concluding that, contra Hill, there are no actions of wide duty that can be so characterized in any significant sense; and (3) a final discussion of the problem of how demanding the requirements of Kantian ethical theory really are. (shrink)

This article discusses the paradox of exclusion/inclusion: U.S. health policy prohibits Latinos who fall under certain classifications from accessing health services and insurance yet permits them to be human subjects in health research. We aim to advance the discussion of health research ethics post the Tuskegee syphilis experiment in Latinos by (a) tracing the impacts of policy exclusion and the social context of anti-Latino sentiment on Latinos' low participation rates in health research and inequitable access to treatment modalities; (b) (...) challenging researchers to address social sources of vulnerabilities; and (c) offering recommendations on adapting a social justice ethical stance to address these challenges, which are part of the Tuskegee Study legacy. (shrink)

As one of the key subjects of multi-center governance of environmental concerns, public perception is crucial in forming and implementing environmental policy. Based on data science research theory and the original theory of public perception, this study proposes a research framework to analyze environmental policy through network text analysis. The primary contents are bidirectional encoder representation from transformers-convolution neural network sentiment tendency analysis, word frequency characteristic analysis, and semantic network analysis. The realism of the suggested framework is demonstrated by (...) using the waste classification policy as an example. The findings indicate a substantial relationship between perceived subject participation and policy pilot areas and that perceived subject participation is repeating. On this premise, specific recommendations are made to encourage policy implementation. (shrink)

[Introduction]: Curiosity is now widely regarded, with some justification, as a vital ingredient of the inquiring mind and, more particularly, as a crucial virtue for the practitioner of the pure sciences. We have become accustomed to associate curiosity with innocence and, in its more mature manifestations, with the pursuit of truth for its own sake. It was not always so. The sentiments expressed in Sir John Davies's poem, published on the eve of the seventeenth century, paint a somewhat different picture. (...) To seek knowledge with no particular end in mind was to indulge in "fruitlesse curiositie," while the "desire to know" was associated with those catastrophic events that took place at the dawn of history in the Garden of Eden and with the ensuing curse that fell upon succeeding generations. Davies's poem neatly sets out two of the chief impediments to the advancement of learning in seventeenth-century England: the fact that the Genesis narrative attributes the Fall of the human race to the desire for knowledge, and the moral disapprobation associated with the vice of curiosity. In short, the traditional classification of curiosity amongst the vices and its complicity in the commission of the first sin represented a major obstacle to early modern projects to enlarge human learning. This essay will explore the changing fortunes of curiosity, from its construction as an intellectual vice in the patristic era to its subsequent transformation, over the course of the seventeenth century, to a virtue. Particular attention will be paid to the way in which Francis Bacon dealt with prevailing conceptions of curiosity and forbidden knowledge and how he modified an existing view of the moral legitimacy of knowledge of nature in order to provide rhetorical justification for his proposed instauration of learning. This change in the status of knowledge of nature, initiated by Bacon and promoted by his successors, highlights the morally charged character of early modem debates over the status of natural philosophy and the particular virtues required of its practitioners. As we shall see, the rehabilitation of curiosity was a crucial element in the objectification of scientific knowledge and led to a shift of focus away from the moral qualities of investigators and the propriety of particular objects of knowledge to specific disciplines, procedures, and methods. (shrink)

The origins of field guides and other plant identification manuals have been poorly understood until now because little attention has been paid to 18th century botanical identification guides. Identification manuals came to have the format we continue to use today when botanical instructors in post-Revolutionary France combined identification keys (step-wise analyses focusing on distinctions between plants) with the "natural method" (clustering of similar plants, allowing for identification by gestalt) and alphabetical indexes. Botanical works featuring multiple but linked techniques to enable (...) plant identification became very popular in France by the first decade of the 19th century. British botanists, however, continued to use Linnaeus's sexual system almost exclusively for another two decades. Their reluctance to use other methods or systems of classification Can be attributed to a culture suspicious of innovation, anti-French sentiment and the association of all things Linnaean with English national pride, fostered in particular by the President of the Linnean Society of London, Sir James Edward Smith. The British aversion to using multiple plant identification technologies in one text also helps explain why it took so long for English botanists to adopt the natural method, even after several Englishmen had tried to introduce it to their country. Historians of ornithology emphasize that the popularity of ornithological guides in the 19th and 20th centuries stems from their illustrations, illustrations made possible by printing technologies that improved illustration quality and reduced costs. Though illustrations are the most obvious features of late 19th century and 20th century guides, the organizational principles that make them functional as identification devices come from techniques developed in botanical works in the 18th century. (shrink)

