Fake news has become an important topic of research in a variety of disciplines including linguistics and computer science. In this paper, we explain how the problem is approached from the perspective of natural language processing, with the goal of building a system to automatically detect misinformation in news. The main challenge in this line of research is collecting quality data, i.e., instances of fake and real news articles on a balanced distribution of topics. We review available datasets and introduce (...) the MisInfoText repository as a contribution of our lab to the community. We make available the full text of the news articles, together with veracity labels previously assigned based on manual assessment of the articles’ truth content. We also perform a topic modelling experiment to elaborate on the gaps and sources of imbalance in currently available datasets to guide future efforts. We appeal to the community to collect more data and to make it available for research purposes. (shrink)

Rhetorical Structure Theory has enjoyed continuous attention since its origins in the 1980s. It has been applied, compared to other approaches, and also criticized in a number of areas in discourse analysis, theoretical linguistics, psycholinguistics, and computational linguistics. In this article, we review some of the discussions about the theory itself, especially addressing issues of the reliability of analyses and psychological validity, together with a discussion of the nature of text relations. We also propose areas for further research. A follow-up (...) article will discuss applications of the theory in various fields. (shrink)

Rhetorical Structure Theory is a theory of text organization that has led to areas of application beyond discourse analysis and text generation, its original goals. In this article, we review the most important applications in several areas: discourse analysis, theoretical linguistics, psycholinguistics, and computational linguistics. We also provide a list of resources useful for work within the RST framework. The present article is a complement to our review of the theoretical aspects of the theory.

We present a corpus-based study of coherence in multimodal documents. We concern ourselves with the types of relationships between graphs and tables and the text of the document in which they appear. In order to understand and categorize the types of relations across modalities, we are making use of Rhetorical Structure Theory, and propose that this can adequately describe these types of relations. We analyzed a corpus comprising three different genres, and consisting of about 1500 pages of material and almost (...) 600 figures, tables and graphs. We show that figures stand in both presentational and subject matter relations to the text, and that the relationship between figures and text is one of a small set out of the larger possible rhetorical relations. We also discuss several issues that arise in the treatment of multimodal material, such as the potential for multiple connections between figure and text. (shrink)

School tourism constitutes a source of learning to strengthen the cultural identity of students. The objective was to compare the development of school tourism in the educational institutions San Pedro Chanel and Carlos Augusto Salaverry. The Leiper space approach was used. The exhibition was constituted by 200 high school students and 20 teachers. The results show that there is statistically significant differences regarding the knowledge of the tourist resources of the province of Sullana. It was concluded that educational tourism is (...) a strategy that tries to bring the student closer to knowledge, awareness and assessment of tourist resources. (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)