The information era witnesses the creation of multimedia data, transfers and transactions in the order of millions. This data by virtue of their formats comes in varying sizes and differing temporal characteristics. The wealth of information carries potential both in terms of explicit content that is expressed and the implicit or hidden content. Processing the former is quite developed while the procedures and applications of working with the implicit knowledge are growing steadily. This paper aims to present a range of techniques from recent works pertaining to the processing and applicability of such data. The purpose of the survey is to bring to light the specific methods of social media data analysis in a concise and organized manner. Specifically, natural language processing, topic modelling, sentiment analysis and affective analysis have been identified as the overarching heads taken up by several recent researches. Finally, some observations pertaining to social media data analysis identified from several works are enlisted.

Data Mining, Machine Learning, Natural Language Processing, Social Media

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