Community Detection and Mining in Social Media

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Debiasing Community Detection: The Importance of Lowly Connected Nodes (2019, background): “Community detection is a fundamental task in social network analysis [19], which identifies sub-groups within social networks.”
A Survey of Signed Network Mining in Social Media (2015, background): “In unsigned networks, community detection identifies groups of densely connected nodes [Tang and Liu 2010; Papadopoulos et al. 2012; Ailon et al. 2013].”
Beyond the hype: Big data concepts, methods, and analytics (2015, background): “…betweenness centrality, closeness centrality, and eigenvector centrality (for l of In m t s ( e f w c T o r a o c a o a ( p c p s o e 3 d p – d m s c s a v r v p a m n o c o v t m r t t g a l r m b i c W A. Gandomi, M. Haider / International Journa ore details refer to Tang & Liu, 2010).”
Social Media Mining: An Introduction (2014, methodology): “Betweenness algorithms can be improved using all-pair shortest paths algorithms [Warshall, 1962] or algorithms optimized for computing betweenness, such as the Brandes’ algorithm discussed in [Brandes, 2001; Tang and Liu, 2010].”
Mobile Crowd Sensing and Computing (2015, background): “For example, Tang and Liu [2010] studied the community detection problem of online social media.”