Detecting Opinions and their Opinion Targets in NTCIR-8

an opinion target, a primary object of the opinion expression (e.g., the real-world object, event, and abstract entity), is helpful for extracting target-related opinions and detecting user interests. This paper presents a novel framework for target-based opinion analysis, which extracts opinionated sentences and identifies their opinion targets from news articles. To determine whether a sentence includes opinions, we utilize opinion lexicons (i.e., predefined clue words) and linguistic patterns. In identifying the opinion target, candidates are generated and examined for existence of four different features. We attempt to capture the relationship between an object target and opinion clues and utilize a document theme. For evaluation, we used English news articles from New York Times, provided by NTCIR-8 MOAT and annotated opinionated sentences and theirs opinion targets. Experimental results show that our proposed method is promising although many additional issues remain to be studied in the future.

[1]  Rada Mihalcea,et al.  Word Sense and Subjectivity , 2006, ACL.

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

[3]  Noriko Kando,et al.  Multilingual opinion holder identification using author and authority viewpoints , 2009, Inf. Process. Manag..

[4]  Janyce Wiebe,et al.  Effects of Adjective Orientation and Gradability on Sentence Subjectivity , 2000, COLING.

[5]  Ellen Riloff,et al.  Learning Extraction Patterns for Subjective Expressions , 2003, EMNLP.

[6]  Steven Skiena,et al.  Large-Scale Sentiment Analysis for News and Blogs (system demonstration) , 2007, ICWSM.

[7]  Sung-Hyon Myaeng,et al.  Identifying Controversial Issues and Their Sub-topics in News Articles , 2010, PAISI.

[8]  Xiaoyan Zhu,et al.  Movie review mining and summarization , 2006, CIKM '06.

[9]  Ellen Riloff,et al.  Creating Subjective and Objective Sentence Classifiers from Unannotated Texts , 2005, CICLing.

[10]  Shlomo Argamon,et al.  Using appraisal groups for sentiment analysis , 2005, CIKM '05.

[11]  Sung-Hyon Myaeng,et al.  Extracting Topic-related Opinions and their Targets in NTCIR-7 , 2008, NTCIR.

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

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

[14]  Andrea Esuli,et al.  SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining , 2006, LREC.

[15]  Vibhu O. Mittal,et al.  A fact/opinion classifier for news articles , 2007, SIGIR.

[16]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[17]  Hong Yu,et al.  Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences , 2003, EMNLP.

[18]  Jungi Kim,et al.  English Opinion Analysis for NTCIR7 at POSTECH , 2008, NTCIR.

[19]  Hsin-Hsi Chen,et al.  Overview of Multilingual Opinion Analysis Task at NTCIR-7 , 2008, NTCIR.

[20]  Swapna Somasundaran,et al.  Finding the Sources and Targets of Subjective Expressions , 2008, LREC.

[21]  Beth Levin,et al.  English Verb Classes and Alternations: A Preliminary Investigation , 1993 .

[22]  Janyce Wiebe,et al.  Development and Use of a Gold-Standard Data Set for Subjectivity Classifications , 1999, ACL.