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Towards Sustainable Development of Online Communities in the Big Data Era: A Study of the Causes and Possible Consequence of Voting on User Reviews

机译:在大数据时代的在线社区的可持续发展:对用户评论投票的原因和可能后果的研究

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摘要

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.
机译:本文重点介绍在线社区中的投票,这允许用户在用户生成的内容(UGC)方面表达自己的意见。但是,在线社区的可持续发展可能会受到UGC社会影响的影响。在本文中,我们研究了在线社区中所谓的人群情报悖论。人群情报悖论意味着审查质量与评价投票的增加并不高。这意味着与许多投票的审查可能具有低质量,并且少量票价可能具有高质量。在线社区中存在的人群情报悖论抑制了用户对参与社交网络的愿望,并可能影响在线社区的可持续发展。旨在展示在线社区中的人群情报悖论的存在,我们首先分析了一大一大批评论从净缓解云音乐爬行,这是中国最受欢迎的在线社区之一。在此步骤中使用最大可能性(ml)和分层回归方法。然后,我们构建一个名为投票采用模型(VAM)的新研究模型,研究不同的因素如何影响在线社区的人群情报悖论。特别是,我们提出了基于VAM模型的六个假设,并基于测量模型和结构模型进行实验,以评估假设。结果表明,审查投票质量并不有影响力,热门网站属性是影响审查投票的主导因素。此外,VAM模型的变量,包括信息可信度,感知易用性以及社会影响力对审查投票产生重大影响。最后,基于实证研究,我们提出了一些研究含义和在线社区建议,以实现未来健康和可持续发展的研究。

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