A research on the text reliability based on evidentiality

Q.I. Su, H.K.Y. Chen, Chu-ren Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review


In this paper, we focus on the reliability of information encoded in a Web 2.0 community platform. Specifically, we aim to explore how linguistically encoded clues can contribute to the task. Given that evidentiality is the linguistic representation for the reliability of a statement, we propose to use evidential, the lexicalized evidentiality, to model text representation under the framework of machine learning based text classification. Based on the model, we conducted experiments to identify the best answers in Collaborative Question Answering (CQA) services. The experimental results confirm that, incorporating evidential for predicting text reliability is effective, since it shows the writer's self-judgment for information reliability. Moreover, our method can largely reduce the dimensionality of the vector space, and therefore provide an improvement in efficiency.
Original languageEnglish
Pages (from-to)201-214
Number of pages14
JournalInternational journal of computer processing of languages
Issue number2
Publication statusPublished - 2011


  • Evidentiality
  • Evidential
  • Reliability
  • Collaborative question answering

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