The origins of field guides and other plant identification manuals have been poorly understood until now because little attention has been paid to 18th century botanical identification guides. Identification manuals came to have the format we continue to use today when botanical instructors in post-Revolutionary France combined identification keys with the "natural method" and alphabetical indexes. Botanical works featuring multiple but linked techniques to enable plant identification became very popular in France by the first decade of the 19th century. British (...) botanists, however, continued to use Linnaeus's sexual system almost exclusively for another two decades. Their reluctance to use other methods or systems of classification Can be attributed to a culture suspicious of innovation, anti-French sentiment and the association of all things Linnaean with English national pride, fostered in particular by the President of the Linnean Society of London, Sir James Edward Smith. The British aversion to using multiple plant identification technologies in one text also helps explain why it took so long for English botanists to adopt the natural method, even after several Englishmen had tried to introduce it to their country. Historians of ornithology emphasize that the popularity of ornithological guides in the 19th and 20th centuries stems from their illustrations, illustrations made possible by printing technologies that improved illustration quality and reduced costs. Though illustrations are the most obvious features of late 19th century and 20th century guides, the organizational principles that make them functional as identification devices come from techniques developed in botanical works in the 18th century. (shrink)

This essay traces threads of nationalist sentiment from three different historical periods of 19th Century Britain, to pre-World War II Germany, to the United States of post-9/11, and evidences how even most noble expressions of nationalism and patriotism might be corrupted by the dominant cultural hegemonies. The term “nationalism” is frequently considered a synonym of “patriotism.” Although the terms emphasize the value of self-determination and solidarity among members of nation-states, nationalism is the governing principle that unifies disparate social entities (...) through a common national identity that is made accessible to many but not all members of the public. Patriotism is the attitudes and behaviors we exhibit within a public forum to validate our placement within national discourse. How we synchronize nationalist agendas with patriotic fervor determines our success in nation-building and in the creation of a global community responsive to needs and interests of our human condition, a condition that dwarfs and precedes all other ideologies and modes of classification. The prefigurations of culture and society predispose us toward assuming a normalized subjectivity that predicts potential patterns of behavior and attitudes in response to hegemonic domination. In seeking to refine and preserve national identity, each of these societies has embraced the replication of hegemony and situated oppositional narratives within coercive doctrines of patriotism and national unity. (shrink)

Communities, policy actors and conservationists benefit from understanding what institutions and land management regimes promote ecosystem services like carbon sequestration and biodiversity conservation. However, the definition of success depends on local conditions. Forests’ potential carbon stock, biodiversity, and rate of recovery following disturbance are known to vary with a broad suite of factors including temperature, precipitation, seasonality, species’ traits and land use history. Methods like forest changes over time , and comparison with 'pristine' reference forests have been proposed to compare (...) the structure and biodiversity of forests in the face of underlying differences. However, data from previous visits or reference forests may be unavailable or costly to obtain. Here, we introduce a new metric of locally weighted forest inter-comparison to mitigate the above shortcomings. This method is applied to an international database of nearly 300 community forests, and compared with previously published techniques. It is particularly suited to large databases where forests may be compared among one another. Further, it avoids problematic comparisons with old-growth forests which may not resemble the goal of forest management. In most cases, the different methods produce broadly congruent results, suggesting that researchers have the flexibility to compare forest conditions using whatever type of data is available. Forest structure and biodiversity are shown to be independently measurable axes of forest condition, although users’ and foresters’ estimations of seemingly unrelated attributes are highly correlated, perhaps reflecting an underlying sentiment about forest condition. These findings contribute new tools for large-scale analysis of ecosystem condition and natural resource policy assessment. Although applied here to forestry, these techniques have broader applications to classification and evaluation problems using crowdsourced or repurposed data for which baselines or external validations are not available. (shrink)

