Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior.

Tim Althoff, Pranav Jindal, Jure Leskovec
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Abstract

Many of today's most widely used computing applications utilize social networking features and allow users to connect, follow each other, share content, and comment on others' posts. However, despite the widespread adoption of these features, there is little understanding of the consequences that social networking has on user retention, engagement, and online as well as offline behavior. Here, we study how social networks influence user behavior in a physical activity tracking application. We analyze 791 million online and offline actions of 6 million users over the course of 5 years, and show that social networking leads to a significant increase in users' online as well as offline activities. Specifically, we establish a causal effect of how social networks influence user behavior. We show that the creation of new social connections increases user online in-application activity by 30%, user retention by 17%, and user offline real-world physical activity by 7% (about 400 steps per day). By exploiting a natural experiment we distinguish the effect of social influence of new social connections from the simultaneous increase in user's motivation to use the app and take more steps. We show that social influence accounts for 55% of the observed changes in user behavior, while the remaining 45% can be explained by the user's increased motivation to use the app. Further, we show that subsequent, individual edge formations in the social network lead to significant increases in daily steps. These effects diminish with each additional edge and vary based on edge attributes and user demographics. Finally, we utilize these insights to develop a model that accurately predicts which users will be most influenced by the creation of new social network connections.

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在线行动与离线影响:在线社交网络如何影响在线和离线用户行为》(Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior.
当今许多使用最广泛的计算机应用软件都利用了社交网络功能,允许用户相互连接、关注、分享内容和评论他人的帖子。然而,尽管这些功能被广泛采用,人们对社交网络对用户保留、参与、在线和离线行为的影响却知之甚少。在此,我们研究了社交网络如何影响用户在体力活动跟踪应用中的行为。我们分析了 600 万用户在 5 年时间里的 7.91 亿次在线和离线行为,结果表明社交网络会显著增加用户的在线和离线活动。具体来说,我们建立了社交网络影响用户行为的因果效应。我们的研究表明,新社交关系的建立使用户在线应用内活动增加了 30%,用户留存率增加了 17%,用户线下真实世界体力活动增加了 7%(每天约 400 步)。通过利用自然实验,我们将新社交关系的社交影响效果与用户使用应用程序和增加步数的动力同时提高的效果区分开来。我们的研究表明,在观察到的用户行为变化中,社交影响占 55%,而剩下的 45% 可以用用户使用该应用的积极性提高来解释。此外,我们还表明,社交网络中随后形成的单个边缘会显著增加每日步数。每增加一个边缘,这些影响就会减弱,并且会根据边缘属性和用户人口统计学特征而有所不同。最后,我们利用这些见解建立了一个模型,该模型可以准确预测哪些用户会受到新社交网络连接的最大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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