Influence attribution in citation networks
University:Aalto University, Finland
Time:11:00am (coffee: 10:30)
Finding who and what is influential is an ever-occurring question. Many methods that aim at characterizing important items or inuential individuals have been developed in areas such as, bibliomet- rics, social-network analysis, link analysis, and web search. In this talk I will study the problem of attributing inuence scores to individuals who accomplish tasks in a collaborative manner. Individuals are assumed to build small teams, in dierent and diverse ways, in order to accomplish atomic tasks. For each task an assessment of success is given, and the goal is to attribute those team-wise scores to the individuals.
One challenge is that individuals in strong coalitions are favored against individuals in weaker coalitions, so the objective is to assign fair attributions that account for such biasing. I will discuss an iterative algorithm for solving this problem that is based on the con- cept of Shapley value. The proposed method is applicable to a variety of scenarios, for example, attributing influence scores to scientists who collaborate in published articles, or employees of a company who partic- ipate in projects. The method has been evaluated on two real datasets: ISI Web of Science publication data and the Internet Movie Database.