A Survey of Fake Data or Misinformation Detection Techniques Using Big Data and Sentiment Analysis

Nowadays, online networking is used generally as the spring of data on account of its ease and simplicity nature. This has turned out to be an open stage for discussion, knowledge dissemination, ideology expression, emotions, as well as sentiment sharing. Since FN affects people and society considerably, it is a major issue; actually, it is a double-edged sword. In internet-based life, the data spread quickly, thus, that news should be predicted quickly by the discovery constituent to halt the FN dispersal. Consequently, it is critical to identify FN via web-centered networking. Incidentally, this paper renders an inclusive systematic literature review and endeavors to discuss technical aspects of fake data detection utilizing Big Data (BD) and Sentiment Analysis (SA). Additionally, this paper also emphasized the technical aspects of identifying fake data in the means of challenges prevalent in the development of its method and also the non-technical challenges mostly centered on its application. Future research can be directed toward solving these challenges.