{"type":"ScholarlyArticle","title":"Opinion-aware Knowledge Graph for Political Ideology Detection","authors":[{"name":"Wei Chen","slug":"wei-chen","given":"Wei","family":"Chen","affiliation":"Key Lab of High Confidence Software Technologies (MOE) , School of EECS , Peking University"},{"name":"Xiao Zhang","slug":"xiao-zhang","given":"Xiao","family":"Zhang","affiliation":"Key Lab of High Confidence Software Technologies (MOE) , School of EECS , Peking University"},{"name":"Tengjiao Wang","slug":"tengjiao-wang","given":"Tengjiao","family":"Wang","affiliation":"Key Lab of High Confidence Software Technologies (MOE) , School of EECS , Peking University"},{"name":"Bishan Yang","slug":"bishan-yang","given":"Bishan","family":"Yang","affiliation":"Computer Science Department , Carnegie Mellon University"},{"name":"Yi Li","slug":"yi-li","given":"Yi","family":"Li","affiliation":"Key Lab of High Confidence Software Technologies (MOE) , School of EECS , Peking University"}],"abstract":"Identifying individual's political ideology from their speeches and written texts is important for analyzing political opinions and user behavior on social media. Traditional opinion mining methods rely on bag-of-words representations to classify texts into different ideology categories. Such methods are too coarse for understanding political ideologies. The key to identify different ideologies is to recognize different opinions expressed toward a specific topic. To model this insight, we classify ideologies based on the distribution of opinions expressed towards real-world entities or topics. Specifically, we propose a novel approach to political ideology detection that makes predictions based on an opinion-aware knowledge graph. We show how to construct such graph by integrating the opinions and targeted entities extracted from text into an existing structured knowledge base, and show how to perform ideology inference by information propagation on the graph. Experimental results demonstrate that our method achieves high accuracy in detecting ideologies compared to baselines including LR, SVM and RNN.","doi":"10.24963/ijcai.2017/510","url":"https://ijcai.org/proceedings/2017/510","pdf":"https://ijcai.org/proceedings/2017/0510.pdf","markdown":"https://ijcai.org/proceedings/2017/510.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/510","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Multidisciplinary Topics and Applications","track":"Main track","number":510,"pages":{"first":3647,"last":3653},"keywords":["Multidisciplinary Topics and Applications: AI and Social Sciences","Natural Language Processing: Sentiment Analysis and Text Mining"],"videos":[],"references":[{"position":1,"raw":"[Ahmed and Xing, 2010] Amr Ahmed and Eric P. Xing. S- taying informed: supervised and semi-supervised multi- view topical analysis of ideological perspective. In Pro- ceedings of the Conference on Empirical Methods in Nat- ural Language Processing, pages 1140-1150, 2010.","title":"Staying informed: supervised and semi-supervised multiview topical analysis of ideological perspective","authors":"Ahmed, Xing ;, Amr Ahmed, Eric P Xing","year":"2010","venue":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bakshy et al., 2015] Eytan Bakshy, Solomon Messing, and Lada Adamic. Exposure to ideo-logically diverse news and opinion on Facebook. Science, 348 (6239) : 1130-1132, 2015.","title":"Exposure to ideo-logically diverse news and opinion on Facebook","authors":"Eytan Bakshy, Solomon Messing, Lada Adamic","year":"2015","venue":"Science","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Bamman and Smith, 2015] David Bamman and Noah A. Smith. Open Extraction of Fine-Grained Political State- ments. In Processings of the Conference on Empirical Methods in Natural Language Processing, pages 76-85. 2015.","title":"Open Extraction of Fine-Grained Political Statements","authors":"Smith ; Bamman, David Bamman, Noah A Smith","year":"2015","venue":"Processings of the Conference on Empirical Methods in Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Bizer et al., 2009] Christian Bizer, Jens Lehmann, Georgi Kobilarov, Sören Auer, Christian Becker, Richard Cyga- niak and Sebastian Hellmann. DBpedia-A crystallization point for the web of data. Journal of Web Semantics, 7 (3): 154-165, 2009.","title":"DBpedia-A crystallization point for the web of data","authors":"Bizer","year":"2009","venue":"Journal of Web Semantics","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Conover et al., 2011] Michael D. Conover, Bruno Gonc ¸alves, Jacob Ratkiewicz, Alessandro Flammini and Filippo Menczer. Predicting the political alignment of twitter users. In Proceedings of 3rd IEEE Conference on Social Computing, pages 192-199. 