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Social network has gained remarkable attention in the last decade. Accessingsocial network sites such as Twitter, Facebook LinkedIn and Google+ through theinternet and the web 2.0 technologies has become more affordable. People arebecoming more interested in and relying on social network for information, newsand opinion of other users on diverse subject matters. The heavy reliance onsocial network sites causes them to generate massive data characterised bythree computational issues namely; size, noise and dynamism. These issues oftenmake social network data very complex to analyse manually, resulting in thepertinent use of computational means of analysing them. Data mining provides awide range of techniques for detecting useful knowledge from massive datasetslike trends, patterns and rules [44]. Data mining techniques are used forinformation retrieval, statistical modelling and machine learning. Thesetechniques employ data pre-processing, data analysis, and data interpretationprocesses in the course of data analysis. This survey discusses different datamining techniques used in mining diverse aspects of the social network overdecades going from the historical techniques to the up-to-date models,including our novel technique named TRCM. All the techniques covered in thissurvey are listed in the Table.1 including the tools employed as well as namesof their authors.

A Survey of Data Mining Techniques for Social Media Analysis