Developing a French FrameNet: Methodology and First results

International audienceThe Asfalda project aims to develop a French corpus with frame-based semantic annotations and automatic tools for shallow semantic analysis. We present the first part of the project: focusing on a set of notional domains, we delimited a subset of English frames, adapted them to French data when necessary, and developed the corresponding French lexicon. We believe that working domain by domain helped us to enforce the coherence of the resulting resource, and also has the advantage that, though the number of frames is limited (around a hundred), we obtain full coverage within a given domain

Discourse Relations and Evaluation

We examine the role of discourse relations (relations between propositions) in the interpretation of evaluative or opinion words. Through a combination of Rhetorical Structure Theory or RST (Mann & Thompson, 1988) and Appraisal Theory (Martin & White, 2005), we analyze how different discourse relations modify the evaluative content of opinion words, and what impact the nucleus-satellite structure in RST has on the evaluation. We conduct a corpus study, examining and annotating over 3,000 evaluative words in 50 movie reviews in the SFU Review Corpus (Taboada, 2008) with respect to five parameters: word category (nouns, verbs, adjectives or adverbs), prior polarity (positive, negative or neutral), RST structure (both nucleus-satellite status and relation type) and change of polarity as a result of being part of a discourse relation (Intensify, Downtone, Reversal or No Change). Results show that relations such as Concession, Elaboration, Evaluation, Evidence and Restatement most frequently intensify the polarity of the opinion words, although the majority of evaluative words (about 70%) do not undergo changes in their polarity because of the relations they are a part of. We also find that most opinion words (about 70%) are positioned in the nucleus, confirming a hypothesis in the literature, that nuclei are the most important units when extracting evaluation automatically

Evaluation in Discourse: a Corpus-Based Study

This paper describes the CASOAR corpus, the first manually annotated corpus that explores the impact of discourse structure on sentiment analysis with a study of movie reviews in French and in English as well as letters to the editor in French. While annotating opinions at the expression, the sentence or the document level is a well-established task and relatively straightforward, discourse annotation remains difficult, especially for non-experts. Therefore, combining both annotations poses several methodological problems that we address here. We propose a multi-layered annotation scheme that includes: the complete discourse structure according to the Segmented Discourse Representation Theory, the opinion orientation of elementary discourse units and opinion expressions, and their associated features. We detail each layer, explore the interactions between them and discuss our results. In particular, we examine the correlation between discourse and semantic category of opinion expressions, the impact of discourse relations on both subjectivity and polarity analysis and the impact of discourse on the determination of the overall opinion of a document. Our results demonstrate that discourse is an important cue for sentiment analysis, at least for the corpus genres we have studied

Huellas discursivas de otredad en ámbitos de violencia escolar

El presente artículo procede de una investigación mediante la cual se buscó elaborar un mapeo de las huellas discursivas de otredad en ámbitos de violencia escolar a través de los procesos lecto – escritores, con el fin de expresar un diagnóstico crítico a partir del análisis de los textos elaborados por los estudiantes de tres instituciones del sector privado ubicadas en tres contextos sociales diferentes, a través de diversas situaciones propuestas por el equipo de investigación, teniendo en cuenta referentes teóricos tales como Teun van Dijk, Jürgen Habermas, Pierre Bourdieu y Michael Foucault, entre otros

Extracting Sentiment from Healthcare Survey Data: An Evaluation of Sentiment Analysis Tools

Sentiment analysis is an emerging discipline with many analytical tools available. This project aimed to examine a number of tools regarding their suitability for healthcare data. A comparison between commercial and non-commercial tools was made using responses from an online survey which evaluated design changes made to a clinical information service. The commercial tools were Semantria and TheySay and the non-commercial tools were WEKA and Google Prediction API. Different approaches were followed for each tool to determine the polarity of each response (i.e. positive, negative or neutral). Overall, the non-commercial tools outperformed their commercial counterparts. However, due to the different features offered by the tools, specific recommendations are made for each. In addition, single-sentence responses were tested in isolation to determine the extent to which they more clearly express a single polarity. Further work can be done to establish the relationship between single-sentence responses and the sentiment they express

A Survey on Semantic Processing Techniques

Semantic processing is a fundamental research domain in computational linguistics. In the era of powerful pre-trained language models and large language models, the advancement of research in this domain appears to be decelerating. However, the study of semantics is multi-dimensional in linguistics. The research depth and breadth of computational semantic processing can be largely improved with new technologies. In this survey, we analyzed five semantic processing tasks, e.g., word sense disambiguation, anaphora resolution, named entity recognition, concept extraction, and subjectivity detection. We study relevant theoretical research in these fields, advanced methods, and downstream applications. We connect the surveyed tasks with downstream applications because this may inspire future scholars to fuse these low-level semantic processing tasks with high-level natural language processing tasks. The review of theoretical research may also inspire new tasks and technologies in the semantic processing domain. Finally, we compare the different semantic processing techniques and summarize their technical trends, application trends, and future directions.Comment: Published at Information Fusion, Volume 101, 2024, 101988, ISSN 1566-2535. The equal contribution mark is missed in the published version due to the publication policies. Please contact Prof. Erik Cambria for detail