With the prevalence of online review websites, understanding online reviewer characteristics has become important, as such an understanding provides brand managers with opportunities to segment their markets, target influencers, and develop effective marketing strategies. Nonetheless, past studies have overlooked the role of network structural positions in the characteristics of online reviewers. Accordingly, using data from Yelp websites as samples, this study attempted to explore the differences in reviewer characteristics by network structural positions. The study used multiple data collection and analysis approaches, including web scraping, network analysis, and statistical analysis. The results of this study showed that compared to peripheral reviewers, core reviewers exhibited significantly more photos and brands reviewed and included a higher proportion of early reviewers. The study has significant theoretical and practical implications for researchers and brand managers who are interested in understanding online review markets.

随着在线评论网站的盛行，了解在线评论者的特征变得很重要，因为这种理解为品牌经理提供了细分市场、瞄准影响者和制定有效营销策略的机会。尽管如此，过去的研究忽视了网络结构位置在在线评论者特征中的作用。因此，本研究以 Yelp 网站的数据为样本，试图探讨不同网络结构位置的评论者特征的差异。该研究使用了多种数据收集和分析方法，包括网络抓取、网络分析和统计分析。本研究结果表明，与外围审稿人相比，核心评论者展示了更多的照片和被评论的品牌，并且包括更高比例的早期评论者。该研究对有兴趣了解在线评论市场的研究人员和品牌经理具有重要的理论和实践意义。