This research aims to analyze the influencing factors of migrant children’s education integration based on the convolutional neural network algorithm. The attention mechanism, LSTM, and GRU are introduced based on the CNN algorithm, to establish an ALGCNN model for text classification. Film and television review data set, Stanford sentiment data set, and news opinion data set are used to analyze the classification accuracy, loss value, Hamming loss, precision, recall, and micro-F1 of the ALGCNN model. Then, on the (...) big data platform, data in the Comprehensive Management System of Floating Population and Rental Housing, Student Status Information Management System, and Student Information Management System of Beijing city are taken as samples. The ALGCNN model is used to classify and compare related data. It is found that in the MR, STT, and MPQA data sets, the classification accuracy and loss value of the ALGCNN model are better than other algorithms. HL is the lowest, the Pre is second only to the BERT algorithm, and the Re and F1 are both higher than other algorithms. From 2015 to 2019, the number of migrant children in different grades of elementary school shows a gradual increase. Among migrant children, the number of migrant children from other counties in this province is evidently higher than the number of migrant children from other provinces. Among children of migrant workers, the number of immigrants from other counties in this province is also notably higher than the number of immigrants from other provinces. With the gradual increase in the years, the proportion of township-level expenses shows a gradual decrease, whereas the proportion of district and county-level expenses shows a gradual increase. Moreover, the accuracy of the ALGCNN model in migrant children and local children data classification is 98.6 and 98.9%, respectively. The proportion of migrant children in the first and second grades of a primary school in Beijing city is obviously higher than that of local children. The average final score of local children was greatly higher than that of migrant children, whereas the scores of migrant children’s listening methods, learning skills, and learning environment adaptability are lower, which shows that an effective text classification model is established based on the CNN algorithm. In short, the children’s education costs, listening methods, learning skills, and learning environment adaptability are the main factors affecting migrant children’s educational integration, and this work provides a reference for the analysis of migrant children’s educational integration. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Allegory and the Spaces of LoveOscar Martín (bio)Writing about Spanish sentimental fiction from 1450 to 1550 is not an easy task, as we are discussing a genre with a difficult theoretical configuration. The investigation of sentimental fiction, however, has been sorting out the classifications that applied to a hodgepodge of works previously labeled as “sentimental novel” (“novela sentimental”). This label, once attached uncritically to a bunch of heterogeneous texts (...) that shared such intangibles as “loving focus” or “prevalence of psychological description over narratives,” has been applied more consistently nowaday, thanks in part to the scholarly efforts started in the 1980s like those of Martínez Jiménez and Muñoz Marquina (1982), and Martínez Latre (1989).1 Using some of these research efforts, Alan Deyermond has codified the genre accurately:Brevity; focus on psychological interest over external action; a tragic vision of love; autobiography (first-person narration or a narrator as a character) and the insertion of letters or poems (or, often, both) into the narration.[77]2Within this scholarly categorization, Regula Rohland de Langbehn has been pivotal in offering—first in 1986, and more recently in 1999—a threefold scheme in the development of the genre she labels as “sentimental novel”: a first group chronologically of the genre would be represented by Siervo libre de amor and Sátira de felice e infelice vida, both works marked by the influence of cancionero poetry—specially in the allegorical structuring and in the characterization of love, and by other subjects being limited to an abstract and general analysis of emotions. Both works also present a debate over the moral value of love. A second group would gravitate around Triste deleytacion and the works of Diego de San Pedro and Juan de Flores, works that show a wider range of topics and the impact of a broader generic textuality like cancionero poetry and such chivalric novels as Tirant. Finally, she distinguishes a third group whose main characteristic is the imprint of Celestina’s influence on both the narrative surface and its thematic approach. In the same vein, Vicenta Blay Manzanera has taken up this threefold scheme, dividing the genre into “the creation of the paradigm” (“la creación del paradigma”) the climactic stage, and the downfall and disarticulation of the narrative sentimental system” (“la fase climática” and “el tercero la fase de declive o desintegración del paradigma”) [“La conciencia genérica” 221]. [End Page 132]Just as Rohland de Langbehn’s works had at least settled down the arguments about the existence of a sentimental novelistic genre, however, medieval Hispanic scholarship has been shaken by an entrenched debate over not only the identification of this genre (novel or fiction) but whether the genre even existed at all. It was Antonio Cortijo Ocaña who, while editing a critical cluster in La Corónica on sentimental fiction, opened the door to some scholars such as Weissberger who voiced their skepticism over the generic nature of sentimental prose, a skepticism already present in an innovative volume published by Gwara and Gerli in 1997. This skeptical position was also supported by Cortijo Ocaña himself, who in 2001 published a monumental work in which, although using the generic term as a departure point, he ended up suggesting the difficulty of defining it, therefore jettisoning it. This position in turn was contested by Rohland de Langbehn, who in 2002 defended the validity of both the existence of a genre and its name novela sentimental, a position that has sparked a new round of replies in a La Corónica forum in 2003.In this debate, I would join today’s minority position on the existence of a sentimental genre, because, as I explained in my 2001 review of Rohland de Langbehn’s book and as I find convincingly argued in her 2002 contribution, there are internal traits within sentimental fictional texts that do not appear together in other sentimental generic texts [139]. In addition, once we take into account the obvious intertextuality of those sentimental texts, as Blay Manzanera has shown [“La conciencia genérica”], and the overutilization of central motifs in the configuration of love’s debate, we... (shrink)

