The hypothesis that perceptual mechanisms could have more representational and logical power than usually assumed is interesting and provocative, especially with regard to brain evolution. However, the importance of embodiment and grounding is exaggerated, and the implication that there is no highly abstract representation at all, and that human-like knowledge cannot be learned or represented without human bodies, is very doubtful. A machine-learning model, Latent Semantic Analysis (LSA) that closely mimics human word and passage meaning relations is (...) offered as a counterexample. (shrink)

In this paper, we use simple techniques derived from on Latent Semantic Analysis (LSA) to provide a simple and robust way of generating extractive summaries for TAC 2008 Update Summarization task.

Standard psychological scaling methods have been widely used as knowledge elicitation tools to uncover structural characteristics of a given domain. However, these methods traditionally rely on relatedness ratings from human experts, which is often time-consuming and tedious. We describe an integrated approach to knowledge elicitation and representation using Latent Semantic Analysis and Pathfinder Network Scaling techniques. The semantic structure of a subject domain can be automatically characterised from a collection of published documents in the domain. The (...) method is illustrated with an example of organising a digital library in accordance to latent semantic structures. (shrink)

The lore is that standard information theory provides an analysis of information quantity, but not of information content. I argue this lore is incorrect, and there is an adequate informational semantics latent in standard theory. The roots of this notion of content can be traced to the secret parallel development of an information theory equivalent to Shannon’s by Turing at Bletchley Park, and it has been suggested independently in recent work by Skyrms and Bullinaria and Levy. This paper (...) explicitly articulates the semantics latent in information theory and defends it as an adequate theory of information content, or natural meaning. I argue that this theory suggests a new perspective on the classic misrepresentation worry for correlation-based semantics. (shrink)

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9‐year‐old children. The neural network was trained and validated in the (...) child semantic space. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed‐effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed. (shrink)

Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization (...) and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views. (shrink)

Empirical studies indicate that analogy consists of two main processes: retrieval and mapping. While current theories and models of analogy have revealed much about the mainly structural constraints that govern the mapping process, the similarities that underpin the correspondences between individual representational elements and drive retrieval are understood in less detail. In existing models symbol similarities are externally defined but neither empirically grounded nor theoretically justified. This paper introduces a new model (EMMA: the environmental model of analogy) which relies on (...) co‐occurrence information provided by LSA (Latent Semantic Analysis; Landauer & Dumais, 1997) to ground the relations between the symbolic elements aligned in analogy. LSA calculates a contextual distribution for each word encountered in a corpus by counting the frequency with which it co‐occurs with other words. This information is used to define a model that locates each word encountered in a high‐dimensional space, with relations between elements in this space representing contextual similarities between words. A series of simulation experiments demonstrate that the environmental approach to semantics embodied in LSA can produce appropriate patterns of analogical retrieval, but that this semantic measure is not sufficient to model analogical mapping. The implications of these findings, both for theories of representation in analogy research and more general theories of semantics in cognition, are explored. (shrink)

Likert-scale surveys are frequently used in cross-cultural studies on leadership. Recent publications using digital text algorithms raise doubt about the source of variation in statistics from such studies to the extent that they are semantically driven. The Semantic Theory of Survey Response (STSR) predicts that in the case of semantically determined answers, the response patterns may also be predictable across languages. The Multifactor Leadership Questionnaire (MLQ) was applied to 11 different ethnic samples in English, Norwegian, German, Urdu and Chinese. (...) Semantic algorithms predicted responses significantly across all conditions, although to varying degree. Comparisons of Norwegian, German, Urdu and Chinese samples in native versus English language versions suggest that observed differences are not culturally dependent but caused by different translations and understanding. The maximum variance attributable to culture was a 5% unique overlap of variation in the two Chinese samples. These findings question the capability of traditional surveys to detect cultural differences. It also indicates that cross-cultural leadership research may risk lack of practical relevance. (shrink)

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We (...) compare the representations of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

