Name
Abstract | ||
|---|---|---|
Most traditional social networks rely on explicitly given relations between users, their friends and followers. In this paper, we go beyond well structured data repositories and create a person-centric network from unstructured text -- the Wikipedia Social Network. To identify persons in Wikipedia, we make use of interwiki links, Wikipedia categories and person related information available in Wikidata. From the co-occurrences of persons on a Wikipedia page we construct a large-scale person-centric network and provide a weighting scheme for the relationship of two persons based on the distances of their mentions within the text. We extract key characteristics of the network such as centrality, clustering coefficient and component sizes for which we find values that are typical for social networks. Using state-of-the-art algorithms for community detection in massive networks, we identify interesting communities and evaluate them against Wikipedia categories. The Wikipedia social network developed this way provides an important source for future social analysis tasks. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2808797.2808840 | Advances in Social Network Analysis and Mining |
Keywords | DocType | Citations |
Wikipedia social network,data repositories,unstructured text,interwiki links,Wikipedia categories,person related information,Wikidata,Wikipedia page,large-scale person-centric network,weighting scheme,network key characteristics,centrality,clustering coefficient,component sizes,community detection,social analysis tasks | Conference | 7 |
PageRank | References | Authors |
0.55 | 21 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Johanna Geiss | 1 | 21 | 3.51 |
| Andreas Spitz | 2 | 49 | 9.19 |
| Michael Gertz | 3 | 179 | 11.68 |