Understanding Awareness Diffusion in Microblogging

The word-of-mouth (WOM) marketing has been recognized to be the most credible and important marketing approach, especially when the social network websites have become an internet phenomenon. Previous studies have shown that the dispersion of WOM across various communities has significant positive impact on product adoption (Godes and Mayzlin, 2004). On the other hand, the homophily theory in sociology indicates that people usually feel more comfortable talking with those who are similar to them than those who are not. Such psychological discomfort caused by communicating to dissimilar people may cause information “stuck” in clusters of similar people in a social network (Touchey, 1974). As a result, it is usually more difficult for information to traverse across the boundary of online communities than to spread within a community. However, it appears that the setting at a microblogging website such as twiter.com enables easier cross-boundary message dispersion. The main reason is that when a person retweets a message received from people he follows, the message is broadcasted to his followers, a group of people who might be very different from those this person follows. Given that microblogging has been an important means for organizations to communicate with prospective/existing customers, such retweet behavior becomes crucial for organizations’ online branding endeavors. This study thus seeks to uncover the factors associated with the retweeting behavior of participants at twitter.com by using content and social network analysis technologies. We believe that the results from this project will have both significant contribution to academic research and important implication for practitioners

Social Capital in the ICT Sector – A Network Perspective on Executive Turnover and Startup Performance

Recently, The Wall Street Journal proclaimed the “War for Internet Talent” among companies in the Information and Communication Technology (ICT) sector. At the same time, talented employees become entrepreneurial and establish their own startups. We aim to provide evidence that startup performance is not based exclusively on access to talent, in the sense of individual human capital, but is also determined by a social capital aspect resulting from their executives’ turnover history. We apply social network analysis (SNA) combined with logistical regression on a large dataset of companies and executives in the ICT sector. Our study contributes to turnover and entrepreneurship in information systems research, as well as to social capital and multilevel systems research. Furthermore, we shed a light on turnover patterns in the ICT sector, contribute to a better understanding of success factors for startups, and provide a practical measure to help identify and differentiate key employees