“Career value” is the name of a kind of value I used (or perhaps I coined) in my classification of value according to good things in life based on the law of nonreplaceability. I classify value into seven classes: (1) health value, (2) sentimental value, (3) economic value1, (4) belief value, (5) environmental value, (6) social value, and (7) career value. Career value refers to the extra value of the most important work, which one wants to do and actually (...) does in one’s life time, for oneself. In Section 2, I explain the nature of career value, which is different from the natures of all other values. In Section 3, I discuss various career values themselves. Career value has several different forms, depending on the nature and size of career. Finally, I conclude that, except for economic value3, which isunsuitable and unreasonable to be a career value, the pursuit of any kind of a nonmaterial career value is a good thing and conforms to the maximization of social utility in utilitarianism. (shrink)

Emotional recognition has arisen as an essential field of study that can expose a variety of valuable inputs. Emotion can be articulated in several means that can be seen, like speech and facial expressions, written text, and gestures. Emotion recognition in a text document is fundamentally a content-based classification issue, including notions from natural language processing (NLP) and deep learning fields. Hence, in this study, deep learning assisted semantic text analysis (DLSTA) has been proposed for human emotion detection using (...) big data. Emotion detection from textual sources can be done utilizing notions of Natural Language Processing. Word embeddings are extensively utilized for several NLP tasks, like machine translation, sentiment analysis, and question answering. NLP techniques improve the performance of learning-based methods by incorporating the semantic and syntactic features of the text. The numerical outcomes demonstrate that the suggested method achieves an expressively superior quality of human emotion detection rate of 97.22% and the classification accuracy rate of 98.02% with different state-of-the-art methods and can be enhanced by other emotional word embeddings. (shrink)

This manuscript constructs an intelligent sentiment analysis and marketing model for bed and breakfast consumption based on a behavioral psychology perspective. Based on the LDA theme model, the theme features and keywords of the reviews covering user feedback are explored from the text data, and the theme framework of user sentiment perception is constructed by combining previous literature on user perception in the B&B market, and the themes of user online reviews are summarized in four dimensions: practical, sensory, (...) cognitive, and emotional components of user experience. In this manuscript, GooSeeker software was selected for data crawling and ROST CM developed by Wuhan University was used for text processing. To improve the accuracy of text classification and improve the missing data, the online comment text is divided into sentences by symbols, and the text is divided into words based on sentences, and the spatial vector model and the text feature word weighting method of TF-IDF are used for vector representation, and the polynomial Bayesian classifier is called to identify the topics of sentences. The classical Theory of Planned Behavior was used to analyze the influencing factors of the willingness to consume experiential B&B tourism, and countermeasure suggestions for the development of B&B tourism were proposed based on the research findings In the empirical testing stage, a questionnaire on the willingness to consume experiential B&B tourism was designed, and web research was chosen to collect the data. SPSS20.0 was used to conduct reliability analysis, factor analysis, correlation analysis, and regression analysis on the data, and AMOS statistics were used to establish a structural equation model to verify the influence path of willingness to consume experiential B&B tourism. Finally, the moderating path of willingness to consume experiential B&B tourism was verified by using multi-group analysis. (shrink)

