Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number

By Bruno Gonçalves, Nicola Perra, Alessandro Vespignani. PLoS ONE, 2011

550 citations recorded by the source corpus.

Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100–200 stable relationships. Thus, the ‘economy of attention’ is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/aa55459c5f4084ca5f9b90f5de7b4dee3641fdbb

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Citations in the corpus

Suicide Ideation Detection via Social and Temporal User Representations using Hyperbolic Learning (2021, result): “These observations validate our experimental design, and are in line with social network analysis on the structure of social media (Gonçalves et al., 2011), particularly Twitter (Bakshy et al., 2011).”
Information network or social network?: the structure of the twitter follow graph (2014, background): “Furthermore, it has been established through studying reciprocated direct messaging on Twitter that the number of social relationships a user can effectively maintain is limited by this constraint as well [5].”
Diffusion of Lexical Change in Social Media (2012, background): “[63] with the geographic and demographic metadata considered here; while intriguing, this is outside the scope of the present paper.”
The Simple Rules of Social Contagion (2013, background): “The role of cognitive constraints in online social interactions has not been widely examined, although one study of Twitter demonstrated that people limit themselves to approximately 150 conversation partners [12], a number similar to the bound on human social group size [10].”
Assessing the Bias in Communication Networks Sampled from Twitter (2012, background): “…influential users (Bakshy et al., 2011; Cha et al., 2010), the dynamics of information exchange (boyd et al., 2010; Cha et al., 2012; Gaffney, 2010; Gonçalves et al., 2011; Honey and Herring, 2009), the existence of polarisation (boyd et al., 2010; Conover et al., 2011), and how information…”
Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science (2015, background): “Replication studies on social platforms suggest that online interaction is still subject to this constraint [20, 36, 37].”
Evidence of Online Performance Deterioration in User Sessions on Reddit (2016, background): “Evidence also suggests that people, and other primates, have ﬁnite cognitive capacity for managing interpersonal relationships [19] limiting their amount of social interaction [20, 21].”
Social Networks and Cognition (2020, background): “Sub-sequent research has generally supported this link (Barton 1996; Dunbar 1993, 1995; Gonçalves et al. 2011; Kudo & Dunbar 2001; Stiller & Dunbar 2007) and has identified cognitive limits on social network size (Roberts et al. 2009).”
Addictive Features of Social Media/Messenger Platforms and Freemium Games against the Background of Psychological and Economic Theories (2019, background): “As prominent representatives of social media applications, Facebook, Snapchat, Instagram, and Twitter can be named and as a prominent messenger application WhatsApp or Signal.”
Coupled disease–behavior dynamics on complex networks: A review (2015, unknown): “Generally, the size of individual social network is restricted to around 150 people [158, 159] .”
Assessing the bias in samples of large online networks (2014, background): “In: Proceedings of the 19th International World Wide Web Conference (WWW 2010). ehmann, J., Goncalves, B., Ramasco, J.J., Catuto, C., 2012.”
How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations (2012, background): “mity [1], study how diurnal and seasonal mood patterns match up with the eects of sleep and circadian rhythms [2], infer socio-economic patterns from public mood levels [3], validate Dunbar’s number [4], and even explore how online chatter can lead to oine forms of political organization and mobiliz”