2011.","title":"Predicting the political alignment of twitter users","authors":"D Michael, Bruno Conover, Jacob Gonc ¸alves, Alessandro Ratkiewicz, Filippo Flammini, Menczer","year":"2011","venue":"Proceedings of 3rd IEEE Conference on Social Computing","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Converse, 1964] Philip E. Converse. The Nature of Belief Systems in Mass Publics. In Ideology and Discontent, The Free Press of Glencoe, New York 1964.","title":"The Nature of Belief Systems in Mass Publics","authors":"Philip E Converse","year":"1964","venue":"Ideology and Discontent","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Cyganiak et al., 2014] Richard Cyganiak, David Wood and Markus Lanthaler. RDF 1.1 Con- cepts and Abstract Syntax. [Online]. Available: http://www.w3.org/TR/2014/REC-rdf11-concepts- 20140225/","title":"RDF 1.1 Concepts and Abstract Syntax","authors":"Richard Cyganiak, David Wood, Markus Lanthaler","year":null,"venue":null,"doi":null,"url":"http://www.w3.org/TR/2014/REC-rdf11-concepts-20140225/","internal_url":null},{"position":8,"raw":"[Ding et al., 2008] Xiaowen Ding, Bing Liu and Philip S. Yu. A holistic lexicon-based approach to opinion mining. In Proceedings of the Conference on Web Search and Web Data Mining, pages 231-240. 2008.","title":"A holistic lexicon-based approach to opinion mining","authors":"Xiaowen Ding, Bing Liu, Philip S Yu","year":"2008","venue":"Proceedings of the Conference on Web Search and Web Data Mining","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Gerrish and Blei, 2011] Sean Gerrish and David M. Blei. Predicting legislative roll calls from text. In Proceedings of the International Conference on Machine Learning, pages 489-496. 2011.","title":"Predicting legislative roll calls from text","authors":"Blei ; Gerrish, Sean Gerrish, David M Blei","year":"2011","venue":"Proceedings of the International Conference on Machine Learning","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Hoffart et al., 2013] Johannes Hoffart, Fabian M. Suchanek, Klaus Berberich and Gerhard Weikum. YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. Artificial Intelligence, 194: 28-61, 2013.","title":"YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia","authors":"Johannes Hoffart, Fabian M Suchanek, Klaus Berberich, Gerhard Weikum","year":"2013","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Iyyer et al., 2014] Mohit Iyyer , Peter Enns , Jordan Boyd- Graber and Philip Resnik. Political ideology detection using recursive neural networks. In Proceedings Annu- al Meeting of Association for Computational Linguistics Conference, pages 1113-1122. 2014.","title":"Political ideology detection using recursive neural networks","authors":"Mohit Iyyer, Peter Enns, Jordan Boyd-Graber, Philip Resnik","year":"2014","venue":"Proceedings Annual Meeting of Association for Computational Linguistics Conference","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Mukherjee and Liu, 2013] Arjun Mukherjee, Bing Liu. Dis- covering user interactions in ideological discussions. In Proceedings Annual Meeting of Association for Computa- tional Linguistics Conference, pages 671-681. 2013.","title":"Discovering user interactions in ideological discussions","authors":"Arjun Mukherjee, Bing Liu","year":"2013","venue":"Proceedings Annual Meeting of Association for Computational Linguistics Conference","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Mullen and Malouf, 2006] Tony Mullen, Robert Malouf. A preliminary investigation into sentiment analysis of infor- mal political discourse. In Proceedings of the AAAI sympo- sium on computational approaches to analyzing weblogs, pages 159-162. 2006.","title":"A preliminary investigation into sentiment analysis of informal political discourse","authors":"Malouf ; Tony Mullen, Robert Mullen, Malouf","year":"2006","venue":"Proceedings of the AAAI symposium on computational approaches to analyzing weblogs","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Nguyen et al., 2013] Viet-An Nguyen, Jordan Boyd-Graber and Philip Resnik. Lexical and Hierarchical Topic Re- gression. In Proceedings of the 2013 Neural Information Processing Systems (NIPS) Conference, pages 1106-1114. 