Statement map: assisting information crediblity analysis by visualizing arguments

ABSTRACT

In this paper we introduce Statement Map, a project designed to help users navigate the vast amounts of information on the internet and come to informed opinions on topics of interest. It does this by mining the Web for a variety of viewpoints and presenting them to users together with supporting evidence in a way that makes it clear how the viewpoints are related. In this paper, we discuss the need to address issues of information credibility on the internet, outline the development of Statement Map generators for Japanese and English, discuss the technical issues that are being addressed, and report on the construction of the resources necessary to meet the project's goals.

REFERENCES

• 1: F. Bond, H. Isahara, K. Kanzaki, and K. Uchimoto. Boot-strapping a wordnet using multiple existing wordnets. In Proc. the 6th International Language Resources and Evaluation (LREC'08), 2008.
• 2: CDC. Update: Measles outbreaks continue in U.S. Website for Centers for Disease Control and Prevention, 2008. Available at: http://www.cdc.gov/Features/MeaslesUpdate/.
• 3: N. Chambers, D. Cer, T. Grenager, D. Hall, C. Kiddon, B. MacCartney, M.-C. de Marneffe, D. Ramage, E. Yeh, and C. D. Manning. Learning alignments and leveraging natural logic. In ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pages 165--170, 2007.
• 4: M.-C. de Marneffe, T. Grenager, B. MacCartney, D. Cer, D. Romage, C. kiddon, and C. D. Manning. Aligning semantic graphs for textual inference and machine reading. In Proc. of AAAI Spring Symposium Series: Machine Reading, 2007.
• 5: A. Esuli and F. Sebastiani. SENTIWORDNET: A publicly available lexical resource for opinion mining. In Proceedings of the 5th Conference on Language Resources and Evaluation (LREC-06), pages 417--422, 2006.
• 6: J. Etoh and M. Okumura. Cross-document relationship between sentences corpus. In Proc. of the 14th Annual Meeting of the Association for Natural Language Processing, pages 482--485, 2005. (in Japanese).
• 7: Eurosurvelliance. Measels once again endemic in the United Kingdom. Eurosurvelliance, 13(27), 2008. Available at: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=18919.
• 8: Finding Dulcenia. European health officials cope with measles outbreaks, lower vaccination rates. Finding Dulcenia: Librarian of the Internet, 2009. Available at: http://www.findingdulcinea.com/news/health/2009/jan/European-Health-Officials-Cope-With-Measles-Outbreaks-Lower-Vaccination-Rates.html.
• 9: O. Glickman, I. Dagan, and M. Koppel. Web based textual entailment. In Proc. of the First PASCAL Recognizing Textual Entailment Workshop, 2005.
• 10: Aria D. Haghighi , Andrew Y. Ng , Christopher D. Manning, Robust textual inference via graph matching, Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, p.387-394, October 06-08, 2005, Vancouver, British Columbia, Canada [doi>10.3115/1220575.1220624]
• 11: A. Hickl, J. Williams, J. Bensley, K. R. B. Rink, and Y. Shi. Recognizing textual entailment with lcc's groundhog system. In Proc. of the Second PASCAL Challenges Workshop, 2005.
• 12: M. Higashiyama. Acquiring Noun Polarity Knowledge Using Selectional Preferences. MASTER Thesis, 2008. (in Japanese).
• 13: R. Iida, K. Inui, and Y. Matsumoto. The task definition of evidence-conclusion relation extraction and its preliminary empirical evaluation. In Proc. of the 15th Annual Meeting of the Association for Natural Language Processing, 2009. (in Japanese).
• 14: Kentaro Inui , Shuya Abe , Kazuo Hara , Hiraku Morita , Chitose Sao , Megumi Eguchi , Asuka Sumida , Koji Murakami , Suguru Matsuyoshi, Experience Mining: Building a Large-Scale Database of Personal Experiences and Opinions from Web Documents, Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, p.314-321, December 09-12, 2008 [doi>10.1109/WIIAT.2008.373]
