Tripartite graph clustering for dynamic sentiment analysis on social media

  title={Tripartite graph clustering for dynamic sentiment analysis on social media},
  author={Linhong Zhu and A. G. Galstyan and James Cheng and Kristina Lerman},
  journal={Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data},
The growing popularity of social media (e.g., Twitter) allows users to easily share information with each other and influence others by expressing their own sentiments on various subjects. In this work, we propose an unsupervised tri-clustering framework, which analyzes both user-level and tweet-level sentiments through co-clustering of a tripartite graph. A compelling feature of the proposed framework is that the quality of sentiment clustering of tweets, users, and features can be mutually… 

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