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A survey of sentiment analysis in social media

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Abstract

Sentiments or opinions from social media provide the most up-to-date and inclusive information, due to the proliferation of social media and the low barrier for posting the message. Despite the growing importance of sentiment analysis, this area lacks a concise and systematic arrangement of prior efforts. It is essential to: (1) analyze its progress over the years, (2) provide an overview of the main advances achieved so far, and (3) outline remaining limitations. Several essential aspects, therefore, are addressed within the scope of this survey. On the one hand, this paper focuses on presenting typical methods from three different perspectives (task-oriented, granularity-oriented, methodology-oriented) in the area of sentiment analysis. Specifically, a large quantity of techniques and methods are categorized and compared. On the other hand, different types of data and advanced tools for research are introduced, as well as their limitations. On the basis of these materials, the essential prospects lying ahead for sentiment analysis are identified and discussed.

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Notes

  1. http://www.journalism.org/2014/05/22/the-eu-elections-on-twitter/.

  2. http://www.queenslandimage.com/.

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Acknowledgments

This research has been supported by Australian Research Council Discovery Project (Grant NO. DP160104075), the Fundamental Research Funds for the Central Universities (Grant NO. 2412017QD028), China Postdoctoral Science Foundation (Grant No. 2017M621192), the Scientific and Technological Development Program of Jilin Province (Grant No. 20180520022JH). Besides, Dr. Lin YUE has been awarded a scholarship under the State Scholarship Fund to finish this research at the University of Queensland; this work also has been awarded by China Scholarship Council (CSC). We feel grateful to Prof. Xiaofang Zhou at the University of Queensland and Prof. Ivor Tsang at University of Technology Sydney, who once offered us valuable suggestions during the study period. Our sincere thanks are also given to the anonymous reviewers, from whose comments we have benefited greatly.

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Authors and Affiliations

  1. School of Information Science and Technology, Northeast Normal University, Changchun, China

    Lin Yue & Minghao Yin

  2. Key Laboratory of Applied Statistics of MOE, Northeast Normal University, Changchun, China

    Lin Yue & Minghao Yin

  3. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia

    Lin Yue, Weitong Chen & Xue Li

  4. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Xue Li

  5. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China

    Lin Yue, Wanli Zuo & Minghao Yin

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  1. Lin Yue
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  2. Weitong Chen
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  3. Xue Li
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  4. Wanli Zuo
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  5. Minghao Yin
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Correspondence to Weitong Chen or Minghao Yin.

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Yue, L., Chen, W., Li, X. et al. A survey of sentiment analysis in social media. Knowl Inf Syst 60, 617–663 (2019). https://doi.org/10.1007/s10115-018-1236-4

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