A review on social audience identification on twitter using text mining methods

Abstract

Data mining is a technique of extracting hidden predictive information from large databases. The important information discovery from the data is more needed in many areas like industries, education, web mining, text mining, etc. Among this text mining is very important in social media. Text mining also referred as the process of deriving information from text. A social media platform such as Twitter is main stream which provides valuable user-generated information by publishing and sharing contents. Identifying interesting contents from large text-streams is a crucial issue in social media because many users struggle with information overload. Analyzing social audience who are interested in a company of social media is very difficult and so many text mining methods e.g. fuzzy keyword match method, Twitter LDA method and Machine learning approaches are used for solving this problem. Using the tweets of the account owner to segment followers and describing a group of high-value social audience members will assist the account owner to spend resources more effectively by sending offers to the appropriate audience which will lead to maximal marketing performance and more the return on contribution.

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