Abstract
With the surge of social media, micro-blog has become a popular information share tool, in which retweeting is a basic way to share and spread information. It is important to predict the retweet number for influence measure and precision market. Contemporary methods usually consider it as a classification or regression problem directly, which can be regarded as one-phase models. However, they cannot accurately predict the number of retweet. In this paper, we propose a two-phase model to predict how many times a tweet can be retweeted in Sina Weibo. That is, the model first classifies tweets into several categories, and then does regression on each category. Extensive experiments on real Sina Weibo dataset show that our model is a general framework to achieve better performances than traditional one-phase prediction model without complex feature extraction.
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Twitter, http://en.wikipedia.org/wiki/Twitter
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© 2014 Springer International Publishing Switzerland
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Liu, G., Shi, C., Chen, Q., Wu, B., Qi, J. (2014). A Two-Phase Model for Retweet Number Prediction. In: Li, F., Li, G., Hwang, Sw., Yao, B., Zhang, Z. (eds) Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science, vol 8485. Springer, Cham. https://doi.org/10.1007/978-3-319-08010-9_84
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DOI: https://doi.org/10.1007/978-3-319-08010-9_84
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08009-3
Online ISBN: 978-3-319-08010-9
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