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Which factors affect the duration of hot topics on social media platforms?

Author

Listed:
  • Jinlou Zhao

    (Harbin Engineering University)

  • Hongyu Gao

    (Harbin Engineering University)

  • Yongli Li

    (Northeastern University)

  • Jiaguo Liu

    (Harbin Engineering University)

Abstract

Hot topics, as a common phenomenon on social media platform, play a major role in public opinion. This paper aims to discuss the issues about the duration of hot topics: which factors influence the duration of a hot topic on a social media platform? To answer this question, Cox regression model of survival analysis was introduced to make empirical analysis. The survey data containing 60 hot topics from 2011 to 2013 was collected from a popular social media platform of China. Besides, model verification is implemented to validate the adopted model and the calibrated parameters. As a result, this paper finds that the number of participants and opinion leaders have a significant positive influence on an incident’s duration, and official response times have a significant negative impact; whereas, the number of attending media has no significant impact. Furthermore, the prediction accuracy in the validation is up to 85 %, which implies that the obtained results would be robust. The established model and the designed empirical analysis are demonstrated to be adaptable to analyze the duration of hot topics, and three factors are found to effect the duration of a hot topic based on our collected dataset. Our analytic method could also be adopted in numerous problems related to the duration issues in the field of information management.

Suggested Citation

  • Jinlou Zhao & Hongyu Gao & Yongli Li & Jiaguo Liu, 2017. "Which factors affect the duration of hot topics on social media platforms?," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2395-2407, September.
  • Handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0395-1
    DOI: 10.1007/s11135-016-0395-1
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    References listed on IDEAS

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    1. Young Mee Shin & Seung Chang Lee & Bongsik Shin & Ho Geun Lee, 2010. "Examining influencing factors of post-adoption usage of mobile internet: Focus on the user perception of supplier-side attributes," Information Systems Frontiers, Springer, vol. 12(5), pages 595-606, November.
    2. Show-Ling Jang & Jennifer H. Chen, 2011. "What determines how long an innovative spell will last?," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 65-76, January.
    3. Hung-Pin Shih & Echo Huang, 2014. "Influences of Web interactivity and social identity and bonds on the quality of online discussion in a virtual community," Information Systems Frontiers, Springer, vol. 16(4), pages 627-641, September.
    4. Bo Wang & Shengbo Liu & Kun Ding & Zeyuan Liu & Jing Xu, 2014. "Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 685-704, October.
    5. Yue Wu & Yong Hu & Xiao-Hai He, 2013. "Public Opinion Formation Model Based On Opinion Entropy," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(11), pages 1-13.
    6. Yuen-Hsien Tseng & Yu-I Lin & Yi-Yang Lee & Wen-Chi Hung & Chun-Hsiang Lee, 2009. "A comparison of methods for detecting hot topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 73-90, October.
    7. Sujin Choi & Ji-young Park & Han Woo Park, 2012. "Using social media data to explore communication processes within South Korean online innovation communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 43-56, January.
    8. MinJae Lee & JinKyu Lee, 2012. "The impact of information security failure on customer behaviors: A study on a large-scale hacking incident on the internet," Information Systems Frontiers, Springer, vol. 14(2), pages 375-393, April.
    9. Bing Wu & Shan Jiang & Hsinchun Chen, 2015. "The impact of individual attributes on knowledge diffusion in web forums," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2221-2236, November.
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    Cited by:

    1. Yaxue Ma & Zhichao Ba & Yuxiang Zhao & Jin Mao & Gang Li, 2021. "Understanding and predicting the dissemination of scientific papers on social media: a two-step simultaneous equation modeling–artificial neural network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7051-7085, August.

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