Journal of Computer-Assisted Linguistic Research - Vol 02 (2018)https://riunet.upv.es:443/handle/10251/1064702024-03-29T09:29:13Z2024-03-29T09:29:13ZThe role of sex differences in detecting deception in computer-mediated communication in EnglishKuzio, Annahttps://riunet.upv.es:443/handle/10251/1064772023-11-21T11:49:19Z2018-09-03T12:35:22ZThe role of sex differences in detecting deception in computer-mediated communication in English
Kuzio, Anna
[EN] While deception seems to be a common approach in interpersonal communication, most examination on interpersonal deception sees the sex of the interlocutor as unconnected with the capability to notice deceptive messages. This research studies the truth and deception detection capability of both male and female receivers when replying to both true and deceptive messages from both male and female speakers. The outcomes indicate that sex may be a significant variable in comprehending the interpersonal detection probabilities of truth and of lies. An interaction of variables including the speakers’ sex, receivers’ sex, and whether the message appears to be truthful or deceptive is created to relate to detection capability.
2018-09-03T12:35:22ZLearning IS-A relations from specialized-domain texts with co-occurrence measuresUreña Gómez-Moreno, Pedrohttps://riunet.upv.es:443/handle/10251/1064752023-11-21T11:49:19Z2018-09-03T12:31:31ZLearning IS-A relations from specialized-domain texts with co-occurrence measures
Ureña Gómez-Moreno, Pedro
[EN] Ontology enrichment is a classification problem in which an algorithm categorizes an input conceptual unit in the corresponding node in a target ontology. Conceptual enrichment is of great importance both to Knowledge Engineering and Natural Language Processing, because it helps maximize the efficacy of intelligent systems, making them more adaptable to scenarios where information is produced by means of language. Following previous research on distributional semantics, this paper presents a case study of ontology enrichment using a feature-extraction method which relies on collocational information from corpora. The major advantage of this method is that it can help locate an input unit within its corresponding superordinate node in a taxonomy using a relatively small number of lexical features. In order to evaluate the proposed framework, this paper presents an experiment consisting of the automatic classification of a chemical substance in a taxonomy of toxicology.
2018-09-03T12:31:31ZDetecting Discourse-Independent Negated Forms of Public Textual CyberbullyingPower, AureliaKeane, AnthonyNolan, BrianO'Neill, Brianhttps://riunet.upv.es:443/handle/10251/1064732023-11-21T11:49:19Z2018-09-03T12:24:03ZDetecting Discourse-Independent Negated Forms of Public Textual Cyberbullying
Power, Aurelia; Keane, Anthony; Nolan, Brian; O'Neill, Brian
[EN] Cyberbullying is a risk associated with the online safety of young people and, in this paper, we address one of its most common implicit forms – negation-based forms. We first describe the role of negation in public textual cyberbullying interaction and identify the cyberbullying constructions that characterise these forms. We then formulate the overall detection mechanism which captures the three necessary and sufficient elements of public textual cyberbullying – the personal marker, the dysphemistic element, and the link between them. Finally, we design rules to detect both overt and covert negation-based forms, and measure their effectiveness using a development dataset, as well as a novel test dataset, across several metrics: accuracy, precision, recall, and the F1-measure. The results indicate that the rules we designed closely resemble the performance of human annotators across all measures.
2018-09-03T12:24:03Z