۱- Introduction

۲- Taxonomy of source detection in network

۳- Source detection in social network

۴- Datasets and experimental setup

۵- Research challenges and future scope

۶- Conclusion

References

Abstract

The ubiquity of handheld devices provides straightforward access to the Internet and Social networking. The quick and easy updates from social networks help users in many situations like natural disasters, man-made disasters, etc. In such situations, individuals share information with the people in their network without checking the veracity of posts, which leads to the issue of rumor diffusion in a social network. Detection of rumor and source identification plays a vital role to control the diffusion of misinformation in a social network and also a good research domain in social network analysis. Source detection of such misinformation is often interesting and challenging task due to the fast diffusion of information and dynamic evolution of the social network. Accurate and quick detection of the rumor source is a very important and useful task in many application domains like source of disease in an epidemic model, start of virus spread, source of information or rumor in a social network. Most of the existing reviews which focused on source detection relate to various application domains and network perspective. But as per the need of current social networking usage and its influence on the society, it is a crucial and important topic to review the source detection approaches in the social network. The objective of this paper is to study and analyze the source detection approaches of rumor or misinformation in a social network. As an outcome of the literature study, we present the pictorial taxonomy of factors to be considered for the source detection approach and the classification of current source detection approaches in the social network. The focus has been given to various state-of-the-art source detection approaches of rumor or misinformation and comparison between approaches in social networks. This paper also focused on research challenges in current source detection approaches, public datasets and future research directions.

Introduction

Nowadays people are living in the society where everyone is connected to various networks like Social network, Internet, Biological network, Technological network, etc. [1] from which they acquire, process and share the information in a network which rabidly leads to an increasing amount of information propagation and diffusion [2]. Emergence and growth trend of social networking sites like Twitter, Facebook, and Reddit are proven as very helpful in disaster situations such as natural disasters (Flood, Storm, Earthquake), man-made disaster (Shootouts, Terrorist attacks) and emergencies [3,4]. The news and information diffusion across social sites got more research attention. This is because social media is a common means for disseminating trending discussions and breaking-news which may contain unproven information regarding events or incidents happened in the world. As per the statistical survey of social network, by the year 2021 there will be 3.02 billion monthly active users worldwide, approximately one third of the Earth’s total population [5]. To deal with the analysis of such a huge data is very vital and demanding task. The rise in interconnections of the network discloses a large range of hazards like viruses, misinformation, rumors with a frequently severe end result [6–۸]. The latest example of rumor related to “۶۰۰ Murders Take Place in Chicago during the second weekend of August 2018” presents a fear and an anxiety about such a large number of violence in the city [9]. The statistical statement was given in the Television show to just target the politicians and their promises during the election campaign. The actual truth after verification said that during the second week of August 2018 only a single murder was found and 600 was totally a misinformation because the city had not seen 600 murders in the entire 2018 up to the date. These types of rumor can spread widely in a social network and introduce many questions about the security of the people living in the city. The extensive spread of misinformation can lead to unacceptable, destructive [10] and negative impacts on individuals and society.