Current Trends in Text Mining for Social Media

Tajinder Singh, Madhu Kumari, Triveni Lal Pal, Ahsan Chauhan
<span title="2017-06-30">2017</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/k7f2snpxzrhybfen3tkjr6uoa4" style="color: black;">International Journal of Grid and Distributed Computing</a> </i> &nbsp;
Online social media has created new paradigms of information sharing which not only provides appropriate platform for the contributors but also for active information seekers. Numerous forms of social media have gained the widespread attention internet users' almost on explosion level. Availability of data on such behemoth scale mandates regular and critical analysis of this information for various perspectives' plausibility. As text mining plays a significant and crucial role in discovery of
more &raquo; ... ese insights therefore its challenges and contribution in social media analysis must be explored extensively. This paper focuses on description of assorted social media text mining methods with their viabilities and summarizes various commercial and open source tools for such data analysis Table 2. Variation in Usage According to Users 18-29 89% 30-49 82% 50-64 65% 65+ 49% Social media allows the users to deploy the services and at the same time offers the platform to contribute (Twitter, Facebook, Tumbler, Flicker, LinkedIn etc.,) [6]. The flow of information was unidirectional, in long established media i.e., B2C. But in the current scenario are absolutely changed, social media allows users to carve up the informational needs speedily. Among all the social media sites, Twitter is gaining momentum [47] as it can be accessed through mobile, website interface, SMS, etc., 80% users are accessing through mobiles and it has 320M monthly lively users [60]. It allows users to post, interpret, share and deliver 140 words' called tweets [5] .
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