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SentiStory: multi-grained sentiment analysis and event summarization with crowdsourced social media data

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Abstract

The massive social media data bring timely, multi-dimensional and rich information. Recently, many researchers have worked on event summarization with crowdsourced social media data. While existing works mostly focus on text-based summary, they only summarize representative microblogs. Public sentiment for the event is also valuable; however, this is not explored in microblogging event summary. In this paper, we propose SentiStory, which is a multi-grained sentiment analysis and event summarization system that summarizes event from two levels: coarse-grained and fine-grained sentiment analysis. In coarse-grained analysis, it discovers microblogs which are important in sentiment, while in fine-grained analysis, it detects significant change of sentiment in the event and identifies which microblog causes the change. Specifically, the proposed system comprises two modules: (1) the microblog preprocessing module firstly reduces redundant information and extracts useful information from the microblog database, and then, it separates different aspects of the event and clusters the same aspect together in a clue. (2) The multi-grained sentiment analysis model analyzes microblogs from two levels: coarse-grained and fine-grained. We perform detailed experimental study on real dataset collected from Sina Weibo, and the results demonstrate the effectiveness of our approach.

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Notes

  1. http://weibo.com/.

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Acknowledgements

This work was partially supported by the National Basic Research Program of China (No. 2015CB352400), the National Natural Science Foundation of China (Nos. 61332005, 61373119).

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Authors and Affiliations

  1. School of Computer Science, Northwestern Polytechnical University, Xi’an, 710129, China

    Yi Ouyang, Bin Guo, Jiafan Zhang, Zhiwen Yu & Xingshe Zhou

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  1. Yi Ouyang
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  2. Bin Guo
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  3. Jiafan Zhang
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  4. Zhiwen Yu
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  5. Xingshe Zhou
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Correspondence to Bin Guo.

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Ouyang, Y., Guo, B., Zhang, J. et al. SentiStory: multi-grained sentiment analysis and event summarization with crowdsourced social media data. Pers Ubiquit Comput 21, 97–111 (2017). https://doi.org/10.1007/s00779-016-0977-x

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