The Study of Predicting Social Topic Trends

  • Sung-Shun WengEmail author
  • Huai-Wen Hsu
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 41)


The rapid growth of the social media leads people participate in the popular topics that have been discussed in our daily lives by the social networks. Large amounts of word-of-mouth and news event have flood the social media. Recognizing the trends of the main topics that people care about from the huge and various social messages, grasping the business opportunities and adopting appropriate strategies have become an important lesson for business, governmental and non-governmental organizations. Previous research on social topic detection has focused on sentiment analysis for content. This study integrates the hidden markov model and latent dirichlet allocation topic model to forecast trends of the social topics based on time series data of user reviews. Experimental results on real dataset showed that the approach proposed by this study are able to recognize the latent social topics, keywords and forecast the trends of social topics effectively on the social media.


Social media Topic detection Time series Trend prediction 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.National Taipei University of TechnologyTaipeiTaiwan

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