Social Network Shaming Text identification, inspection, reduction

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Social Network Shaming Text identification, inspection, reduction
Author(s):
Karan Tailor, Pradnya Navale, Het Bhatt, Rutuja Nehul
Keywords:
Shaming, Social Network, OSN network, Performance metrics
Abstract
Twitter is a web social networking service that has quite 300 million users, generating an enormous amount of data daily. Twitter’s most significant feature is its ability for users to tweet about events, situations, feelings, opinions, or maybe something new in real-time. there's no system of accuracy or reliability in place: Anyone can say just anything. It is a simple thanks to attacking your detractors for them to attack, the type of Twitter war. during this survey, various applications of machine learning and hate speech detection to ease the detection of shammers and shamming tweets were included. With the rise of online social networks, and the growth of publicly shaming events, voices against the callousness of the positioning owners are growing stronger, there's a necessity to investigate the shaming tweets, classify shamming tweets into different categories, and mitigate them by blocking them.
Article Details
Unique Paper ID: 152097 Publication Volume & Issue: Volume 8, Issue 2 Page(s): 459 - 465
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