Signed Networks in Social Media

Abstract

Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships affects the structure of on-line social networks. We connect our analyses to theories of signed networks from social psychology. We find that the classical theory of structural balance tends to capture certain common patterns of interaction, but that it is also at odds with some of the fundamental phenomena we observe --- particularly related to the evolving, directed nature of these on-line networks. We then develop an alternate theory of status that better explains the observed edge signs and provides insights into the underlying social mechanisms. Our work provides one of the first large-scale evaluations of theories of signed networks using on-line datasets, as well as providing a perspective for reasoning about social media sites.

References in corpus (1)

• Structure and tie strengths in mobile communication networks

Cited by in corpus (14)

• Predicting Positive and Negative Links in Online Social Networks
• Governance in Social Media: A case study of the Wikipedia promotion process
• Fast Exact Shortest-Path Distance Queries on Large Networks by Pruned Landmark Labeling
• Viral Misinformation: The Role of Homophily and Polarization
• Social determinants of content selection in the age of (mis)information
• Core-Periphery in Networks: An Axiomatic Approach
• Roles of Ties in Spreading
• Signed graph embedding: when everybody can sit closer to friends than enemies
• Matrix Factorization with Explicit Trust and Distrust Relationships
• Exploring Hierarchies in Online Social Networks
• Negative Link Prediction in Social Media
• Scale-Adaptive Group Optimization for Social Activity Planning
• A Linear Time Active Learning Algorithm for Link Classification -- Full Version --
• Nonadaptive Mastermind Algorithms for String and Vector Databases, with Case Studies