id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_eabupqevvbdzbepciteahrkls4	Konstantinos Konstantinidis	Exploring Twitter communication dynamics with evolving community analysis	2017	34	.pdf	application/pdf	13162	1155	60	Keywords Online social networks, Community evolution detection, Community ranking, community ranking algorithm for a modern online social network application. users are extracted using the Infomap community detection method (Rosvall & Bergstrom, the last and featured step, the evolution is studied in order to rank the communities and dynamic community containers which provide structured access to information. • a novel ranking framework for dynamic communities based on temporal and contextual Another dynamic community detection method used to extract trends was introduced of the complete network, and then applied a dynamic community detection algorithm on Every node in the resulting graphs represents a Twitter user who communicated tweets Table 2 Number of detected dynamic communities with and without the timeslot delay. B), Newman (C, D) and Louvain (E, F) community detection algorithms for the 2014 BBC's Sherlock series (A, C, E) and the 2012 US elections (B, D, F). dynamic community detection in social networks. Community ranking in social network.	./cache/work_eabupqevvbdzbepciteahrkls4.pdf	./txt/work_eabupqevvbdzbepciteahrkls4.txt