Multilingual opinion holder identification using author and authority viewpoints

Opinion holder identification research is important for discriminating between opinions that are viewed from different perspectives. We propose a new opinion holder identification method that is based on a differentiation between the author and authority viewpoints in opinionated sentences. In our method, the author- and authority-opinionated sentences were extracted, respectively, by utilizing the different features because their writing styles were different. Although the researchers have not focused on it, this differentiation is important for correctly identifying opinion holders. We describe our participation in the NTCIR-6 Opinion Analysis Pilot Task by focusing on the opinion holder identification results in Japanese and English. The evaluation results showed that our system performed fairly well with respect to Japanese documents, and postsubmission analysis has revealed that improvements could be made with respect to English documents as well.

[1]  Eduard Hovy,et al.  Extracting Opinions, Opinion Holders, and Topics Expressed in Online News Media Text , 2006 .

[2]  Shlomo Argamon,et al.  Appraisal Extraction for News Opinion Analysis at NTCIR-6 , 2007, NTCIR.

[3]  Soo-Min Kim,et al.  Identifying and Analyzing Judgment Opinions , 2006, NAACL.

[4]  Janyce Wiebe,et al.  Learning Subjective Language , 2004, CL.

[5]  Hsin-Hsi Chen,et al.  Overview of Opinion Analysis Pilot Task at NTCIR-6 , 2007, NTCIR.

[6]  Shlomo Argamon,et al.  Extracting Appraisal Expressions , 2007, NAACL.

[7]  V. Hatzivassiloglou Lists of manually and automatically identified gradable, polar, and dynamic adjectives, gzipped tar file , 2000 .

[8]  Noriko Kando,et al.  Multi-Document Viewpoint Summarization Focused on Facts, Opinion and Knowledge , 2006, Computing Attitude and Affect in Text.

[9]  Janyce Wiebe,et al.  Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2005, HLT.

[10]  Steven Skiena,et al.  International Sentiment Analysis for News and Blogs , 2021, ICWSM.

[11]  Bing Liu,et al.  Opinion observer: analyzing and comparing opinions on the Web , 2005, WWW '05.

[12]  Sung-Hyon Myaeng,et al.  Opinion Analysis based on Lexical Clues and their Expansion , 2007, NTCIR.

[13]  Yuji Matsumoto,et al.  Japanese Dependency Analysis using Cascaded Chunking , 2002, CoNLL.

[14]  Claire Cardie,et al.  Partially Supervised Coreference Resolution for Opinion Summarization through Structured Rule Learning , 2006, EMNLP.

[15]  Claire Cardie,et al.  Cornell System Description for the NTCIR-6 Opinion Task , 2007, NTCIR.

[16]  Claire Cardie,et al.  Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns , 2005, HLT.

[17]  Claire Cardie,et al.  Annotating Expressions of Opinions and Emotions in Language , 2005, Lang. Resour. Evaluation.

[18]  Claire Cardie,et al.  Toward Opinion Summarization: Linking the Sources , 2006 .