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User Profiling Based on Sentiment Analysis of Twitter Data

Author(s):

Dr. G Ramesh , K.L.N College of Engineering; R. Abirami, K.L.N College of Engineering; S. Padmavathy, K.L.N College of Engineering; G. Nandhini Devi, K.L.N College of Engineering

Keywords:

Sentiment Analysis, Naive Bayes, Polarity Classification

Abstract

Nowadays candidates are typically victimising the net searches, social networking websites, associate degreed social media to seek out their appropriate jobs where choosing an apt candidate with same set of skills is turning into a difficult task for the recruiters. We measure the practicability of exploitation of twitter knowledge to boost the effectiveness of a recruitment system, particularly for resume classification by using social network analysis methodology. So, the concept of SOCIAL MEDIA ANALYSIS (TWITTER DATA) is recommended to extract the personal data of a candidate to examine the differences depending on the intended use of twitter and their degrees of friendship between twitter and real world friends. Uses text classification to predict personality based on tweets tweeted by users. By analyzing users interactions, probability of polarity (tweets, reactions or emotions) is determined.

Other Details

Paper ID: IJSRDV7I11038
Published in: Volume : 7, Issue : 1
Publication Date: 01/04/2019
Page(s): 1565-1567

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