A model for the influence of media on the ideology of content in online social networks
Heather Z. Brooks, Mason A. Porter
Abstract
The authors study the relationship between the spread of content and the bias and quality of such content using a bounded-confidence opinion model that incorporates media and nonmedia accounts with dynamic content updating. Using this model, they show how to maximize media impact in a network by tuning the number of media accounts and the number of followers per account, and they examine how this impact depends on network features.
Topics & Concepts
Content (measure theory)Social mediaIdeologyUser-generated contentQuality (philosophy)Media contentContent analysisComputer scienceSocial network (sociolinguistics)Content distributionInternet privacyPublic relationsContext (archaeology)AdvertisingSociologyDigital mediaSocial psychologyNetwork mediaMeasure (data warehouse)Social network analysisKey (lock)PsychologyThe InternetOpinion leadershipComponent (thermodynamics)Relation (database)Opinion Dynamics and Social InfluenceComplex Network Analysis TechniquesSocial Media and Politics