Utilizing Word Vector Representation for Classifying Argument Components in Persuasive Essays

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Aside from the proper usage of grammar, diction and punctuation, a good essay must have cohesion and coherence. In persuasive essay, argumentative discourse is important as the parameter to see the cohesion and coherence among the arguments. An argument is characterized by one's stance (claim) which is strengthened with facts (premises) to complete the validity of the stance. Ideally, claims must be followed by premises either they support or attack the claims. In this paper, we try to identify 4 kinds of argument components (major claim, claim, premise, and non-argumentative) using some predefined features and measure the performance of word vector representation utilization in identifying argument components. We also present the results of our initial experiment by using deep learning to classify the argument components.

     

     


  • Keywords


    argument component, word vector representation, deep learning

  • References


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Article ID: 26406
 
DOI: 10.14419/ijet.v8i1.9.26406




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