5 results match your criteria: "Berkman Center for Internet and Society[Affiliation]"

Scientists and health communication professionals expressed frustration over the relationship between misinformation circulating on the Internet and global public perceptions of and responses to the Ebola epidemic originating in West Africa. Using the big data platform Media Cloud, we analyzed all English-language stories about keyword "Ebola" published from 1 July 2014 to 17 November 2014 from the media sets U.S.

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Social selection and peer influence in an online social network.

Proc Natl Acad Sci U S A

January 2012

Department of Sociology and Berkman Center for Internet and Society, Harvard University, Cambridge, MA 02138, USA.

Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music.

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Emotions as infectious diseases in a large social network: the SISa model.

Proc Biol Sci

December 2010

Program for Evolutionary Dynamics, Berkman Center for Internet and Society, Department of Mathematics, Harvard University, Cambridge, MA 02138, USA.

Human populations are arranged in social networks that determine interactions and influence the spread of diseases, behaviours and ideas. We evaluate the spread of long-term emotional states across a social network. We introduce a novel form of the classical susceptible-infected-susceptible disease model which includes the possibility for 'spontaneous' (or 'automatic') infection, in addition to disease transmission (the SISa model).

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