Background: Research suggests that humans have the tendency to increase the valence of events when these are imagined to happen in the future, but to decrease the valence when the same events are imagined to happen in the past. This line of research, however, has mostly been conducted by asking participants to value imagined, yet probable, events. Our aim was to re-examine this time-valence asymmetry using real-life data: a Reuter’s news and a Facebook status updates corpus. Method: We organized the (...) Reuter news (120,000,000 words) and the Facebook status updates data (41,056,346 words) into contexts grouped in chronological order (i.e., past, present, and future) using verbs and years as time markers. These contexts were used to estimate the valence of each article and status update, respectively, in relation to the time markers using natural language processing tools (i.e., the Latent Semantic Analysis algorithm). Results: Our results using verbs, in both text corpus, showed that valence for the future was significantly higher compared to the past (future > past). Similarly, in the Reuter year condition, valence increased approximately linear from 1994 to 1999 for texts written 1996-7. In the Facebook year condition, the valence of the future was also significantly higher than past valence. Conclusion: Generally, the analyses of the Reuters data indicated that the past is devaluated relative to both the present and the future, while the analyses of the Facebook data indicated that both the past and the present are devaluated against the future. On this basis, we suggest that people strive to communicate the promotion of a bright future and the prevention of a dark future, which in turn leads to a temporal-valence asymmetrical phenomenon (valence = pastshrink)

The past decade has witnessed the emergence of a novel stance on semantic representation, and its relationship to context sensitivity. Connectionist-minded philosophers, including Clark and van Gelder, have espoused the merits of viewing hidden-layer, context-sensitive representations as possessing semantic content, where this content is partially revealed via the representations'' position in vector space. In recent work, Bodén and Niklasson have incorporated a variant of this view of semantics within their conception of semantic systematicity. Moreover, Bodén and Niklasson (...) contend that they have produced experimental results which not only satisfy a kind of context-based, semantic systematicity, but which, to the degree that reality permits, effectively deals with challenges posed by Fodor and Pylyshyn (1988), and Hadley (1994a). The latter challenge involved well-defined criteria for strong semantic systematicity. This paper examines the relevant claims and experiments of Bodén and Niklasson. It is argued that their case fatally involves two fallacies of equivocation; one concerning ''semantic content'' and the other concerning ''novel test sentences''. In addition, it is argued that their ultimate construal of context sensitive semantics contains serious confusions. These confusions are also found in certain publications dealing with "latent semantic analysis". Thus, criticisms presented here have relevance beyond the work of Bodén and Niklasson. (shrink)

Two main goals of the emerging field of neurocognitive poetics are the use of more natural and ecologically valid stimuli, tasks and contexts and providing methods and models allowing to quantify distinctive features of verbal materials used in such tasks and contexts and their effects on readers responses. A natural key element of poetic language, metaphor, still is understudied insofar as relatively little empirical research looked at literary or poetic metaphors. An exception is Katz et al.’s corpus of 204 literary (...) metaphors by authors such as Shakespeare or Dylan Thomas, for which various rating data are available. We reanalyzed their corpus using a combination of quantitative narrative analysis, latent semantic analysis, and machine learning in order to identify relevant features of the metaphors that influenced the ratings. The combined application of computational tools sheds light on surface and affective-semantic features that co-determine the reception of poetic metaphors and successfully predicted the period of origin, authorship and goodness ratings of the metaphors. The present results can be used for generating quantitative hypotheses or selecting and matching verbal stimuli in empirical studies of literature and neurocognitive poetics. (shrink)

Population counts and longitude and latitude coordinates were estimated for the 50 largest cities in the United States by computational linguistic techniques and by human participants. The mathematical technique Latent Semantic Analysis applied to newspaper texts produced similarity ratings between the 50 cities that allowed for a multidimensional scaling (MDS) of these cities. MDS coordinates correlated with the actual longitude and latitude of these cities, showing that cities that are located together share similar semantic contexts. This (...) finding was replicated using a first‐order co‐occurrence algorithm. The computational estimates of geographical location as well as population were akin to human estimates. These findings show that language encodes geographical information that language users in turn may use in their understanding of language and the world. (shrink)