Résumé Dans cet article, je propose une typologie des études contemporaines relatives au troisième segment de la Ligne en République VI, en adoptant une classification des interprétations qui prend pour fil conducteur la question de la nature eidétique de l’objet de la dianoia. Le sentiment de confusion que la disparité des voies interprétatives laisse au lecteur vient de ce que les interprètes contemporains confondent l’objet spécifiquement dianoétique, qui est le γνωστόν, et le référent à la fois dianoétique et (...) noétique, qui est le νοητόν.We present here a typology of contemporary studies concerning the third segment of the Line in Republic VI, in which we adopt a classification of interpretations whose main thread is the question of the eidetic nature of the object of dianoia. The feeling of confusion with which the reader is often left is due to the disparity between some 10 different approaches where contemporary interpreters fail to distinguish between the specifically dianoetic object, which is the γνωστόν, and the referent, both dianoetic and noetic, which is the νοητόν. (shrink)

The content of a work of literature, Walter Benjamin reminds us in “The Author as Producer,” is inextricably bound up with its form. Hence, it is hardly astounding that much critical attention has been focused on the proper generic classification of Harriet E. Wilson’s Our Nig . This task, though, has not been easy. Henry Louis Gates, rediscoverer and earliest critic of Our Nig, for example, goes to great length discussing parallels between Wilson’s work and Nina Baym’s ‘overplot’ of (...) the ‘women’s novel,’ before settling on reading it as a new form of distinctly African-American lit- erature that combines “conventions of the sentimental novel with certain key conventions of the slave narratives” . Elizabeth Ammons, by contrast, places Our Nig squarely in the feminist tradition of the sentimental novel and argues that “the ideal of mother love explicit in Uncle Tom’s Cabin operates implicitly in Our Nig.” 4 2 3 Contesting Ammons’ claim, Eric Gardner asserts that Our Nig is not a ‘novel of abolition’ but “a novel about Northern racial issues, a young black woman’s bildungsroman, and, as such, is far from Uncle Tom’s Cabin.” 5 Echoing some of Gardner’s points, Elizabeth Breau contends that Our Nig “is actually satiric” and therefore gives an overly “bleak picture of northern antebellum society.” Foregrounding neither Bildung nor “ironic inversions” but the “politics of rage at work in Wilson’s tale,” Julia Stern argues that Our Nig “used the sentimental form to mask a gothic message.” 7 Rejecting Gates’ attempt to posit Our Nig as “a significant beginning of an African-American literary mode, a distinctive first in a century of firsts,” John Ernest wants to read Wilson’s work as a traditional “blend of autobiography and fiction,” hoping to ‘re-place’ it “within the racial, gender, and economic matrix of secular history.” R.J. Ellis, while accepting Gates’ assessment that Our Nig “draw[s] on the genres of sentimental fiction and abolitionist slave narrative,” stresses the ways in which the ‘hybrid’ work “fractures generic boundaries” in order to provide a “full retrieval of Frado’s pain, her experience of body politics.” Lastly, offering a reading that links Our Nig to the Puritan tradition, Elizabeth West argues that Our Nig “manipulates well-known trappings of the conversion narrative” by telling “the story of the heroine’s failed initiation into the community of earthly saints.”. (shrink)

With the deepening of globalization, brand plays an important role in determining the competitiveness of enterprises. It is worth thinking about how to quantify the brand value reasonably to achieve the purpose of improving the competitiveness of enterprises. The research of commercial brands based on emotion analysis extracts the views of consumers on the evaluation data of brand attributes, analyzes the emotional tendency of consumers' views, and then helps enterprises adjust their production strategies. The purpose of emotion analysis is to (...) judge users' views and attitudes toward goods or services by analyzing texts. In this paper, the linear support vector machine model is used to extract and study the features in sentiment analysis. Then, the brand based on the fusion model is evaluated, and the experimental conclusions are drawn: the method of fusing the depth features extracted by word vector and the named entity extracted by CRF makes the brand effect of fusing emotional factors better than the feature extraction method only using CRF named entity recognition. It is proved that the model method proposed in this paper has a certain role in actual business. Feature fusion often combines shallow model methods and fuses various shallow feature screening technologies based on word segmentation results. This paper introduces fusion features and supplements feature vectors based on the results of the deep learning word vector model. Support Vector Machine maps feature vectors to some sample points in the space, finds a plane that can realize sample classification, and maximizes the distance between the two sample points closest to the plane in two types of samples, to maximize the classification performance and improve the generalization of the model. (shrink)

