An efficient method for restraining negative information cascades in online social networks

Information cascades is recognized as a major factor in disastrous social network phenomenons. The clustering of network community can block the cascade of negative information and users' behaviors in online social networks (OSNs). Confronting limited network resources, this paper takes the interaction relationship between network structure optimizing and neighbors' behaviors cascading as the breakthrough point, and study the restrain method of negative information cascades under emergency. This paper proposes a method for restraining the cascade of negative information, which is in order to improve the clustering of network communities by means of links that are logically removed (termed CLLR). By limited links with high betweenness being logically removed, CLLR method enhances the community density in a network, thereby effectively block information cascades. Experimental results show that CLLR method significantly improve the clustering of a network, efficiently block the speed and scope of information cascades in OSNs.

I. Introduction

Online social networks (OSNs) such as Twitter and Facebook have become an important part of people's daily lives. OSNs not only help people stay in touch with family and friends, but also keep abreast of breaking news and emerging contents. False or unverified information spreads just like accurate information on the web, thus possibly going viral and influencing the public opinion and its decisions [1]–[4]. Especially, information cascades are identified as a major factor in almost every disastrous social network phenomenon, ranging from viral marketing, rumor diffusion, cyber violence, and various negative information spread. During the COVID-19 outbreak in early 2020, various kinds of bad information on the Internet, such as “a certain place closed the city”, “a certain place has a large-scale infection”, etc., greatly misled the public and disrupted public order [5]. Therefore, effective methods for restraining negative information cascades are crucial for OSNs and it has been a hot topic in the last decades.