• 15: Takashi Inui , Kentaro Inui , Yuji Matsumoto, Acquiring causal knowledge from text using the connective marker tame, ACM Transactions on Asian Language Information Processing (TALIP), v.4 n.4, p.435-474, December 2005 [doi>10.1145/1113308.1113313]
• 16: N. Kobayashi, K. Inui, and Y. Matsumoto. Opinion mining from web documents: Extraction and structurization. Journal of the Japanese Society for Artificial Intelligence, 22(2):227--238, 2007.
• 17: D. R. Lankes. Trusting the internet: New approaches to credibility tools. In M. J. Metzger and Andrew, editors, Digital Media, Youth, and Credibility, pages 101--122. MIT Press, 2008.
• 18: B. MacCartney, M. Galley, and C. D. Manning. A phrase-based alignment model for natural language inference. In Proc. of 2008 Conference on Empirical Methods in Natural Language Processing (EMNLP-08), pages 802--811, 2008.
• 19: Bill MacCartney , Trond Grenager , Marie-Catherine de Marneffe , Daniel Cer , Christopher D. Manning, Learning to recognize features of valid textual entailments, Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, p.41-48, June 04-09, 2006, New York, New York [doi>10.3115/1220835.1220841]
• 20: E. Marsi and E. Krahmer. Classification of semantic relations by humans and machines. In In ACL-05 Workshop on Empirical Modeling of Semantic Equivalence and Entailment, pages 1--6, 2005.
• 21: Suguru Matsuyoshi , Koji Murakami , Yuji Matsumoto , Kentaro Inui, A Database of Relations between Predicate Argument Structures for Recognizing Textual Entailment and Contradiction, Proceedings of the 2008 Second International Symposium on Universal Communication, p.366-373, December 15-16, 2008 [doi>10.1109/ISUC.2008.31]
• 22: Ryan McDonald , Koby Crammer , Fernando Pereira, Online large-margin training of dependency parsers, Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, p.91-98, June 25-30, 2005, Ann Arbor, Michigan [doi>10.3115/1219840.1219852]
• 23: Miriam J. Metzger, Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research, Journal of the American Society for Information Science and Technology, v.58 n.13, p.2078-2091, November 2007 [doi>10.1002/asi.v58:13]
• 24: Y. Miyabe, H. Takamura, and M. Okumura. Identifying cross-document relations between sentences. In In Proc. of the 3rd International Joint Conference on Natural Language Processing (IJCNLP-08), pages 141--148, 2008.
• 25: E. Nichols, K. Murakami, K. Inui, and Y. Matsumoto. Constructing a scientific blog corpus for information credibility analysis. In Proc. of the 15th Annual Meeting of the Association for Natural Language Processing, 2009.
• 26: Pew Research. Internet overtakes newspapers as news outlet. Website for the Pew Research Center for the People & the Press, 2008. Available at: http://people-press.org/report/479/internetovertakes-newspapers-as-news-source.
• 27: P. Plait. ÆaØA ,ebut how do we recover from Jenny McCarthy? Bad Astronomy, 2008. Available at:>http://blogs.discovermagazine.com/badastronomy/2008/10/20/but-how-do-we-recoverfrom-jenny-mccarthy/.
• 28: S. Pradhan, W. Ward, K. Hacioglu, J. Martin, and D. Jurafsky. Shallow semantic parsing using support vector machines. In Proceedings of the Human Language Technology Conference/North American chapter of the Association of Computational Linguistics (HLT/NAACL), Boston, MA, 2004.
• 29: D. Radev, J. Otterbacher, and Z. Zhang. CSTBank: Cross-document Structure Theory Bank. http://tangra.si.umich.edu/clair/CSTBank, 2003.
