id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-285522-3gv6469y	Bello-Orgaz, Gema	Social big data: Recent achievements and new challenges	2015-08-28		.txt	text/plain	13157	724	48	Big data has become an important issue for a large number of research areas such as data mining, machine learning, computational intelligence, information fusion, the semantic Web, and social networks. The rise of different big data frameworks such as Apache Hadoop and, more recently, Spark, for massive data processing based on the MapReduce paradigm has allowed for the efficient utilisation of data mining methods and machine learning algorithms in different domains. Currently, the exponential growth of social media has created serious problems for traditional data analysis algorithms and techniques (such as data mining, statistics, machine learning, and so on) due to their high computational complexity for large datasets. This section provides a description of the basic methods and algorithms related to network analytics, community detection, text analysis, information diffusion, and information fusion, which are the areas currently used to analyse and process information from social-based sources.	./cache/cord-285522-3gv6469y.txt	./txt/cord-285522-3gv6469y.txt