Measuring Information Diffusion in an Online Community

被引:92
作者
Garg, Rajiv [1 ]
Smith, Michael D. [1 ]
Telang, Rahul [1 ]
机构
[1] Carnegie Mellon Univ, Heinz Coll, Sch Informat Syst & Management, Pittsburgh, PA 15213 USA
基金
美国国家科学基金会;
关键词
data mining; empirical research; information diffusion; new content discovery; online music community; peer influence; social influence; WORD-OF-MOUTH; SOCIAL INTERACTIONS; PRODUCT REVIEWS; COMMUNICATION; INTERNET; BEHAVIOR; SALES; IDENTIFICATION; CONVERSATIONS; INFLUENTIALS;
D O I
10.2753/MIS0742-1222280202
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Measuring peer influence in social networks is an important business and policy question that has become increasingly salient with the development of globally interconnected information and communication technology networks. However, in spite of the new data sources available today, researchers still face many of the same measurement challenges that have been present in the literature for over four decades: homophily, reflection and selection problems, identifying the source of influence, and determining preexisting knowledge. The goal of this paper is to develop an empirical approach for measuring information diffusion and discovery in online social networks that have these measurement challenges. We develop such an approach and apply it to data collected from 4,000 users of an online music community. We show that peers on such networks significantly increase music discovery. Moreover, we demonstrate how future research can use this method to measure information discovery and diffusion using data from other online social networks.
引用
收藏
页码:11 / 37
页数:27
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