Summary
In this chapter, we introduce a method that can help understand significant and novel — i.e. emerging — topics. Here, KeyGraph is extended to be a method for the analysis and visualization of co-citations between Web pages. Communities, each having members (Web pages, their authors, and readers) with common interests are obtained as graph-based clusters, and an emerging topic is detected as a Web page relevant to multiple communities, corresponding to weak ties between strongly tied communities. An ultimate application of our method might be to understand the chances for governments and citizens, i.e. for discussing and deciding how we should deal with essential factors underlying emergent social events.
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Matsumura, N., Ohsawa, Y. (2003). Chance Discoveries from the WWW. In: Ohsawa, Y., McBurney, P. (eds) Chance Discovery. Advanced Information Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06230-2_21
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DOI: https://doi.org/10.1007/978-3-662-06230-2_21
Publisher Name: Springer, Berlin, Heidelberg
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