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arXiv · 1401.2018

On the Real-time Prediction Problems of Bursting Hashtags in Twitter

Shoubin Kong·Qiaozhu Mei·Ling Feng·Zhe Zhao·Fei Ye
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Abstract

Hundreds of thousands of hashtags are generated every day on Twitter. Only a few become bursting topics. Among the few, only some can be predicted in real-time. In this paper, we take the initiative to conduct a systematic study of a series of challenging real-time prediction problems of bursting hashtags. Which hashtags will become bursting? If they do, when will the burst happen? How long will they remain active? And how soon will they fade away? Based on empirical analysis of real data from Twitter, we provide insightful statistics to answer these questions, which span over the entire lifecycles of hashtags.

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Shoubin Kong, Qiaozhu Mei, Ling Feng, Zhe Zhao, Fei Ye. 2014-01-09. On the Real-time Prediction Problems of Bursting Hashtags in Twitter. https://arxiv.org/abs/1401.2018

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