Information spread in social networks

1. Information spread in social networks Marin Stamov CS 765 Oct 26 2011

2. Outline • Social network • Importance of the information spread in social networks • Information types • Advertising in social networks • Information spread models • Sequential social learning • Rational word-of-mouth learning • Information aggregation model • Binary agreement model • Diffusion model of actionable information • My contribution

3. Social network • A social structure made up of individuals connected by one or more specific types of interdependency • Nodes -> individuals • Edges -> friendship

4. • Email networks • Cell phone call networks • Real-world interactions • Online networks

5. • Age distribution of Facebook profiles

6. Importance of the information spread in social networks • Knowledge is power • Misinformation and rumors can be mistaken for useful information • Individual’s beliefs can be changed based on interactions with their friends

7. Types of information • News • Facts • Opinions • Rumors • Behavior • Fashion • Obesity

8. Advertising in social networks • Products recommended by trustful sources are more likely to be considered • Recommendations based on interests and preferences • Individuals satisfied with a product, will advertise it to their friends even without gating paid to do so

9. Agent based models • Aclass of computational models for simulating the interactions of autonomous agents • Each agent makes individual decisions based on the information that he has and a set of rules • Agents may execute various behaviors appropriate for the system they represent

10. Sequential social learning model • Agent’s actions and behavior can be influenced by other agents in observable world • Agents decide what action to make when their turn comes • Does a popularity of a choice indicate that this is a good choice? • The agent involved in herd behavior act in specific way, not motivated by personal reasons

11. Model of rational word-of-mouth learning • Generations of agents make choices between two alternatives. • Each agent asks agents that have already made a choice, what did they chose and how satisfied they are • If each agent samples two or more others, in the long run every agent will choose the same thing

12. Information aggregation model • Each scalar in the model represents a belief that a certain individual holds • Agents meet pair-wise • Two types of agents: regular and forceful • Regular – regular --> updated beliefs are set to the average of their pre-meeting beliefs • Forceful – regular --> updated beliefs are set to the beliefs of the forceful agent

13. social influence: Binary agreement model • Opinions can be: • A • B • Undecided AB • At each step: • A random speaker is chosen • A random neighbor of the speaker is chosen • Different from epidemic like models • A “converted” individual can revert back • symmetric in both opinions

14. social influence: Binary agreement model • If spoken opinion not on listener’s list he adds it • If it ison the list both keep only spoken opinion • consensus state can be reached B A A A Listener Speaker

15. social influence: Binary agreement model • A committed set of minority opinion holders on a network, can reverse the majority • Applications: • Influencing public opinion • Reducing hostile opinion

16. Diffusion model of actionable information • The information trust value is related to the social relationship between the sender and the receiver 1 Believer Undecided Disbelieved 0 Uninformed

17. The nodes process and act on the information • Diffusion model with abort information • Abort message can be broadcasted after the action message • Nodes combine action and abort information • Disbelieved nodes spread abort information

18. My contribution • Analyze what factors affect the information spread in social networks • Betweenness, Closeness, and Degree • Node influence • Edges weights (trust) • Information importance and it’s representation • Try to identify misinformation and limit its spread • Create new information spread model or improve an existing one

19. References [1] DaronAcemoglu,AsumanOzdaglar, Spread of (Mis)Information in Social Networks Games and Economic Behavior 7 (2010) [2] D. Acemoglu, MuntherDahleh, IlanLobel, Bayesian learning in social networks, Preprint, (2008) [3] A. Banerjee and D. Fudenberg, Word-of-mouth learning, Games and Economic Behavior 46 (2004) [4] V. Bala and S. Goyal, Learning from neighbours, Review of Economic Studies 65(1998) [5] A. Banerjee, A simple model of herd behavior, Quarterly Journal of Economics 107(1992) [6] S. Sreenivasan, J. Xie, W. Zhang, Influencing with committed minorities, NetSci (2011) [7] Cindy Hui, Modeling the Spread of Actionable Information in Social Networks, (2011) [8] LadaAdamic, Co-evolution of network structure and content, NetSci (2011)

20. Thank you! Questions ?