This paper brings together cutting-edge, quantitative corpus methodologies and discourse analysis to explore the relationship between text complexity and subjectivity as descriptive features of opinionated language. We are specifically interested in how text complexity and markers of subjectivity and argumentation interact in opinionated discourse. Our contributions include the marriage of quantitative approaches to text complexity with corpus linguistic methods for the study of subjectivity, in addition to large-scale analyses of evaluative discourse. As our corpus, we use the Simon Fraser Opinion (...) and Comments Corpus, which comprises approximately 10,000 opinion articles and the corresponding reader comments from the Canadian online newspaper The Globe and Mail, as well as a parallel corpus of hard news articles also sampled from The Globe and Mail. Methodologically, we combine conditional inference trees with the analysis of random forests, an ensemble learning technique, to investigate the interplay between text complexity and subjectivity. Text complexity is defined in terms of Kolmogorov complexity, that is, the complexity of a text is measured based on its description length. In this approach, texts which can be described more efficiently are considered to be linguistically less complex. Thus, Kolmogorov complexity is a measure of structural surface redundancy. Our take on subjectivity is inspired by research in evaluative language, stance and Appraisal and defined as the expression of evaluation and opinion in language. Drawing on a sentiment analysis lexicon and the literature on stance markers, a custom set of subjectivity and argumentation markers is created. The results show that complexity can be a powerful tool in the classification of text into different text types, and that stance adverbials serve as distinctive features of subjectivity in online news comments. (shrink)

In response to the concern that criteriological psychiatric diagnosis, based on the DSM and ICD classifications, pigeon-holes patients, there have been calls for it to be augmented by an idiographic formulation [IDGA Workgroup, WPA 2003]. I have argued elsewhere that this is a mistake [Thornton 2008a, 2008b, 2010]. Looking back to its original proponent Wilhelm Windelband yields no clear account of the contrast between idiographic and nomothetic judgement. Abstracting from Jaspers’ account of understanding an idea of idiographic judgement based on (...) the contrast between singular and general causal relations also fails. I argue, however, that Windelband does provide a helpful clue in his remark that ‘every interest and judgement, every ascription of human value is based upon the singular and the unique... Our sense of values and all of our axiological sentiments are grounded in the uniqueness and incomparability of their object’ [Windelband 1980: 182]. This suggests a role for the idiographic not as the content of a particular kind of judgement but rather as characterising its aim. I argue that this connects to the issue of the generalisability of small scale qualitative social science research and to the critique of ‘looking away’ in moral philosophy. (shrink)

