Sentiment Analysis for Title-Sentence Sequences of News Articles

DOI

Bibliographic Information

Other Title
  • ニュース記事のタイトルと文の系列に対する感情分析

Description

<p>We propose a method to identify emotion labels of titles and sentences of news articles using a model combining BERT and BiLSTM-CRF as a problem of sequence labeling. First, we constructed a dataset with emotion labels ("positive," "negative," or "neutral") annotated for titles and sentences of news articles, and then evaluated its effectiveness of the model using the dataset. Furthermore, as an application example, we demonstrate a task of manually classifying articles written about a certain keyword into positive, negative, or neutral. We confirmed that the classification work could be completed in a shorter time than when these emphasis was not applied when the colors of titles and sentences were emphasized according to the estimated emotion labels.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390569845477335168
  • NII Article ID
    130008051713
  • DOI
    10.11517/pjsai.jsai2021.0_2yin508
  • ISSN
    27587347
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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