The alignment of bargaining positions is crucial to a successful negotiation. Prior research has shown that similarity in language use is indicative of the conceptual alignment of interlocutors. We use latent semantic analysis to explore how the similarity of language use between negotiating parties develops over the course of a three-party negotiation. Results show that parties that reach an agreement show a gradual increase in language similarity over the course of the negotiation. Furthermore, reaching the most financially (...) efficient outcome is dependent on similarity in language use between the parties that have the most to gain from such an outcome. (shrink)

I consider the potential of eight text-scaling methods for the analysis of jurisprudential change. I use a small corpus of well-documented German Federal Constitutional Court opinions on European integration to compare the machine-generated scores to scholarly accounts of the case law and legal expert ratings. Naive Bayes, Word2Vec, Correspondence Analysis and Latent Semantic Analysis appear to perform well. Less convincing are the performance of Wordscores, ML Affinity and lexicon-based sentiment analysis. While both the high-dimensionality (...) of judicial texts and the validation of computer-based jurisprudential estimates pose major methodological challenges, I conclude that automated text-scaling methods hold out great promise for legal research. (shrink)

Semantic Analysis is a lively and clearly written introduction to the study of meaning in language and to the language-culture connection. Goddard covers traditional and contemporary issues and approaches with the relationship between semantics, conceptualization, and culture as a key theme. He also details a number of case studies that draw on a wide range of material from non-Indo-European languages, particularly Australian Aboriginal languages and Malay, on which the author is an authority.

In Latent Semantic Analysis (LSA) the meaning of a word is represented as a vector in a high‐dimensional semantic space. Different meanings of a word or different senses of a word are not distinguished. Instead, word senses are appropriately modified as the word is used in different contexts. In N‐VP sentences, the precise meaning of the verb phrase depends on the noun it is combined with. An algorithm is described to adjust the meaning of a predicate (...) as it is applied to different arguments. In forming a sentence meaning, not all features of a predicate are combined with the features of the argument, but only those that are appropriate to the argument. Hence, a different “sense” of a predicate emerges every time it is used in a different context. This predication algorithm is explored in the context of four different semantic problems: metaphor interpretation, causal inferences, similarity judgments, and homonym disambiguation. (shrink)

The VIA Classification of Strengths and Virtues is the most commonly used model of positive personality. In this study, we used two methods of model modification to develop models for two measures of the character strengths, the VIA Inventory of Strengths-Revised and the Global Assessment of Character Strengths. The first method consisted of freeing residual covariances based on modification indices until good fit was achieved. The second was residual network modeling (RNM), which frees residual partial correlations while minimizing a function (...) that penalizes more complex models. Models based on both strategies were developed for the two questionnaires. The resulting structural models were then applied to four other samples. Though both modification procedures achieved good fit in the sample used to develop the models, only RNM resulted in adequate model fit for both measures in all cross-validation samples. This finding suggests RNM is more robust against overfitting than traditional practices. Moreover, the result supports the validity of the three-factor model of character strengths with replicability. (shrink)

The multilevel conversational exchanges between a mentor and a learner could be seen as a radical constructivist account of their comprehensions. The process of knowledge construction could be realised to have significant importance in the context of mentor-learner interactions. The most important fundamental is that ‘the conversational exchanges between mentors and learners ask questions and give answers concerning their individual conceptions, comprehensions and reasonings’. These questions and answers are the main building blocks of the ‘Relations’ between mentors and learners. In (...) this article, I will employ Predicate Logic in order to focus on the relationships between learners and mentors. This research will—conceptually and logically—be concerned with [formal] semantic analysis of mentoring-learning relationships in the context of constructivist interactions. The conclusions will shed light on how a [formal] semantics for constructivist interactions is established. (shrink)

This paper presents a semantical analysis of the Weak Kleene Logics Kw3 and PWK from the tradition of Bochvar and Halldén. These are three-valued logics in which a formula takes the third value if at least one of its components does. The paper establishes two main results: a characterisation result for the relation of logical con- sequence in PWK – that is, we individuate necessary and sufficient conditions for a set.

