Reconstructing History of Social Network Evolution Using Web Search Engines

We propose a simple web search engine based method for collecting approximated historical data of temporally changing social adaptive networks, which are rather difficult to obtain experimentally in conventional research methods. In the proposed method, a search query string is combined with additional keywords that specify inclusion/exclusion of specific years to limit the search results to a particular time point. Using the proposed method, we reconstructed the temporal evolution of a social network from 2005 to 2009 of 93 individuals who are important in the US economy. We measured centralities of those individuals for every year and found several illustrative cases where the temporal change of centrality of an individual correctly captured the actual events that are related to him/her over this time period. These results indicate the effectiveness of the proposed method. Limitations and future directions of research are discussed.