Competing for Attention in Social Media under Information Overload Conditions

Abstract

Although the many forms of modern social media have become major channels for the dissemination of information, they are becoming overloaded because of the rapidly-expanding number of information feeds. We analyze the expanding user-generated content in Sina Weibo, the largest micro-blog site in China, and find evidence that popular messages often follow a mechanism that differs from that found in the spread of disease, in contrast to common believe. In this mechanism, an individual with more friends needs more repeated exposures to spread further the information. Moreover, our data suggest that in contrast to epidemics, for certain messages the chance of an individual to share the message is proportional to the fraction of its neighbours who shared it with him/her. Thus the greater the number of friends an individual has the greater the number of repeated contacts needed to spread the message, which is a result of competition for attention. We model this process using a fractional susceptible infected recovered (FSIR) model, where the infection probability of a node is proportional to its fraction of infected neighbors. Our findings have dramatic implications for information contagion. For example, using the FSIR model we find that real-world social networks have a finite epidemic threshold. This is in contrast to the zero threshold that conventional wisdom derives from disease epidemic models. This means that when individuals are overloaded with excess information feeds, the information either reaches out the population if it is above the critical epidemic threshold, or it would never be well received, leading to only a handful of information contents that can be widely spread throughout the population.

arXiv comment11 pages, 5 figures

References in corpus (17)

• Epidemic spreading in scale-free networks
• The spread of epidemic disease on networks
• Network robustness and fragility: Percolation on random graphs
• Theory of Rumour Spreading in Complex Social Networks
• Epidemic outbreaks in complex heterogeneous networks
• Minority Opinion Spreading in Random Geometry
• Dynamics of Majority Rule
• Second look at the spread of epidemics on networks
• The Simple Rules of Social Contagion
• How Visibility and Divided Attention Constrain Social Contagion
• Triple Point in Correlated Interdependent Networks
• Dynamics of Non-Conservative Voters
• Emergence of influential spreaders in modified rumor models
• Optimal Path and Minimal Spanning Trees in Random Weighted Networks
• Entropy-based Classification of 'Retweeting' Activity on Twitter
• Strategy of Competition between Two Groups based on a Contrarian Opinion Model
• Social distancing strategies against disease spreading

Cited by in corpus (12)

• Suppressing disease spreading by using information diffusion on multiplex networks
• Information Overload in Group Communication: From Conversation to Cacophony in the Twitch Chat
• Modeling of Information Diffusion on Social Networks with Applications to WeChat
• Co-evolutionary dynamics in social networks: A case study of Twitter
• Understanding WeChat User Preferences and "Wow" Diffusion
• Information Cascades in Feed-based Networks of Users with Limited Attention
• Identifying long-term periodic cycles and memories of collective emotion in online social media
• Atypical viral dynamics from transport through popular places
• Reversible bootstrap percolation: Fake news and fact checking
• Comparing the diversity of information by word-of-mouth vs. web spread
• Anomalous Contagion and Renormalization in Dynamical Networks with Nodal Mobility
• Nonlinear dynamics of information overload: Impact on source localization in complex networks