Presentation Title

Complex contagion features without social reinforcement in a model of social information flow

Project Collaborators

James Bagrow (Faculty Advisor), Saranzaya Magsarjav, Tobin South, Lewis Mitchell

Abstract

Contagion models are a primary lens through which we understand the spread of
information over social networks. However, simple contagion models cannot
reproduce the complex features observed in real world data, leading to research
on more complicated complex contagion models. A noted feature of complex
contagion is social reinforcement, that individuals require multiple exposures
to information before they begin to spread it themselves. Here we show that the
quoter model, a model of the social flow of written information over a network,
displays features of complex contagion, including the weakness of long ties and
that increased density inhibits rather than promotes information flow.
Interestingly, the quoter model exhibits these features despite having no
explicit social reinforcement mechanism, unlike complex contagion models. Our
results highlight the need to complement contagion models with an
information-theoretic view of information spreading to better understand how
network properties affect information flow and what are the most necessary
ingredients when modeling social behavior.

Primary Faculty Mentor Name

James Bagrow

Status

Graduate

Student College

College of Engineering and Mathematical Sciences

Program/Major

Mathematics

Primary Research Category

Engineering & Physical Sciences

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Complex contagion features without social reinforcement in a model of social information flow

Contagion models are a primary lens through which we understand the spread of
information over social networks. However, simple contagion models cannot
reproduce the complex features observed in real world data, leading to research
on more complicated complex contagion models. A noted feature of complex
contagion is social reinforcement, that individuals require multiple exposures
to information before they begin to spread it themselves. Here we show that the
quoter model, a model of the social flow of written information over a network,
displays features of complex contagion, including the weakness of long ties and
that increased density inhibits rather than promotes information flow.
Interestingly, the quoter model exhibits these features despite having no
explicit social reinforcement mechanism, unlike complex contagion models. Our
results highlight the need to complement contagion models with an
information-theoretic view of information spreading to better understand how
network properties affect information flow and what are the most necessary
ingredients when modeling social behavior.