title: Leaders in social networks, the Delicious case.
abstract: Finding pertinent information is not limited to search engines. Online communities can amplify the influence of a small number of power users for the benefit of all other users. Users' information foraging in depth and breadth can be greatly enhanced by choosing suitable leaders. For instance in delicious.com, users subscribe to leaders' collection which lead to a deeper and wider reach not achievable with search engines. To consolidate such collective search, it is essential to utilize the leadership topology and identify influential users. Google's PageRank, as a successful search algorithm in the World Wide Web, turns out to be less effective in networks of people. We thus devise an adaptive and parameter-free algorithm, the LeaderRank, to quantify user influence. We show that LeaderRank outperforms PageRank in terms of ranking effectiveness, as well as robustness against manipulations and noisy data. These results suggest that leaders who are aware of their clout may reinforce the development of social networks, and thus the power of collective search.
authors: Research Center for Complex System Science, University of Shanghai for Science and Technology, Shanghai, People's Republic of China.
authors: Linyuan
authors: L
authors: Lü
authors: Yi-Cheng
authors: YC
authors: Zhang
authors: Chi Ho
authors: CH
authors: Yeung
authors: Tao
authors: T
authors: Zhou
mesh_terms: D000465:Algorithms; D006801:Humans; D020407:Internet; D007857:Leadership; D012944:Social Support