Evidence of complex contagion of information in social media: An experiment using Twitter bots

PLoS ONE

Volumn 12, Issue 9, 2017, Pages

  Mønsted, Bjarke ^a   Sapieżyński, Piotr ^a   Ferrara, Emilio ^b,c   Lehmann, Sune ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^c INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADVERTISING; BEHAVIOR; CONTROLLED STUDY; DIFFUSION; HUMAN; MARKETING; PROPAGANDA; SOCIAL MEDIA; ALGORITHM; BAYES THEOREM; INFORMATION SCIENCE; INTERPERSONAL COMMUNICATION; SOFTWARE; THEORETICAL MODEL;

ALGORITHMS; BAYES THEOREM; COMMUNICATION; HUMANS; INFORMATION THEORY; MODELS, THEORETICAL; SOCIAL MEDIA; SOFTWARE;

EID: 85029816920     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0184148     Document Type: Article

References (33)

1. Castellano C, Fortunato S, Loreto V. Statistical physics of social dynamics. Reviews of modern physics. 2009; 81(2):591. https://doi.org/10.1103/RevModPhys.81.591
2. Goffman W, Newill V. Generalization of epidemic theory. Nature. 1964; 204(4955):225–228. https://doi.org/10.1038/204225a0 PMID: 14212412
3. Granovetter M. Threshold models of collective behavior. American journal of sociology. 1978; p. 1420–1443. https://doi.org/10.1086/226707
4. Daley DJ, Kendall DG. Epidemics and rumours. Nature. 1964; 204(4963):1118–1118. https://doi.org/10.1038/2041118a0 PMID: 14243408
5. Daley D, Kendall DG. Stochastic rumours. IMA Journal of Applied Mathematics. 1965; 1(1):42–55. https://doi.org/10.1093/imamat/1.1.42
6. Centola D, Macy M. Complex contagions and the weakness of long ties. American journal of Sociology. 2007; 113(3):702–734. https://doi.org/10.1086/521848
7. Centola D. The spread of behavior in an online social network experiment. Science. 2010; 329 (5996):1194–1197. https://doi.org/10.1126/science.1185231 PMID: 20813952
8. Onnela JP, Reed-Tsochas F. Spontaneous emergence of social influence in online systems. Proceedings of the National Academy of Sciences. 2010; 107(43):18375–18380. https://doi.org/10.1073/pnas. 0914572107
9. Romero DM, Meeder B, Kleinberg J. Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter. In: Proceedings of the 20th international conference on World wide web. ACM; 2011. p. 695–704.
10. Bond RM, Fariss CJ, Jones JJ, Kramer AD, Marlow C, Settle JE, et al. A 61-million-person experiment in social influence and political mobilization. Nature. 2012; 489(7415):295–298. https://doi.org/10.1038/ nature11421 PMID: 22972300
11. Ugander J, Backstrom L, Marlow C, Kleinberg J. Structural diversity in social contagion. Proceedings of the National Academy of Sciences. 2012; 109(16):5962–5966. https://doi.org/10.1073/pnas. 1116502109
12. Weng L, Menczer F, Ahn YY. Virality prediction and community structure in social networks. Scientific reports. 2013; 3. https://doi.org/10.1038/srep02522
13. Muchnik L, Aral S, Taylor SJ. Social influence bias: A randomized experiment. Science. 2013; 341 (6146):647–651. https://doi.org/10.1126/science.1240466 PMID: 23929980
14. Karsai M, Iñiguez G, Kaski K, Kertész J. Complex contagion process in spreading of online innovation. Journal of The Royal Society Interface. 2014; 11(101):20140694. https://doi.org/10.1098/rsif.2014. 0694
15. Kramer AD, Guillory JE, Hancock JT. Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences. 2014; 111(24):8788–8790. https://doi.org/10.1073/pnas.1320040111
16. Hodas NO, Lerman K. The Simple Rules of Social Contagion. Scientific Reports. 2014; 4:4343. https://doi.org/10.1038/srep04343 PMID: 24614301
17. Ferrara E, Yang Z. Measuring emotional contagion in social media. PloS one. 2015; 10(11):e0142390. https://doi.org/10.1371/journal.pone.0142390 PMID: 26544688
18. Goel S, Anderson A, Hofman J, Watts DJ. The structural virality of online diffusion. Management Science. 2015; 62(1):180–196.
19. Lerman K. Information Is Not a Virus, and Other Consequences of Human Cognitive Limits. Future Internet. 2016; 8(2):21. https://doi.org/10.3390/fi8020021
20. Campbell E, Salathé M. Complex social contagion makes networks more vulnerable to disease outbreaks. Scientific reports. 2013; 3. https://doi.org/10.1038/srep01905 PMID: 23712758
21. Subrahmanian V, Azaria A, Durst S, Kagan V, Galstyan A, Lerman K, et al. The DARPA Twitter Bot Challenge. Computer. 2016; 49(6):38–46. https://doi.org/10.1109/MC.2016.183
22. Ferrara E, Varol O, Davis C, Menczer F, Flammini A. The rise of social bots. Communications of the ACM. 2016; 59(7):96–104. https://doi.org/10.1145/2818717
23. Lehman S, Sapiezynski P. #BanksyInBoston or #BotsInCopenhagen?; 2014. Available from: http://www.aaai.org/Symposia/Spring/sss14symposia.php#ss08
24. McPherson M, Smith-Lovin L, Cook JM. Birds of a feather: Homophily in social networks. Annual review of sociology. 2001; p. 415–444.
25. Aral S, Muchnik L, Sundararajan A. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proceedings of the National Academy of Sciences. 2009; 106 (51):21544–21549. https://doi.org/10.1073/pnas.0908800106
26. Shalizi CR, Thomas AC. Homophily and contagion are generically confounded in observational social network studies. Sociological methods & research. 2011; 40(2):211–239. https://doi.org/10.1177/ 0049124111404820
27. Wang YH. On the number of successes in independent trials. Statistica Sinica. 1993; p. 295–312.
28. Basheer I, Hajmeer M. Artificial neural networks: fundamentals, computing, design, and application. Journal of microbiological methods. 2000; 43(1):3–31. https://doi.org/10.1016/S0167-7012(00)00201-3 PMID: 11084225
29. Shi Y, Eberhart R, Chen Y. Implementation of evolutionary fuzzy systems. IEEE Transactions on Fuzzy Systems. 1999; 7(2):109–119. https://doi.org/10.1109/91.755393
30. Schwarz G. Estimating the dimension of a model. The annals of statistics. 1978;.
31. Raftery A. Bayesian model selection in social research. Sociological methodology. 1995;.
32. Golder SA, Macy MW. Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science. 2011; 333(6051):1878–1881. https://doi.org/10.1126/science.1202775 PMID: 21960633
33. Davis CA, Varol O, Ferrara E, Flammini A, Menczer F. Botornot: A system to evaluate social bots. In: Proceedings of the 25th International Conference Companion on World Wide Web. International World Wide Web Conferences Steering Committee; 2016. p. 273–274.