Topical clustering is used to analyze tweet data

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Ravi kumar kuchipudi, Dr V.V. Jaya Rama Krishnaiah,

Abstract

Practical management guidance and the spread of "social networking" have made "networking" more important than ever. As a result of social media, massive amounts of data are generated. It is estimated that over 400 million people use Facebook each month, exchanging over 5 billion pieces of information. Online social networks like Twitter, Facebook, LinkedIn, and Instagram connect people from all over the world. An increasing number of applications use social network analysis, which allows us to gather important information about the people in the network, share information, or make connections. Our approach to analyzing Twitter and Facebook profiles by geography is presented in this paper. The user should be able to choose the locations of these other individuals. According to the analysis, we'll compare Facebook and Twitter profiles based on where they're located, and then we'll extract tweets and comments made by people in that area. As a result, the project's focus is on big data analytics..

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