Abstract
Spilling information study now factual instance remains fetching the best ever then the majority well-organized method to obtain useful knowledge from what is happening now, letting group to respond rapidly once problematic originate hooked on opinion or to classify newest tendencies portion to recuperate their performance. The problem we try to solve is that cutting-edge absence of existence living cutting-edge obverse of TV usual, shape information dispensation scheme that make informative information concerning contest competitions then relate view of admirers toward competition production. By means of tweet information, we discover sub-events cutting-edge willing and then view of admirers position Twitter associated toward game. We endorse a scheme aimed at factual instance summarization of arranged sub-events aimed at sporting race by means of tweet information. We too suggest a method that examines spirits of persons placement Twitter. We focused on summarizing sporting events, specifically FIFA World Cup 2017 and IPL 2017. For a system using social media like twitter toward retain path of belongings trendy about, we appearance on behalf of next qualities: (I) gratitude of bursty subject by way of rapidly as the situation arises; (II) summarization of linked bursty theme; (III) examining viewpoint of followers then relating view toward ready.
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References
Chakrabarti, D., Punera, K.: Event summarization using tweets. ICWSM 11, 66–73 (2011)
Arkaitz, Z., Damiano, S., Enrique, A., Julio, G.: Towards real-time summarization of scheduled events from twitter streams. In: Proceedings of the 23rd ACM Conference on Hypertext and Social Media, pp. 319–320 (2012)
Corney, D., Martin, C., Göker, A.: Two sides to every story: subjective event summarization of sports events using Twitter. In: ICMR2014 Workshop on Social Multimedia and Storytelling, pp. 662–672 (2014)
Bollen, J., Pepe, A., Mao, H.: Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena (2009). arXiv:0911.1583
Seol, Y.-S., Kim, H.-W., Kim, D.-J.: Emotion recognition from textual modality using a situational personalized emotion model. Int. J. Hybrid Inf. Technol. 5(2), 169–174 (2012)
Jiang, L., Yu, M., Zhou, M., Liu, X., Zhao, T.: Target-dependent twitter sentiment classification. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 151–160 (2011)
Sharifi, B., Hutton, M.-A., Kalita, J., Automatic summarization of twitter topics. In: National Workshop on Design and Analysis of Algorithm, Tezpur, India (2010)
Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes twitter users: real-time event detection by social sensors. In: Proceedings of the 19th International Conference on World Wide Web, pp. 851–860 (2010)
Turney, P.D.: Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 417–424 (2002)
Lin, C., Lin, C.: Generating event storylines from microblogs. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, pp. 210–216 (2012)
O’Connor, B., Balasubramanyan, R.: From tweets to polls: linking text sentiment to public opinion time series. In: Proceedings of the International AAAI Conference on Weblogs and Social Media, Washington, DC, pp. 511–519, May 2010
Stone, P.: Sentiment Lexicon General Inquirer: A Competitive Approach to Content Analysis. The MIT Press (1966)
Hole, V., Takalikar, M.: A survey on sentiment analysis and summarization for prediction. Int. J. Eng. Comput. Sci. (IJECS) 3(12), 9503–9506 (2014). ISSN 2319-7242
Hatzivassiloglou, V., McKeown, K.: Predicting the semantic orientation of adjectives. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics: Association for Computational Linguistics, pp. 174–181 (1997)
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Vijay Kumar, N., Janga Reddy, M. (2019). Factual Instance Tweet Summarization and Opinion Analysis of Sport Competition. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_16
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DOI: https://doi.org/10.1007/978-981-13-3393-4_16
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