Abstract
21st century sees the rocketing of Internet, which becomes the main platform of information exchange. During the process, opinion leaders play a great part, leading the public opinion and somehow bringing about the economic and social value. Thus, it's meaningful and valuable to recognize them in the network. This study makes use of a trending case's data on Sina Weibo, the biggest social media in China, aiming to build a user feature recognition indicator system based on social network analysis theory. As a three-level system, it first allocates weights to measurement indicators in accordance with Analytic Hierarchy Process (AHP) and identifies opinion leaders by index which generates from Network Centrality Algorithm. After that, back to check whether these selected opinion leaders have all the features an opinion leader should have. It turns out that seven opinion leaders picked by our model are qualified. That is to say, our model is plausible.
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