Leading users and opinion leaders in social networks of university students

Prior research has shown that leading users and opinion leaders may have a positive effect on innovation adoption. This raises a question: identifying the position of leading users and opinion leaders. Therefore, this study attempts to identify leading users and opinion leaders from the perspective of social networks. In the research of social networks, centrality analysis is used to measure the power of each individual by using of UCINET 6.0. We use a sample of 2 school classes consisting 66 college students, hierarchical linear modeling (HLM) is used to test the correlation. We find that eigenvector centrality can positively identify both leading users and opinion leaders. In addition, eigenvector centrality is a more powerful indicator to test centrality in networks by taking the quality of connection in consideration.