Paper Details

Nowadays peoples are going towards social media increasingly to fetch the information and to share theiropinion on social media. As there is rapid diffusion of information on social media, the information posted on socialmedia spread so fast and easy. This information posted on social media not always right or not truthful to make sense. Anadvantage of social media is that all the people can share information and also gives their opinions on that platform. Thedrawback of such rapid diffusion of information is that false information are also spread. As the rumors are spreading onTwitter and other social media so fast and easier. We need to provide some solutions to detect such rumors. In this paper,our detection approach is based on the classification. Our detection approach is divided into three parts: Preprocessing,Sentiment Analysis and Classification. Also we are comparing different supervised learning techniques/methods forgetting better and accurate detection of rumors. We are using one more external module i.e. news websites verificationand comparing sentiment score of our proposed method and sentiment score of this external module.

Dr. Dinesh B. Vaghela, Divya M. Patel, “Rumor Detection with Twitter and News Channel Data Using Sentiment Analysis and Classification”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 2, pp. 924-930, February 2018.