Abstract
In this paper, a simple but effective method for social event detection based mainly on natural language processing is introduced. Meanwhile existing approaches use many typical text-classification methods and disregard the importance of language characteristics, the proposed method exploits such language characteristics from text items in social metadata (e.g. title, description and tag) to leverage social event detection. First and foremost, we analyze the specific characteristics of natural language in social media to choose the most suitable features. Second, we employ common natural language processing techniques along with machine learning methods to extract features and perform classification. As a result, we experienced the F1 score higher than the results of related works that used state-of-the-art methods. The proposed method proves the significance of understanding language characteristics in building social event classification programs. It also offers good clues to improve existing works on social event detection.
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References
Ellison, N.B., et al.: Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication 13(1), 210–230 (2007)
Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: Procs of the 19th Int. Conf. on World Wide Web, pp. 591–600 (2010)
Gupta, I., Gautam, K., Krishna, C.: VIT@ MediaEval 2013 Social Event Detection Task: Semantic Structuring of Complementary Information for Clustering Events. In: MediaEval (2013)
Reuter, T., et al.: Social Event Detection at MediaEval 2013: Challenges, datasets, and evaluation. In: Procs. of the MediaEval 2013 Multimedia Benchmark Workshop, Barcelona, Spain, October 18-19 (2013)
Dekang, L.: An information-theoretic definition of similarity. Journal of ICML 98, 296–304 (1998)
Schinas, E., et al.: CERTH@ MediaEval 2013 Social Event Detection Task. In: Procs. of the MediaEval 2013 Multimedia Benchmark Workshop, Barcelona, Spain, October 18-19 (2013)
Brenner, M., Izquierdo, E.: Social event detection and retrieval in collaborative photo collections. In: Procs of the 2nd ACM International Conference on Multimedia Retrieval (2012)
Sakaki, T., et al.: Earthquake shakes Twitter users: real-time event detection by social sensors. In: Procs. of the 19th international conference on World Wide Web, pp. 851–860 (2010)
Duranti, A., Goodwin, C.: Rethinking context: Language as an interactive phenomenon, vol. (11). Cambridge University Press (1992)
Nguyen, T.T.V., Dao, M.S., Mattivi, R., De Natale, F.: Event Detection from Social Media: User-centric Parallel Split-n-merge and Composite Kernel. In: Procs. of ICMR 2014 Workshop on Social Events in Web Multimedia (SEWM) (2014)
Marcus, M., et al.: Building a large annotated corpus of English: The Penn Treebank. Journal of Computational Linguistics 19(2), 313–330 (1993)
Lewis, D., et al.: Rcv1: A new benchmark collection for text categorization research. The Journal of Machine Learning Research 5, 361–397 (2004)
Vapnik, V.: The nature of statistical learning theory. Springer (2000)
Vapnik, V.: Statistical learning theory (adaptive and learning systems for signal processing, communications and control series). John Wiley & Sons, A Wiley-Interscience Publication, New York (1998)
Joachims, T.: A statistical learning learning model of text classification for support vector machines. In: Procs. of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 128–136 (2001)
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Nguyen, DD., Dao, MS., Nguyen, TV.T. (2015). Natural Language Processing for Social Event Classification. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_7
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DOI: https://doi.org/10.1007/978-3-319-11680-8_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11679-2
Online ISBN: 978-3-319-11680-8
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