"Popularity Effect" in User-Generated Content: Evidence from Online Product Reviews
Online product reviews are increasingly important for consumer decisions, yet we still know little about how reviews are generated in the first place. In an effort to gather more reviews, many websites encourage user interactions such as allowing one user to subscribe to another. Do these interactio...
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| Veröffentlicht in: | Information systems research 2014-06, Vol.25 (2), p.222-238 |
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| creator | Goes, Paulo B. Lin, Mingfeng Yeung, Ching-man Au |
| description | Online product reviews are increasingly important for consumer decisions, yet we still know little about how reviews are generated in the first place. In an effort to gather more reviews, many websites encourage user interactions such as allowing one user to subscribe to another. Do these interactions actually facilitate the generation of product reviews? More importantly, what kind of reviews do such interactions induce? We study these questions using data from one of the largest product review websites where users can subscribe to one another. By applying both panel data and a flexible matching method, we find that as users become more popular, they produce more reviews and more
objective
reviews; however, their numeric ratings also systematically change and become more negative and more varied. Such trade-off has not been previously documented and has important implications for both product review and other user-generated content websites. |
| doi_str_mv | 10.1287/isre.2013.0512 |
| format | Article |
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objective
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objective
reviews; however, their numeric ratings also systematically change and become more negative and more varied. 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objective
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| fulltext | fulltext |
| identifier | ISSN: 1047-7047 |
| ispartof | Information systems research, 2014-06, Vol.25 (2), p.222-238 |
| issn | 1047-7047 1526-5536 |
| language | eng |
| recordid | cdi_proquest_journals_1540457979 |
| source | Jstor Complete Legacy; INFORMS PubsOnLine; EBSCOhost Business Source Complete |
| subjects | Audiences Behavior Consumers Customer feedback Data mining Decision making Hypotheses Influence Information services Information services industry matching online community Online social networks opinion leader Popularity Product reviews Ratings & rankings Services social media Social networks Studies text mining Trust User generated content Virtual communities Websites Writers |
| title | "Popularity Effect" in User-Generated Content: Evidence from Online Product Reviews |
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