ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

PUBLIC TROLLING DETECTION ON TWITTER USINGMACHINE LEARNING: A REVIEW

Abstract

ABSTRACT: Millions of users around the world are involved in social networking sites. User interactions with these social sites such as twitterhave huge and sometimes unwanted effects on the everyday life. The main social connectivity websites are a goal platform for users to dispersea large number of irrelevant and undesirable data. Twitter has become one of the most extravagant microblogging services of all times and isgenerally used to share unreasonable opinions. In this proposed work the public dishonour site in Twitter is mechanised. Nine kinds ofdishonouring tweets are classified as: harmful tweets, correlationships, condemnation, rigour, house-related, volgar, spam, non-spam orwhatever-outery, each of the tweets being arranged in either one or the other way. The fact that the lion's share of them will probably mortifythe person involved is seen in the many people who take an interest in clients who make remarks on a particular occasion. Curiously, it is alsodishonouring whose devotees check the non-dishonourment on Twitter more quickly.Keywords – Remove dishonours, online user behaviour, public dishonouring, tweet classification

Full Text PDF

IMPORTANT DATES 

Submit paper at ijasret@gmail.com

Paper Submission Open For December 2021
UGC indexed in (Old UGC) 2017
Last date for paper submission 30th January, 2021
Deadline Submit Paper any time
Publication of Paper Within 01-02 Days after completing all the formalities
Paper Submission Open For Publication /online Conference 
Publication Fees Rs.1000  ***                                  Free for PR Students