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AUTHOR(S): Rukmani P, S. Graceline Jasmine, Vergin Raja Sarobin, Sathiya Narayanan, Modigari Narendra, Dhanya D., Benson Edwin Raj,
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TITLE Dynamic Analysis of Twitter and Facebook Through Social Network Analysis |
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ABSTRACT In recent years, the use of social media has seen a significant surge. Having begun on a very small scale as a socialization forum, it has now helped itself in every possible sphere. Advertising goods, exchanging news, driving companies and much more are among them. More people are drawn to social networking sites such as Facebook, Google+, Twitter, so we propose an approach for estimating the lifetime and retweet times of tweets. Similarly the popularity of the tweets are also computed using the social network analysis. In order to create prediction knowledge bases, the data are extracted from retweet graphs, such as posting times, content information's, and area of interest etc. Tweets are sequentially extracted from the knowledge base with a similar topic, retweet pattern and properties and then used to make a prediction. The user-user relationship is followed and user-user relationships are modeled to better analyze the data. Different indices of centrality are determined to assess the prominent people who led the election campaign. In order to better understand whether social media has any major impact on tweet data, the outcomes are then compared with ground-truth evidence. |
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KEYWORDS Twitter Tweets, Centrality measures, Retweet pattern, Similarity Index |
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Cite this paper Rukmani P, S. Graceline Jasmine, Vergin Raja Sarobin, Sathiya Narayanan, Modigari Narendra, Dhanya D., Benson Edwin Raj,. (2021) Dynamic Analysis of Twitter and Facebook Through Social Network Analysis. International Journal of Education and Learning Systems, 6, 1-7 |
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