Prediction Model of Movie Box Office Based on Social Media Data

DOI

10.2991/aeecs-18.2018.43How to use a DOI?

Keywords

Box office prediction, Popularity of actor, Popularity of tweets, LDA.

Abstract

In the current movie box office forecasting research, most of the research is based on the basic features in the movie mining, ignoring the influence of actors in the social media platform on movie box office. This paper proposes to crawl the Sina Weibo and comment data, analyzing the popularity of actors and tweets. In addition, we propose the LDA topic model based on popularity of tweets, which as the input of the LDA model. Then the topic distributions based on popularity of actors are obtained. Combined with the above two features, a variety of regression algorithms are used to construct the prediction model. The experimental result shows that the feature extraction method can improve the forecasting effect of the box office to a certain extent.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lili Yuan
AU  - Wen Yu
PY  - 2018/03
DA  - 2018/03
TI  - Prediction Model of Movie Box Office Based on Social Media Data
BT  - Proceedings of the 2018 2nd International Conference on Advances in Energy, Environment and Chemical Science (AEECS 2018)
PB  - Atlantis Press
SP  - 253
EP  - 260
SN  - 2352-5401
UR  - https://doi.org/10.2991/aeecs-18.2018.43
DO  - 10.2991/aeecs-18.2018.43
ID  - Yuan2018/03
ER  -