Evidence of Complex Contagion of Information in Social Media: An Experiment Using Twitter Bots

PloS one 12.9 (2017): e0184148

12 Pages Posted: 4 Feb 2019

See all articles by Bjarke Mønsted

Bjarke Mønsted

Technical University of Denmark

Piotr Sapieżyński

Technical University of Denmark

Emilio Ferrara

University of Southern California - Information Sciences Institute

Sune Lehmann

Technical University of Denmark

Date Written: September 22, 2017

Abstract

It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using ‘social bots’ deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques.

Suggested Citation

Mønsted, Bjarke and Sapieżyński, Piotr and Ferrara, Emilio and Lehmann, Sune, Evidence of Complex Contagion of Information in Social Media: An Experiment Using Twitter Bots (September 22, 2017). PloS one 12.9 (2017): e0184148. Available at SSRN: https://ssrn.com/abstract=3008748

Bjarke Mønsted

Technical University of Denmark ( email )

Anker Engelunds Vej 1
Building 101A
Lyngby, 2800
Denmark

Piotr Sapieżyński

Technical University of Denmark ( email )

Anker Engelunds Vej 1
Building 101A
Lyngby, 2800
Denmark

Emilio Ferrara (Contact Author)

University of Southern California - Information Sciences Institute ( email )

United States

HOME PAGE: http://emilio.ferrara.name

Sune Lehmann

Technical University of Denmark ( email )

Anker Engelunds Vej 1
Building 101A
Lyngby, 2800
Denmark

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