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Research on the Method of Identifying Opinion Leaders Based on Online Word-of-Mouth

In: Smart Service Systems, Operations Management, and Analytics

Author

Listed:
  • Chenglin He

    (Nanjing University of Aeronautics and Astronautics)

  • Shan Li

    (Nanjing University of Aeronautics and Astronautics)

  • Yehui Yao

    (Nanjing University of Aeronautics and Astronautics)

  • Yu Ding

    (Nanjing University of Aeronautics and Astronautics)

Abstract

Opinion leadersOpinion leader are attracting increasing attention on practitioners and academics. Opinion leaders’ online Word-of-Mouth (WOM) plays a guiding and decisive role in reducing risks and uncertainty faced by users in online shopping. It is of great significance of businesses and enterprises to effectively identify opinion leadersOpinion leader. This study proposes an integrated method by looking at not only essential indicators of reviewers but also the review characteristics. The RFMRFM model is used to evaluate the activity of reviewers. Four variables L (text length), T (period time), P (with or without a picture) and S (sentiment intensity) are derived to measure review helpfulness from review text. And two effective networks are built using the Artificial Neural Network (ANN)Artificial Neural Network (ANN). This study utilizes a real-life data set from Dianping.com for analysis and designs three different experiments to verify the identification effect. The results show that this method can scientifically and effectively identify the opinion leadersOpinion leader and analyze the influence of opinion leaders.

Suggested Citation

  • Chenglin He & Shan Li & Yehui Yao & Yu Ding, 2020. "Research on the Method of Identifying Opinion Leaders Based on Online Word-of-Mouth," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu & Weiwei Chen (ed.), Smart Service Systems, Operations Management, and Analytics, pages 209-222, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-30967-1_19
    DOI: 10.1007/978-3-030-30967-1_19
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