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Predicting Question Response Rate in Different Topics in Zhihu

In: Liss 2020

Author

Listed:
  • Hong-de Liu

    (China University of Petroleum)

  • Ming Li

    (China University of Petroleum)

  • Cheng-qi Yang

    (China University of Petroleum)

Abstract

As a popular social question answering platform in China, Zhihu is facing the problem of a low question response rate. In order to find out the reason, we conduct a predictive research on the question response rate of different topics. By comparing the influencing factors of the question response rate of different topics, we tend to find a solution which is beneficial to increase users’ activity. We obtain a total of 4293 data in six hot topics. A binary logistic regression method is used to construct a question response rate prediction model for different topics from the characteristics of the question and the questioner. Using 600 data to verify 6 prediction models, the prediction accuracy rate of which is more than 80%. We find carrier richness, question length, polite expression, expression of urgency and reliability of the questioner affect the question response rate of six topics. Moreover, posting period, affective tendency expression, the questioners degree of social learning, extended centrality and inward centrality cast different effects in different topics.

Suggested Citation

  • Hong-de Liu & Ming Li & Cheng-qi Yang, 2021. "Predicting Question Response Rate in Different Topics in Zhihu," Springer Books, in: Shifeng Liu & Gábor Bohács & Xianliang Shi & Xiaopu Shang & Anqiang Huang (ed.), Liss 2020, pages 291-303, Springer.
    • Handle: RePEc:spr:sprchp:978-981-33-4359-7_21
    DOI: 10.1007/978-981-33-4359-7_21
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