用户努力和网络结构对网络信息获取的中介作用
User Effort and Network Structure Mediate Access to Information in Networks
摘要：
在社会网络中，个体对信息的获取取决于信息的分布以及个体在网络中的位置。然而，个人管理其社会关系和处理信息的能力有限。在这项工作中，我们研究了这种有限的能力和网络结构如何相互作用，以影响信息的多样性社会媒体用户接收。以前的研究网络在信息获取的作用是有限的，在他们的能力来衡量信息的多样性。我们通过观察社交媒体用户与其追随者在线分享的消息来了解他们感兴趣的话题，从而解决这个问题。我们提出了一个概率模型，将人类的认知约束的生成模型的信息共享。然后，我们使用模型学习的主题来衡量用户从社交媒体联系人那里获得的信息的多样性。我们确认，用户在结构上不同的网络位置，桥梁，否则断开区域的追随者图，暴露于更多样化的信息。此外，我们确定用户的努力作为一个重要的变量，介导访问不同的信息在社交媒体。在网站上投入更多精力的用户不仅比参与度较低的用户在网络中处于结构上更多样化的位置，而且当位于类似的网络位置时，他们也会收到更多样化的信息。这些发现表明，网络结构和网络信息获取之间的关系比以前认为的更加微妙。
英文摘要：
Individuals' access to information in a social network depends on its distributed and where in the network individuals position themselves. However, individuals have limited capacity to manage their social connections and process information. In this work, we study how this limited capacity and network structure interact to affect the diversity of information social media users receive. Previous studies of the role of networks in information access were limited in their ability to measure the diversity of information. We address this problem by learning the topics of interest to social media users by observing messages they share online with their followers. We present a probabilistic model that incorporates human cognitive constraints in a generative model of information sharing. We then use the topics learned by the model to measure the diversity of information users receive from their social media contacts. We confirm that users in structurally diverse network positions, which bridge otherwise disconnected regions of the follower graph, are exposed to more diverse information. In addition, we identify user effort as an important variable that mediates access to diverse information in social media. Users who invest more effort into their activity on the site not only place themselves in more structurally diverse positions within the network than the less engaged users, but they also receive more diverse information when located in similar network positions. These findings indicate that the relationship between network structure and access to information in networks is more nuanced than previously thought.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
