Slides for a talk delivered at UC3M in the "Management of Multimedia Information on the Internet" masters course.
The talk deals with the elusive topic of influence in (online) social networks.
In the first part I discuss prominence measures --actually, rank prestige measures such as PageRank, HITS, or TunkRank-- as proxies for influence and their performance when tackling with follow spam.
In the second part I describe a different approach that does not rely on the user graph but, instead, exploits interactive behaviors (in this case @mentions). To evaluate such an approach attention measured as clicks in posted URLs is used.
Finally, some conclusions are provided such as the difference between influence and prominence, the good performance of TunkRank when compared to classic PageRank or the benefits of using the velocity-acceleration method described in the second part of the talk.