Abstract
Given a news article, how many tweets are relevant to it in Twitter? Can we continuously collect only such tweets in real-time? In this paper, we propose a method for matching news articles and tweets in real-time. By collecting tweets relevant to news articles, we can get reactions to news articles such as sentiments and opinions from Twitter users. Our contributions are two-fold: (a) flexibility: our method collects the appropriate number of tweets for various kinds of news articles, each of which has the different number of tweets that mention it. (b) efficiency: our method can reduce the update time of an inverted index which is used for efficient matching of news articles and tweets. Also, we experimentally demonstrate the effectiveness of our method on streams of news articles and tweets from Yahoo!News and Twitter, respectively. We use the area under the ROC curve (AUC) to compare the accuracy of our method and that of baselines. The comparison shows that the AUC of our method is higher than that of the baselines by up to 22.7%. Furthermore, our method can update its index about 10 times faster compared to the existing technique.
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References
Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.: Sentiment analysis of twitter data. In: LSM, pp. 30–38 (2011)
Amati, G., Bianchi, M., Marcone, G.: Sentiment estimation on twitter. In: IIR, pp. 39–50 (2014)
Canneyt, S.V., Feys, M., Schockaert, S., Demeester, T., Develder, C., Dhoedt, B.: Detecting newsworthy topics in twitter. In: SNOW-DC@WWW, pp. 25–32 (2014)
Chakrabarti, D., Punera, K.: Event summarization using tweets. In: ICWSM (2011)
Fawcett, T.: An introduction to ROC analysis. Pattern Recognition Letters 27(8), 861–874 (2006)
Hu, M., Liu, S., Wei, F., Wu, Y., Stasko, J.T., Ma, K.L.: Breaking news on twitter. In: CHI, pp. 2751–2754 (2012)
Kwak, H., Lee, C., Park, H., Moon, S.B.: What is twitter, a social network or a news media? In: WWW, pp. 591–600 (2010)
Luo, Z., Osborne, M., Wang, T.: Opinion retrieval in twitter. In: ICWSM (2012)
Nichols, J., Mahmud, J., Drews, C.: Summarizing sporting events using twitter. In: IUI, pp. 189–198 (2012)
Osborne, M., Dredze, M.: Facebook, twitter and google plus for breaking news: is there a winner? In: ICWSM (2014)
Pak, A., Paroubek, P.: Twitter as a corpus for sentiment analysis and opinion mining. In: LREC (2010)
Petrovic, S., Osborne, M., McCreadie, R., Macdonald, C., Ounis, I., Shrimpton, L.: Can twitter replace newswire for breaking news? In: ICWSM (2013)
Sharifi, B., Hutton, M.A., Kalita, J.K.: Experiments in microblog summarization. In: SocialCom/PASSAT, pp. 49–56 (2010)
Shi, B., Ifrim, G., Hurley, N.: Be in the know: Connecting news articles to relevant twitter conversations. CoRR, Vol. abs/1405.3117 (2014)
Shraer, A., Gurevich, M., Fontoura, M., Josifovski, V.: Top-k publish-subscribe for social annotation of news. PVLDB 6(6), 385–396 (2013)
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Onishi, S., Yamaguchi, Y., Kitagawa, H. (2015). Real-Time Relevance Matching of News and Tweets. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2015 Conferences. OTM 2015. Lecture Notes in Computer Science(), vol 9415. Springer, Cham. https://doi.org/10.1007/978-3-319-26148-5_7
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DOI: https://doi.org/10.1007/978-3-319-26148-5_7
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