Background: The three-dimensional model of nurses’ moral sensitivity has typically been studied using a variable-centered rather than a person-centered approach, preventing a more complete understanding of how these forms of moral sensitivity are expressed as a whole. Latent profile analysis is a person-centered approach that classifies individuals from a heterogeneous population into homogeneous subgroups, helping identify how different subpopulations of nurses use distinct combinations of different moral sensitivities to affect their service behaviors. Objective: Latent profile analysis (...) was used to identify three distinct profiles of nurses’ moral sensitivity. Associations of the profiles with service behaviors were then examined. Methods: Five hundred twenty-five nurses from three tertiary hospitals in China were investigated with Moral Sensitivity Questionnaire and Nurses’ Service Behavior Scale. Latent profile analysis was used to analyze the data. Ethical considerations: Approval was obtained from the Ethics committee for biomedical research of Medical College, the Hebei University of Engineering. Results: A three-profile moral sensitivity model provided the best fit to the data. The resulting profiles were low moral sensitivity, moderate moral sensitivity, and high moral sensitivity. There were significant differences in service behaviors among different profiles of moral sensitivity. Conclusion: The results provide a new and expanded view of nurses’ moral sensitivity, which may be used to monitor nurses’ service behaviors comprehensively and to evaluate nursing ethics management strategies. (shrink)

This study aimed to examine the number of latent classes of criminal social identity that exist among male recidivistic prisoners. Latent class analysis was used to identify homogeneous groups of criminal social identity. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the associationsto number of police arrests, recidivism, and violent offending while controlling for current age. The best fitting latent class model was a five-class solution: ‘High (...) criminal social identity’, ‘High Centrality, Moderate Affect, Low Ties’, ‘Low Centrality, Moderate Affect, High Ties’,‘Low Cognitive, High Affect, Low Ties’, and ‘Low criminal social identity’. Each of the latent classes was predicted by differing external variables. Criminal social identity is best explained by five homogenous classes that display qualitative and quantitative differences. (shrink)

Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of (...) known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically. (shrink)

This paper presents an analysis of wh-complements in Montague Grammar. We will be concerned primarily with semantics, though some remarks on syntax are made in Section 4. Questions and wh-comple ments in Montague Grammar have been studied in Hamblin (1976), Bennett (1979), Karttunen (1977) and Hauser (1978) among others. These proposals will not be discussed explicitly, but some differences with Karttunen's analysis will be pointed out along the way.

From the end of 2018 in China, the Big-data Driven Price Discrimination (BDPD) of online consumption raised public debate on social media. To study the consumers’ attitude about the BDPD, this study constructed a semantic recognition frame to deconstruct the Affection-Behavior-Cognition (ABC) consumer attitude theory using machine learning models inclusive of the Labeled Latent Dirichlet Allocation (LDA), Long Short-Term Memory (LSTM), and Snow Natural Language Processing (NLP), based on social media comments text dataset. Similar to the questionnaires published (...) results, this article verified that 61% of consumers expressed negative sentiment toward BDPD in general. Differently, on a finer scale, this study further measured the negative sentiments that differ significantly among different topics. The measurement results show that the topics “Regular Customers Priced High” (69%) and “Usage Intention” (67%) occupy the top two places of negative sentiment among consumers, and the topic “Precision Marketing” (42%) is at the bottom. Moreover, semantic recognition results that 49% of consumers’ comments involve multiple topics, indicating that consumers have a pretty clear cognition of the complex status of the BDPD. Importantly, this study found some topics that had not been focused on in previous studies, such as more than 8% of consumers calling for government and legal departments to regulate BDPD behavior, which indicates that quite enough consumers are losing confidence in the self-discipline of the platform enterprises. Another interesting result is that consumers who pursue solutions to the BDPD belong to two mutually exclusive groups: government protection and self-protection. The significance of this study is that it reminds the e-commerce platforms to pay attention to the potential harm for consumers’ psychology while bringing additional profits through the BDPD. Otherwise, the negative consumer attitudes may cause damage to brand image, business reputation, and the sustainable development of the platforms themselves. It also provides the government supervision departments an advanced analysis method reference for more effective administration to protect social fairness. (shrink)

