On the role of conductance, geography and topology in predicting hashtag virality

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• 作者：Siddharth Bora ; Harvineet Singh ; Anirban Sen…
• 关键词：Trend prediction ; Information diffusion ; Virality ; Classification ; Twitter social network
• 刊名：Social Network Analysis and Mining
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：5
• 期：1
• 全文大小：1,072 KB
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• 作者单位：Siddharth Bora (1)
  Harvineet Singh (1)
  Anirban Sen (1)
  Amitabha Bagchi (1)
  Parag Singla (1)
  
  1. Indian Institute of Technology, Hauz Khas, New Delhi, India
  
• 刊物类别：Computer Science
• 刊物主题：Sociology
  Data Mining and Knowledge Discovery
  Theoretical Ecology
  Game Theory
  
• 出版者：Springer Wien
• ISSN：1869-5469

文摘

We focus on three aspects of the early spread of a hashtag in order to predict whether it will go viral: the network properties of the subset of users tweeting the hashtag, its geographical properties, and, most importantly, its conductance-related properties. One of our significant contributions is to discover the critical role played by the conductance-based features for the successful prediction of virality. More specifically, we show that the second derivative of the conductance gives an early indication of whether the hashtag is going to go viral or not. We present a detailed experimental evaluation of the effect of our various categories of features on the virality prediction task. When compared to the baselines and the state-of-the-art techniques proposed in the literature our feature set is able to achieve significantly better accuracy on a large dataset of 7.7 million users and all their tweets over a period of month, as well as on existing datasets.