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Retweet Prediction Using Context-Aware Coupled Matrix-Tensor Factorization

  • Bo Jiang
  • Feng YiEmail author
  • Jianjun Wu
  • Zhigang Lu
Conference paper
  • 846 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11775)

Abstract

Retweet behavior plays an important role in the process of information diffusion on social networks. Although many researches have been studied the problem of retweet prediction, these studies ignore the important characteristic of multiple contextual dimensions for user’s decision in the modeling process. To this end, we propose a novel multiple dimensions retweet prediction model based on context-aware coupled matrix-tensor factorization (RCMTF). This model first introduces a reference tensor based on the historical retweet behavior patterns to alleviate the problem of data sparsity, and then constructs three contextual factor matrices from user and message and influence dimensions on basis of network structure, message content and historical interactions to further improve the prediction accuracy. Finally, we collaboratively factorizes these contextual factors under matrix and tensor factorization models framework for predicting user’s retweet behaviors. Extensive experiments are conducted to demonstrate the effectiveness of the proposed method on two real-world datasets. The results show that our proposed model outperforms the state-of-the-art methods.

Keywords

Retweet prediction Social network Tensor factorization Matrix factorization Contextual information 

Notes

Acknowledgement

This work is supported by Natural Science Foundation of China (No. 61702508, No. 61802404). This work is also partially supported by Key Laboratory of Network Assessment Technology, Chinese Academy of Sciences.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  2. 2.School of Computer ScienceUniversity of Electronic Science and Technology of China, Zhongshan InstituteZhongshanChina
  3. 3.Beijing College of Politics and LawBeijingChina
  4. 4.School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina

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