Abstract
Abstract
Purpose – Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.
Design/methodology/approach – This study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).
Findings – The 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/implications – This study provides a comprehensive and theoretical understanding of reviewers’ motivation for writing long reviews.
Practical implications – Online communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.
Originality/value – Many 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.
Keywords Online review, Review length, Self-determination theory, Machine learning, Sentiment analysis, Big data
Paper type Research paper
Purpose – Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.
Design/methodology/approach – This study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).
Findings – The 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/implications – This study provides a comprehensive and theoretical understanding of reviewers’ motivation for writing long reviews.
Practical implications – Online communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.
Originality/value – Many 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.
Keywords Online review, Review length, Self-determination theory, Machine learning, Sentiment analysis, Big data
Paper type Research paper
| Original language | English |
|---|---|
| Pages (from-to) | 1-27 |
| Number of pages | 27 |
| Journal | Internet Research |
| DOIs | |
| Publication status | Published - 16 Dec 2023 |