Abstract:This article correlates the physical composition of the built environment with social interactions and human relationships. The resulting framework draws on an embodied cognitive position through interdisciplinary knowledge with priority given to architectural theory and cognitive linguistics. This approach does not address idiosyncratic, phenomenological descriptions of experiences of place but the potential relationship of human bodies through situated semantics suggested by spatial composition. In this article we ask how the physical arrangement of a space can provide information for analyzing the (...) probable social relations such as positions of hierarchy, power, and authority. We identify two theoretical models, namely latent embodied cognitive operations and space as a situated concept, which can be used to correlate physical arrangements with social meaning. (shrink)

Although we believe the results reported below to have direct philosophical import, we shall for the most part confine our remarks to the realm of mathematics. The reader is referred to [4] for a philosophically oriented discussion, comprehensible to mathematicians, of tense logic.The “minimal” tense logicT0is the system having connectives ∼, →,F(“at some future time”), andP(“at some past time”); the following axioms:(whereGandHabbreviate ∼F∼ and ∼P∼ respectively); and the following rules:(8) fromαandα → β, inferβ,(9) fromα, infer any substitution instance ofα,(10) fromα, (...) inferGα,(11) fromα, inferHα.A tense logic is a systemTwhose language is that ofT0and whose axioms and rules include (1)–(11). The axioms and rules ofTother than (1)–(11) are calledproperaxioms and rules.We shall investigate three systems of semantics for tense logics, i.e. three notions ofstructureand three relations ⊧ which stand between structures and formulas. One reads⊧αas “αis valid in.” A structureis amodelof a tense logicTif every formula provable inTis valid in. A semantics isadequateforTif the set of models ofTin the semantics is characteristic forT, i.e. if wheneverT ∀ αthen there is a modelofTin the semantics such that∀ α. Two structuresand, possibly from different semantics, are calledequivalent(∼) if exactly the same formulas are valid inas in. (shrink)

Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.

This article presents the results of a preliminary multidisciplinary research of the specificities of youth’s response to various descriptors. Using the semiotic, in-depth psychological, theological and mathematical analysis of the collected associative chains, the author compares the responses of youth representatives to religious and ethical terms with colloquial lexemes, as well as determines sensitivity to these terms and proclivity for their logical and sensory-emotional perception. Particularly, method of semantic multiplication allows identifying strong and weak descriptors of semiosis under (...) consideration. The author determines the trends that outline a number of structural and psychodynamic characteristics of psychic reality of modern Russian youth. The following conclusions were made in the course of this research: 1. Sensitivity (and corresponding awareness) to religious descriptors was demonstrated by less than half of the respondents, and a fifth of the entire sample of terms appeared to be unfamiliar to the respondents; 2. The analysis of ethical associative chains at the level of interpretation, indicated the existence of such a phenomenon as “indeterminate religiosity”, which implies a certain spiritual pursuit, which at the moment does not comply with the familiar to a respondent religions traditions; 3. The acquired data, on the one hand, correspond to the classic “Maslow's Hierarchy of Needs”, while on the other hand, spiritual pursuit of respondents and simultaneously scarce character of “existential” associations may testify in favor of the dominance of “ethical-spiritual” paradigm in psychic reality of respondents (which also complies with the Maslow’s research of later period in the area of “existential needs” and “peak experiences”; 4. All of the aforementioned means that the key to interaction with modern youth (including didactical and educational) is the paradigm of ethical values, which can also be connected with a latent spiritual pursuit. (shrink)