2013.","title":"Viet-An Nguyen, Jordan Boyd-Graber and Philip Resnik. Lexical and Hierarchical Topic Regression","authors":"Nguyen","year":"2013","venue":"Proceedings of the 2013 Neural Information Processing Systems (NIPS) Conference","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Pang and Lee, 2008] Bo Pang and Lillian Lee. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2 (1-2) : 1-135, 2008.","title":"Opinion mining and sentiment analysis","authors":"Lee ; Pang, Bo Pang, Lillian Lee","year":"2008","venue":"Foundations and Trends in Information Retrieval","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Qiu et al., 2015] Minghui Qiu, Yanchuan Sim, Noah A. Smith and Jing Jiang. Modeling User Arguments, Inter- actions, and Attributes for Stance Prediction in Online De- bate Forums. In Proceedings of SIAM International Con- ference on Data Mining, pages 855-863. 2015.","title":"Modeling User Arguments, Interactions, and Attributes for Stance Prediction in Online Debate Forums","authors":"Qiu","year":"2015","venue":"Proceedings of SIAM International Conference on Data Mining","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Schuhmacher and Ponzetto, 2014] Michael Schuhmach- er, Simone Paolo Ponzetto. Knowledge-based graph document modeling. In Proceedings of the 7th ACM international conference on Web search and data mining, pages 543-552. 2014.","title":"Knowledge-based graph document modeling","authors":"Michael Schuhmacher, Paolo Simone, Ponzetto","year":"2014","venue":"Proceedings of the 7th ACM international conference on Web search and data mining","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Sim et al., 2013] Yanchuan Sim, Brice D. L. Acree, Justin H. Gross and Noah A. Smith. Measuring ideological pro- portions in political speeches. In Proceedings of the Con- ference on Empirical Methods in Natural Language Pro- cessing, pages 91-101. 2013.","title":"Measuring ideological proportions in political speeches","authors":"Sim","year":"2013","venue":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Somasundaran and Wiebe, 2010] Swapna Somasundaran and Janyce Wiebe. Recognizing Stances in Ideological On-Line Debates. In Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, pages 116-124. 2010.","title":"Recognizing Stances in Ideological On-Line Debates","authors":"Wiebe Somasundaran, Swapna Somasundaran, Janyce Wiebe","year":"2010","venue":"Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Thomas et al., 2006] Matt Thomas, Bo Pang and Lillian Lee. Get out the vote: Deter-mining support or opposition from Congressional floor-debate transcripts. In Proceed- ings of the Conference on Empirical Methods in Natural Language Processing, pages 327-335. 2006.","title":"Get out the vote: Deter-mining support or opposition from Congressional floor-debate transcripts","authors":"Matt Thomas, Bo Pang, Lillian Lee","year":"2006","venue":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Treier and Hillygus, 2009] Shawn Treier and D. Sunshine Hillygus. The Nature of Political Ideology in the Con- temporary Electorate. Public Opinion Quarterly, 73 (4): 679-703, 2009.","title":"The Nature of Political Ideology in the Contemporary Electorate","authors":"Shawn Treier, D Sunshine Hillygus","year":"2009","venue":"Public Opinion Quarterly","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Wang and Domeniconi, 2008] Pu Wang and Carlotta Domeniconi. Building Semantic Kernels for Text Classi- fication using Wikipedia. In Proceedings of the 14th ACM International Conference on Knowledge Discovery and Data Mining, pages 713-721. 2008.","title":"Building Semantic Kernels for Text Classification using Wikipedia","authors":"Wang, Domeniconi ;, Pu Wang, Carlotta Domeniconi","year":"2008","venue":"Proceedings of the 14th ACM International Conference on Knowledge Discovery and Data Mining","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Wiebe et al., 2004] Janyce Wiebe, Theresa Wilson, Rebec- ca Bruce, Matthew Bell and Melanie Martin. Learning subjective language. Computational Linguistics, 30 (3): 277-308, 2004.","title":"Learning subjective language","authors":"Janyce Wiebe, Theresa Wilson, Rebecca Bruce, Matthew Bell, Melanie Martin","year":"2004","venue":"Computational Linguistics","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}