Open AccessDetection of FAKE NEWS on SOCIAL MEDIA using CLASSIFICATION Data Mining Techniques
Author(s) -
Deepak Sharma,
Shilpa Singhal
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1637.109119
Subject(s) - misinformation , rumor , social media , computer science , correctness , microblogging , reliability (semiconductor) , support vector machine , originality , artificial intelligence , data science , decision tree , sentiment analysis , machine learning , internet privacy , world wide web , computer security , psychology , social psychology , power (physics) , physics , public relations , quantum mechanics , political science , creativity , programming language
In today’s world social media is one of the most important tool for communication that helps people to interact with each other and share their thoughts, knowledge or any other information. Some of the most popular social media websites are Facebook, Twitter, Whatsapp and Wechat etc. Since, it has a large impact on people’s daily life it can be used a source for any fake or misinformation. So it is important that any information presented on social media should be evaluated for its genuineness and originality in terms of the probability of correctness and reliability to trust the information exchange. In this work we have identified the features that can be helpful in predicting whether a given Tweet is Rumor or Information. Two machine learning algorithm are executed using WEKA tool for the classification that is Decision Tree and Support Vector Machine.