Detection of FAKE NEWS on SOCIAL MEDIA using CLASSIFICATION Data Mining Techniques
Deepak Sharma1, Shilpa Singhal2
1Deepak Sharma*, Research Scholar, MD University, Rohtak, India.
2Shilpa Singhal, PG Student, C-DAC, GGSIP University, New Delhi, India.
Manuscript received on September 17, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 3132-3138 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1637109119/2019©BEIESP | DOI: 10.35940/ijeat.A1637.109119
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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: 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.
Keywords: Decision tree, Support Vector Machine (SVM), Data Mining, WEKA.