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Journal of Computer-Assisted Linguistic Research
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  This is an Open Access Journal Open Access journal
ISSN (Online) 2530-9455
Published by Universitat Politècnica de València Homepage  [25 journals]
  • Detecting Discourse-Independent Negated Forms of Public Textual

    • Authors: Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill
      Pages: 1 - 20
      Abstract: 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.
      PubDate: 2018-07-12
      DOI: 10.4995/jclr.2018.8917
      Issue No: Vol. 2, No. 1 (2018)
  • Learning IS-A relations from specialized-domain texts with co-occurrence

    • Authors: Pedro Urena
      Pages: 21 - 38
      Abstract: 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.
      PubDate: 2018-07-12
      DOI: 10.4995/jclr.2018.9916
      Issue No: Vol. 2, No. 1 (2018)
  • The role of sex differences in detecting deception in computer-mediated
           communication in English

    • Authors: Anna Kuzio
      Pages: 39 - 53
      Abstract: 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.
      PubDate: 2018-07-12
      DOI: 10.4995/jclr.2018.10521
      Issue No: Vol. 2, No. 1 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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