Temporal multi-layer network construction from major news events

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Abstract

Good news should answer the following questions: ‘Who?’, ‘Where?’, ‘When?’, ‘What?’, and possibly ‘Why?’. We present an approach which extracts interesting events from thousands of daily news.We construct a time-varying, threelayer network where the nodes are entities of interest in the news. The temporal aspect of the network answers the ‘When?’ question. The layers are: (1) the co-occurrence of entities which answers the ‘Who?’ or ‘Where?’, (2) the summary layer which answers the ‘What?’, and (3) the sentiment layer which labels the links as ‘good’ or ‘bad’ news. We demonstrate the news network evolution over a period of four years in an interactive web portal.

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Sluban, B., Grčar, M., & Mozetič, I. (2016). Temporal multi-layer network construction from major news events. In Studies in Computational Intelligence (Vol. 644, pp. 29–41). Springer Verlag. https://doi.org/10.1007/978-3-319-30569-1_3

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