• 30: Dragomir R. Radev, A common theory of information fusion from multiple text sources step one: cross-document structure, Proceedings of the 1st SIGdial workshop on Discourse and dialogue, p.74-83, October 07-08, 2000, Hong Kong [doi>10.3115/1117736.1117745]
• 31: A. Ratnaparkhi. A maximum entropy model for part-of-speech tagging. In E. Brill and K. Church, editors, Proceedings of the Empirical Methods in Natural Language Processing, pages 133--142, 1996.
• 32: D. Roth and M. Sammons. Semantic and logical inference model for textual entailment. In Proc. of the Third PASCAL Recognizing Textual Entailment Workshop, 2007.
• 33: C. Sao, M. Eguchi, S. Matsuyoshi, and K. Inui. An annotation scheme for capturing modality and polarity of events in japanese text. In Proc. of the 15th Annual Meeting of the Association for Natural Language Processing, 2009. (in Japanese).
• 34: K. Shinzato, T. Shibata, D. Kawahara, C. Hashimoto, and S. Kurohashi. Tsubaki: An open search engine infrastructure for developing new information access methodology. In Proc. the 3rd International Joint Conference on Natural Language Processing (IJCNLP2008), pages 189--196, 2008.
• 35: A. Sumida, K. Torisawa, and K. Shinzato. Concept-instance relation extraction from simple noun sequences using a search engine on a web repository. In Proc. the Web Content Mining with Human Language Technologies workshop on the 5th International Semantic Web, 2006.
• 36: A. Sumida, N. Yoshinaga, and K. Torisawa. Boosting precision and recall of hyponymy relation acquisition from hierarchical layouts in wikipedia. In Proc. the 6th International Language Resources and Evaluation (LREC'08), 2008.
• 37: A. Sumida, N. Yoshinaga, K. Torisawa, and K. Mannari. Acquiring a large number of hyponymy relations from the wikipedia. In Proc. of the 14th Annual Meeting of the Association for Natural Language Processing, pages 769--772, 2008. (in Japanese).
• 38: I. Szpektor, E. Shnarch, and I. Dagan. Instance-based evaluation of entailment rule acquisition. In Proc. of the 45th Annual Meeting of the Association of Computational Linguistics, pages 456--463, 2007.
• 39: Us Magazine. Jenny McCarthy: My son no longer has autism. Website for Us Magazine, 2008. Available at: http://www.usmagazine.com/news/jennymccarthy-my-son-is-no-longer-autistic/.
• 40: J. V. and M. de Rijke. Recognizing textual entailment using lexical similarity. In Proc. of the First PASCAL Challenges Workshop, 2005.
• 41: A. J. Wakefield, S. H. Murch, A. Anthony, J. Linnell, D. M. Casson, M. Malik, M. Berelowitz, A. P. Dhillon, M. A. Thomson, P. Harvey, A. Valentine, S. E. Davies, and J. A. Walker-Smith. Ileal-lymphoid-nodular hyperplasia, non-specific colitis, and pervasive developmental disorder in children. The Lancet, 351(9103), 1998.
• 42: B. Wellner and J. Pustejovsky. Automatically identifying the arguments of discourse connectives. In Proc. of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pages 92--101, 2007.
• 43: What Japan Thinks. Checking internet news in Japan. Website for What Japan Thinks, 2008. Available at: http://whatjapanthinks.com/2008/07/13/checking-internet-news-in-japan/#more-1225.
• 44: J. Wiebe, T. Wilson, and C. Cardie. Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 39(2-3):165--210, 2005.
• 45: M. William and S. Thompson. Rhetorical structure theory: towards a functional theory of text organization. Text, 8(3):243--281, 1988.
• 46: Z. Zhang and D. Radev. Combining labeled and unlabeled data for learning cross-document structural relationships. In Proc. the Proceedings of IJC-NLP, 2004.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Linguistic processing

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Text analysis

General Terms:
Algorithms, Languages

Keywords:
factuality analysis, semantic relations, sentiment analysis, statement map