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

Chenglin He, Shan Li (), Yehui Yao and Yu Ding
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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

A chapter in Smart Service Systems, Operations Management, and Analytics, 2020, pp 209-222 from Springer

Abstract: 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.

Keywords: Online WOM; Opinion leader; ANN; RFM; WOM content (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-30967-1_19

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DOI: 10.1007/978-3-030-30967-1_19

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