在线社交网络中的选择性行为

Chunjing Xiao, Ling Su, J. Bi, Yuxia Xue, A. Kuzmanovic
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引用次数: 11

摘要

根据经典的传播理论,即Gate keeping和Selective Exposure,个体在传播和接收信息时,会根据自己的心理偏好产生选择性行为。与这两种理论相关的选择行为已经分别进行了广泛的研究。同时,由于在线社交网络(OSNs)的出现,可以收集更大规模的反馈和用户信息。在本文中,基于这些数据,我们分析了用户属性(如年龄、性别和文化背景)之间的相关性,并通过将用户标记为YouTube、Flickr和Twitter上的传播者和/或受众来分析他们的选择行为。我们发现,尽管osn中有大量可用的内容,但用户的选择范围相对较小,并且确实表现出选择性的行为属性。特别是,他们最关注的是具有相似属性的传播者所发布的内容,即性别、年龄和国家。尽管如此,我们也发现了三种osn在选择行为方面的显著差异和共性。特别是,(i)三种网络的传播者、受众和双重角色用户的比例和属性存在较大差异;(ii) Flickr的信息全球传播水平几乎是Twitter的两倍,YouTube的信息全球传播水平约为中位数;(iii)对于特定国家,不同osn的信息全球传播水平是不同的。对于一个特定的OSN,不同国家的情况是不同的,(iv)尽管OSN中普遍存在双重角色用户,但大多数此类用户要么是传播者,要么是受众,但不是两者都非常活跃。我们的发现不仅有助于理解这两种理论,而且还可以应用于从广告和推荐系统到开发预测模型的各个领域。
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Selective Behavior in Online Social Networks
According to the classical communication theories, known as Gate keeping and Selective Exposure, individuals tend to have selective behavior when they disseminate and receive information based on their psychological preferences. Selective behavior related to these two theories have been broadly studied separately. While, thanks to the advent of Online Social Networks (OSNs), larger-scale feedback and user information can be collected. In this paper, based on these data, We analyze the correlation among users' properties (such as age, gender, and cultural background) and analyze their selective behavior by tagging users as disseminators and/or audiences in YouTube, Flickr, and Twitter. We find that despite enormous amount of content available in OSNs, users have a comparatively small selective range and do exhibit selective behavior properties. In particular, they pay the most attention to the content published by disseminators that share similar properties, i.e., gender, age, and country. Nonetheless, we also find significant differences and commonalities among the three OSNs with respect to selective behavior. In particular, (i) the proportion and properties of disseminators, audiences, and dual-role users are quite different for the three networks, (ii) the global level of information spread in Flickr is almost two times than that in Twitter and YouTube is approximately the median one, (iii) For a given country, the global level of information spread is different for different OSNs. For a given OSN, it is different for different countries, (iv) despite ubiquitous presence of dual-role users in OSNs, most of such users are very active as either disseminators or audiences, but not both. Our findings are not only useful for understanding these two theories, but also have applications ranging from advertising and recommendation systems to developing predicting models.
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