A comparative study of HITS vs PageRank algorithms for Twitter users analysis

Social Networks such as Facebook, Twitter, Google+ and LinkedIn have millions of users. These networks are constantly evolving and it is a good source of information, both explicitly and implicitly. The analysis of Social Network mainly focuses on the aspect of social networking with an emphasis on mapping relationships, patterns of interaction between user and content information. One of the common research topics focuses on the centrality measures where useful information of the connected people in the social network is represented in a graph. In this paper, we employed two link-based ranking algorithms to analyze the ranking of the users: HITS (Hyperlink-Induced Topic Search) and PageRank. We constructed Twitter user retweet-relationship graph using 21 days worth of data. Lastly, we compared the ranking sequence of the users in addition to their followers count against the average and also whether they are verified Twitter accounts. From the results obtained, both HITS and PageRank showed a similar trend, and more importantly highlighted the importance of the direction of the edges in this work.