Abstract
This paper focuses on the review voting in online communities, which allows users to express their own opinions in terms of User-generated Content (UGC). However, the sustainable development of online communities is likely to be affected by the social influence of UGC. In this paper, we study the so-called crowd intelligence paradox of review voting in online communities. The crowd intelligence paradox means that the quality of reviews is not highly connected with the increasing of review votes. This implies that a review with many votes is likely to be of low quality, and a review with few votes is likely to be of high quality. The crowd intelligence paradox existing in online communities inhibits users’ wishes of participating in social networks and may impact the sustainable development of online communities. Aiming to demonstrate the existence of the crowd intelligence paradox in online communities, we first analyzed a large set of reviews crawled from Net Ease Cloud Music, which is one of the most popular online communities in China. The maximum likelihood (ML) and the hierarchical regression approaches are used in this step. Then, we construct a new research model called the Voting Adoption Model (VAM) to study how different factors impact the crowd intelligence paradox in online communities. Particularly, we propose six hypotheses based on the VAM model and conduct experiments based on the measurement model and the structural model to evaluate the hypotheses. The results show that the quality of reviews is not influential to review votes, and the hot-site attribute is a dominant factor influencing review voting. In addition, the variables of the VAM model, including information credibility, perceived ease of use, and social influence have significant impacts on review voting. Finally, based on the empirical study, we present some research implications and suggestions for online communities to realize healthy and sustainable development in the future.
Highlights
With the rapid development of social networks, more and more people tend to spend a lot of time in online communities, such as online video sharing platforms or online music platforms
Aiming at answering factors influencing the crowd intelligence paradox, we present a new research model named Voting Adoption Model (VAM), which is an integration of the information adoption model (IAM), the self-determination theory (SDT), and the signal theory
We analyzed the sub-dataset with the hierarchical regression method using Stata 14.0 and the ordinary least squares method (OLS)
Summary
With the rapid development of social networks, more and more people tend to spend a lot of time in online communities, such as online video sharing platforms or online music platforms. Online communities are mostly based on the application of User-Generated Content (UGC), which allows users to create personalized information and share them to online communities [1]. We note that there is a paradox of review voting in online communities, i.e., the number of votes is not consistent with the quality of the corresponding content. Some content with low quality surprisingly receives more votes than others with high quality. Such a paradox has a close relationship with the crowd intelligence of online communities, and might have an impact on the sustainable development of online communities. There are no studies focusing on the paradox of review voting in online communities
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
