Abstract
The abundance of sentiment-carrying user-generated content renders automated cross-language informationmonitoring tools crucial for today’s businesses. In order to facilitate cross-language sentiment analysis, we propose to compare the sentiment conveyed by unstructured text across languages through universal star ratings for intended sentiment. We demonstrate that the way natural language reveals people’s intended sentiment differs across languages. The results of our experiments with respect to modeling this relation for both Dutch and English by means of a monotone increasing step function mainly suggest that language-specific sentiment scores can separate universal classes of intended sentiment from one another to a limited extent.
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Abbasi, A., Chan, H., Salem, A.: Sentiment Analysis in Multiple Languages: Feature Selection for Opinion Classification in Web Forums. ACM Transactions on Information Systems 26(3) (2008)
Baccianella, S., Esuli, A., Sebastiani, F.: SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. In: 7th Conference on International Language Resources and Evaluation (LREC 2010), pp. 2200–2204. European Language Resources Association (2010)
Bal, D., Bal, M., van Bunningen, A., Hogenboom, A., Hogenboom, F., Frasincar, F.: Sentiment Analysis with a Multilingual Pipeline. In: Bouguettaya, A., Hauswirth, M., Liu, L. (eds.) WISE 2011. LNCS, vol. 6997, pp. 129–142. Springer, Heidelberg (2011)
Bautin, M., Vijayarenu, L., Skiena, S.: International Sentiment Analysis for News and Blogs. In: 2nd International Conference on Weblogs and Social Media (ICWSM 2008), pp. 19–26. AAAI Press (2008)
Dau, W., Xue, G., Yang, Q., Yu, Y.: Co-Clustering Based Classification. In: 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2007), pp. 210–219. Association for Computing Machinery (2007)
Dau, W., Xue, G., Yang, Q., Yu, Y.: Transferring Naive Bayes Classifiers for Text Classification. In: 22nd Association for the Advancement of Articifial Intelligence Conference on Artificial Intelligence (AAAI 2007), pp. 540–545. AAAI Press (2007)
Gliozzo, A., Strapparava, C.: Cross Language Text Categorization by Acquiring Multilingual Domain Models from Comparable Corpora. In: ACL Workshop on Building and Using Parallel Texts (ParaText 2005), pp. 9–16. Association for Computational Linguistics (2005)
Heerschop, B., Goossen, F., Hogenboom, A., Frasincar, F., Kaymak, U., de Jong, F.: Polarity Analysis of Texts using Discourse Structure. In: 20th ACM Conference on Information and Knowledge Management (CIKM 2011), pp. 1061–1070. Association for Computing Machinery (2011)
Heerschop, B., Hogenboom, A., Frasincar, F.: Sentiment Lexicon Creation from Lexical Resources. In: Abramowicz, W. (ed.) BIS 2011. LNBIP, vol. 87, pp. 185–196. Springer, Heidelberg (2011)
Heerschop, B., van Iterson, P., Hogenboom, A., Frasincar, F., Kaymak, U.: Analyzing Sentiment in a Large Set of Web Data while Accounting for Negation. In: 7th Atlantic Web Intelligence Conference (AWIC 2011), pp. 195–205. Springer (2011)
Hofman, K., Jijkoun, V.: Generating a Non-English Subjectivity Lexicon: Relations that Matter. In: 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2009), pp. 398–405. Association for Computing Machinery (2009)
Jansen, B., Zhang, M., Sobel, K., Chowdury, A.: Twitter Power: Tweets as Electronic Word of Mouth. Journal of the American Society for Information Science and Technology 60(11), 2169–2188 (2009)
Korte Reviews: Korte Reviews (2011), http://kortereviews.tumblr.com/
Lemaire: Lemaire Film Reviews (2011), http://www.lemairefilm.com/
Melville, P., Sindhwani, V., Lawrence, R.: Social Media Analytics: Channeling the Power of the Blogosphere for Marketing Insight. In: 1st Workshop on Information in Networks, WIN 2009 (2009)
Metacritic: Metacritic Reviews (2011), http://www.metacritic.com/browse/movies/title/dvd/
Mihalcea, R., Banea, C., Wiebe, J.: Learning Multilingual Subjective Language via Cross-Lingual Projections. In: 45th Annual Meeting of the Association for Computational Linguistics (ACL 2007), pp. 976–983. Association for Computational Linguistics (2007)
Moens, M., Boiy, E.: A Machine Learning Approach to Sentiment Analysis in Multilingual Web Texts. Information Retrieval 12(5), 526–558 (2007)
Paltoglou, G., Thelwall, M.: A study of Information Retrieval weighting schemes for sentiment analysis. In: 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), pp. 1386–1395. Association for Computational Linguistics (2010)
Pang, B., Lee, L.: A Sentimental Education: Sentiment Analysis using Subjectivity Summarization based on Minimum Cuts. In: 42nd Annual Meeting of the Association for Computational Linguistics (ACL 2004), pp. 271–280. Association for Computational Linguistics (2004)
Pang, B., Lee, L.: Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval 2(1), 1–135 (2008)
Short Reviews: Short Reviews (2011), http://shortreviews.net/browse/
Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-Based Methods for Sentiment Analysis. Computational Linguistics 37(2), 267–307 (2011)
Taboada, M., Voll, K., Brooke, J.: Extracting Sentiment as a Function of Discourse Structure and Topicality. Tech. Rep. 20. Simon Fraser University (2008), http://www.cs.sfu.ca/research/publications/techreports/#2008
Wan, X.: Co-Training for Cross-Lingual Sentiment Classification. In: Joint Conference of the 47th Annual Meeting of ACL and the 4th International Join Conference on Natural Language Processing of the AFNLP (ACL 2009), pp. 235–243. Association for Computational Linguistics (2009)
Whitelaw, C., Garg, N., Argamon, S.: Using Appraisal Groups for Sentiment Analysis. In: 14th ACM International Conference on Information and Knowledge Management (CIKM 2005), pp. 625–631. Association for Computing Machinery (2005)
Wierzbicka, A.: Dictionaries vs. Encyclopedias: How to Draw the Line. In: Alternative Linguistics: Descriptive and Theoretical Modes, pp. 289–316. John Benjamins Publishing Company (1995)
Wierzbicka, A.: Emotion and Facial Expression: A Semantic Perspective. Culture Psychology 1(2), 227–258 (1995)
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Hogenboom, A., Bal, M., Frasincar, F., Bal, D. (2013). Towards Cross-Language Sentiment Analysis through Universal Star Ratings. In: Uden, L., Herrera, F., Bajo Pérez, J., Corchado Rodríguez, J. (eds) 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing. Advances in Intelligent Systems and Computing, vol 172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30867-3_7
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DOI: https://doi.org/10.1007/978-3-642-30867-3_7
Publisher Name: Springer, Berlin, Heidelberg
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