A Survey on Fake News Detection using Support Vector Model

Abstract

In the boosting period of Social Media availability and easy availability of Internet to end users in various regions, many challenges are also occurred with usage of this technology. Fake news spreading in various field is also a major challenge in recent time. Fake news has been spreading into vast in significant numbers for various business reasons and also for political reasons. Problem of fake news has become frequent in the online world. People can get affected and their view are also affected easily by these type of fake news for its fabricated words. This type of news has enormous effects on the offline community in various sectors. In this way it is an interesting topic for research. Significant research has been conducted on the detection of fake news from English texts and other languages but there is chancel to improve the work with other languages as well as from multiple sources. Various algorithms like SVM and other supervised algorithm can be helpful to classify fake news. As Sentiment Score is an also a major point for detection of Fake news; in our work we are applying SVM algorithm with TF/IDF, multiple Languages (Language Conversation) etc.”