Big Data Veracity: Methods and challenges

Abstract

Today, the Internet has become the main source of information, a place where there are no restrictions on who can share information .This latter can play an important role in prediction, estimation and decision making processes. But, this role will not only be achieved through abundance, it will also be the result of data quality. Veracity refers to the assurance of quality or credibility of the data collected. The data can be incomplete, biased, vague or wrong. For this reason, automatic filtering mechanism has been developed. Moreover, due to the increasing velocity of information spread, manual assessment of information veracity became hard, a time consuming process and even the already existing automatic filtering mechanisms has to be improved to cope with the speed of information spread. In this paper, a literature review is established to highlight the recent methods and techniques which are exploited in computerized veracity assessment. The challenges and limitations of existing works will be discussed, and future research directions will be proposed to address critical issues of data veracity in the era of big data.