Abstract:Although Angelina Weld Grimké's 1916 play, Rachel, has historically been read as a sentimental, anti-lynching drama, such classifications might limit the play's anarchic potential. Instead of viewing the characters as responding to anti-Black violence, this paper proposes reframing the play's discussion within a context of Black maternity and its necessary engagement with the Afro-pessimist concept of social death. Such reorientation suggests that Rachel works within the theater's very materiality in order to explore the effects of anti-Blackness on Black life. Specifically, (...) this paper argues that the play's performances of abiological Black maternity—and, particularly, the titular character's performances—fugitively evade the natal alienation of social death. Furthermore, such performances link past, present, and future stage productions as well as character representations, recreating kinship formations within Black social life to stage spatio-temporal disruptions on the equation of Blackness as social death. In this way, Rachel offers modern scholars an understanding of how older works might yet be read in light of the more recent theoretical work of radical Black feminist and Afro-pessimist scholars. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Resisting Structural Evil: Love as Ecological-Economic Vocation by Cynthia Moe-LobedaKiara A. JorgensonReview of Resisting Structural Evil: Love as Ecological-Economic Vocation CYNTHIA MOE-LOBEDA Minneapolis: Fortress Press, 2013. 309 pp. $22.00The factors that have contributed to today’s perilous global economy and ecology originate in structures that predate recent implosions of international banks or measurements of rising climates. These structures—systemic and social while also personal—are the focus of Moe-Lobeda’s work, Resisting (...) Structural Evil: Love as Ecological-Economic Vocation. Convinced that sin and violence is “uncreating” the beauty of God’s interdependent community and can only be countered and alleviated by a moral vision structured around “justice-seeking love,” Moe-Lobeda provides a compelling theological critique and reconstruction of the Christian concept of love by way of a fresh retrieval of the classical Christian doctrine of vocation.The book’s argument consists of a tapestry of sobering statistics, theological analysis, and narrative prose. Early on Moe-Lobeda takes great care to explain how the moral crises of today relate to the embedded social structures of yesterday. Here her attention to the globalization of economies and subsequent ecological injustice is particularly helpful since few contemporary texts make explicit this critical connection. In a chapter titled “Countering Moral Oblivion” she also devotes attention to why seemingly good people, particularly good Christians, passively and ignorantly participate in systems of oppressive power. This portion of her book, coupled with her discussion of how Christian theology can be a resource of hope, is empowering and particularly attentive to the role of biblical theology in the ecological conversation. Unlike many other theoretical books on the topic, Moe-Lobeda’s book can be appropriated as a tool for lifestyle appraisal useful to the academician, pastor, and lay reader alike. Indeed, Moe-Lobeda can evoke discomfort with her compelling vision and challenging call for a change in our current practices.Pivoting her argument on the promise of hope, the second half of Resisting Structural Evil discusses what can and must be realized. And it is here that Moe-Lobeda’s voice makes a contribution not only to Christian ecological ethics but also to Christian social ethics at large. Vocation, she argues, encompasses more than what traditional renderings of vocare have sought to connote. The human call to life is a call to love in compassion and justice both the neighbor [End Page 208] and the self, and must be made manifest in the public sphere. What is more, one must fulfill one’s vocation not only for the sake of the human other but also for the benefit of the oikos (household) present within all economic and ecological communities. To this end, Moe-Lobeda’s attention to love as vocation uniquely characterizes her approach to ecological ethics, thereby transcending traditional deontolological or teleological classifications. Unique within Protestant work on ecological ethics, Resisting Structural Evil provides a fresh depiction of character ethics wherein the pursuit of moral aptitude is fundamentally rooted in biotic community.This very strength may also foster some critique since Moe-Lobeda’s schema is so thoroughly corporate in scope that it affords little time and attention to what some virtue and character ethicists would call the inward journey. Yet Moe-Lobeda, aligned with the liberal and feminist traditions from which she hails, views love and power as inseparable. “What is needed,” she argues, “is a realization that power without love is reckless and abusive and that love without power is sentimental and anemic” (169). Hence, on a very fundamental level Resisting Structural Evil is a book arguing for a radically new paradigm, one where the enormity of today’s crises is met with an equally comprehensive dose of transformative loving power.Kiara A. JorgensonLuther SeminaryCopyright © 2015 Society of Christian Ethics... (shrink)

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...) potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

Sentimental Rules is an ambitious and highly interdisciplinary work, which proposes and defends a new theory about the nature and evolution of moral judgment. In it, philosopher Shaun Nichols develops the theory that emotions play a critical role in both the psychological and the cultural underpinnings of basic moral judgment. Nichols argues that our norms prohibiting the harming of others are fundamentally associated with our emotional responses to those harms, and that such 'sentimental rules' enjoy an advantage in cultural evolution, (...) which partly explains the success of certain moral norms. This has sweeping and exciting implications for philosophical ethics. Nichols builds on an explosion of recent intriguing experimental work in psychology on our capacity for moral judgment and shows how this empirical work has broad import for enduring philosophical problems. The result is an account that illuminates fundamental questions about the character of moral emotions and the role of sentiment and reason in how we make our moral judgments. This work should appeal widely across philosophy and the other disciplines that comprise cognitive science. (shrink)