A Machine Learning-based Online Social Network Analysis for 360-Degree User Profiling
R. Kanniga Devi 

R. Kanniga Devi, Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Krishnankoil (Tamil Nadu), India.

Manuscript received on 11 December 2019 | Revised Manuscript received on 22 December 2019 | Manuscript Published on 30 December 2019 | PP: 992-998 | Volume-9 Issue-2S2 December 2019 | Retrieval Number: B11031292S219/2019©BEIESP | DOI: 10.35940/ijitee.B1103.1292S219

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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: This paper aims to analyse the online social network for reconnaissance of people for finding their potentiality. The work considers one of the famous social networking sites, Twitter, where people express their thoughts and ideas, through which the people in the site knowingly or unknowingly reveal the information about themselves such as personal interests, likes and dislikes. The Machine Learning technique facilitates the work to mine the tweet data of a person to get his/her 360-degree profiling. This profiling is helpful to identify the personality type of a person, which is essential for the Government to identify the people involved in spreading the fake news in Twitter.

Keywords: Machine Learning, Natural Language Processing, Online Social Network, Personality Test, Profiling, Sentimental Analysis, Twitter.
Scope of the Article: Machine Learning