Enhanced Social Media Metrics Analyzer Using Twitter Corpus as an Example
K. Jayamalini1, M. Ponnavaikko2
1K. Jayamalini, Research Scholar, Computer Science Engineering, Bharath University, Chennai, India.
2Dr. M. Ponnavaikko, Provost, Vinayaka Mission‘s Research Foundation, AV Campus, Chennai, India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 12 May 2019 | Manuscript published on 30 May 2019 | PP: 822-828 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5773058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: social media is the collection of online communications channels dedicated to community-based input, interaction, content-sharing and collaboration. Websites and mobile applications dedicated to forums, microblogging, social networking, social bookmarking, social curation, and wikis are most popular and different types of social media. Social media become an essential part of human life. In business, social media is used to market products, promote brands, and connect to current customers and foster new business.Online social media is ubiquitous in nature. It allows people to use short text messages to express their opinions and sentiments about products, events and other people. For example, Twitter is an online news and social networking service where users post and interact with short messages, called “tweets”. Therefore, nowadays social media become a potential source for business to find people’s sentiments and opinions about a particular event or product. Social media analytics is the practice of gathering huge amount of digital data generated online from blogs and social media websites and analyzing them to find the insights and make business decisions. This paper focuses on development of enhanced social media metrics analyser using various latest methods and algorithms with the help of R language and R tool.
Keyword: Social Media data, Opinion Mining (OM), Sentiment Analysis (SA), Metrics Analyser, Twitter.
Scope of the Article: Data Mining