通信源
社会化媒体
计算机科学
社交网络(社会语言学)
内容(测量理论)
互联网隐私
业务
万维网
电信
数学
数学分析
作者
Jing Peng,Ashish Agarwal,Kartik Hosanagar,Raghuram Iyengar
摘要
Improving content sharing on social media platforms helps firms enhance the efficacy of their marketing campaigns. The authors study the impact of network overlap—the overlap in network connections between two users—on content sharing in directed social media platforms. The authors propose a hazards model that flexibly captures the impact of three measures of network overlap (i.e., common followees, common followers, and common mutual followers) on content sharing. Using data on content sharing from two directed social media platforms (Twitter and Digg), the authors establish that a receiver is more likely to share content from a sender with whom they share more common followees, common followers, or common mutual followers even after accounting for other measures. In addition, common followers have a higher effect than common mutual followers on the sharing propensity of the receiver. Finally, the effect of common followers and common mutual followers is positive when the content is novel but decreases, and may even become negative, when many others have already shared it. Collectively, these results have a bearing for marketers to more effectively target users for spreading content on social media platforms.
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