Building a Social Network for Success
研究品牌或个人如何通过社交网络活动管理网络结构并驱动长期成功，以音乐艺术家数据为例，使用贝叶斯模型分析网络活动对流行度的异质动态影响。
This article proposes a framework for studying how a brand, firm, or individual can use networking activities to manage a social network and drive its success. Using data from ego networks of music artists, the article models how artists can enhance their social networking presence and stimulate relationships between fans to achieve long-term benefits in terms of music plays. The authors use a Bayesian modeling framework to model the heterogeneous and dynamic impact of networking activities on network structure and on music popularity, while relying on instrumental variables from another independent online social network to handle potential endogeneity. The results imply that artists can shape network structure via marketing activities and thereby achieve a long-term impact on success that far exceeds the direct and short-term impact in magnitude. Specifically, improving the density of ego networks enables long-term effects beyond those that stem from growth in network size.