Measuring Information Diffusion in an Online Community

• 成果类型: Article
• 署名作者: Garg, Rajiv; Smith, Michael D.; Telang, Rahul
• 署名单位: Carnegie Mellon University
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.2753/MIS0742-1222280202
• 发表日期: 2011
• 页码: 11-37
• 关键词: word-of-mouth; social interactions; product reviews; COMMUNICATION; internet; BEHAVIOR; sales; identification; conversations; INFLUENTIALS

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.