You followed my bot! Transforming robots into influential users in Twitter
Systems like Klout and Twitalyzer were developed as an attempt to measure the influence of users within social networks. Although the algorithms used by these systems are not public known, they have been widely used to rank users according to their influence, especially in the Twitter social network. As media companies might base their viral marketing campaigns on influence scores, users might attempt to boost their influence scores with simple mechanisms like following unknown users to be followed back or even interacting with those who reciprocate these actions. In this paper, we investigate if widely used influence scores are vulnerable and easy to manipulate. Our approach consists of developing Twitter bot accounts able to interact with real users to verify strategies that can increase their influence scores according to different systems. Our results show that it is possible to become influential using very simple strategies, suggesting that these systems should review their influence score algorithms to avoid accounting with automatic activity.