Motivation for writing long online reviews: a big data analysis of an anime community

被引:2
作者
Leung, Kevin [1 ]
Cho, Vincent [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Management & Mkt, Kowloon, Hong Kong, Peoples R China
关键词
Online review; Review length; Self-determination theory; Machine learning; Sentiment analysis; Big data; SELF-DETERMINATION THEORY; WORD-OF-MOUTH; INTRINSIC MOTIVATION; STRENGTH DETECTION; PRODUCT REVIEWS; HELPFULNESS; SENTIMENT; PERFORMANCE; EXPERIENCE; EMOTION;
D O I
10.1108/INTR-07-2022-0548
中图分类号
F [经济];
学科分类号
02 ;
摘要
PurposeBased on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.Design/methodology/approachThis study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).FindingsThe findings show that intensity of emotions, experience in writing reviews and helpful votes in past reviews are the most important factors and positively influence review length. The overall rating of the anime moderates the effects of some motivation factors. Moreover, reviewers commenting on their favorite or nonfavorite anime also have varied motivation factors. Furthermore, this study has addressed the p-value problem due to the large sample size.Research limitations/implicationsThis study provides a comprehensive and theoretical understanding of reviewers' motivation for writing long reviews.Practical implicationsOnline communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.Originality/valueMany past studies have investigated what reviews are more helpful. Review length is the most important factor of review helpfulness and positively affects it. However, few studies have examined the determinants of review length. This study attempts to address this issue.
引用
收藏
页码:1845 / 1871
页数:27
相关论文
共 67 条
[1]  
Aiello L., 2014, Handbook of Research on Management of Cultural Products: E-Relationship Marketing and Accessibility Perspectives
[2]   Do product reviews really reduce search costs? [J].
Amblee, Naveen ;
Ullah, Rahat ;
Kim, Wonjoon .
JOURNAL OF ORGANIZATIONAL COMPUTING AND ELECTRONIC COMMERCE, 2017, 27 (03) :199-217
[3]   Word of Mouth, Observed Adoptions, and Anime-Watching Decisions: The Role of the Personal vs. the Community Network [J].
Ameri, Mina ;
Honka, Elisabeth ;
Xie, Ying .
MARKETING SCIENCE, 2019, 38 (04) :567-583
[4]  
Bakshi Shuchita, 2021, Leisure/Loisir, V45, P603, DOI 10.1080/14927713.2021.1924076
[5]   WHAT MOTIVATES POSTING ONLINE TRAVEL REVIEWS? INTEGRATING GRATIFICATIONS WITH TECHNOLOGICAL ACCEPTANCE FACTORS [J].
Bakshi, Shuchita ;
Dogra, Nikita ;
Gupta, Anil .
TOURISM AND HOSPITALITY MANAGEMENT-CROATIA, 2019, 25 (02) :335-354
[6]  
Baumeister R.F., 2001, Rev. Gen. Psychol., V5, P323, DOI [DOI 10.1037/1089-2680.5.4.323, 10.1037//1089-2680.5.4.323]
[7]   Incentives and prosocial behavior [J].
Benabou, Roland ;
Tirole, Jean .
AMERICAN ECONOMIC REVIEW, 2006, 96 (05) :1652-1678
[8]   Freedom to feel: Aself-determinationtheory account of emotion regulation [J].
Benita, Moti .
SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS, 2020, 14 (11)
[9]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[10]  
Cameron AC, 2013, Regression Analysis of Count Data place unknown