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Cited by 56Social Media and PoliticsComplex Network Analysis TechniquesOpinion Dynamics and Social Influence

An exploration of social identity: The geography and politics of news‐sharing communities in twitter

Open access
HerdaĞdelen, AmaÇ, Zuo, Wenyun, Gard‐Murray, Alexander, Bar‐Yam, Yaneer·2013·Complexity
DOI 10.1002/cplx.21457
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Abstract

The importance of collective social action in current events is manifest in the Arab Spring and Occupy movements. Electronic social media have become a pervasive channel for social interactions, and a basis of collective social response to information. The study of social media can reveal how individual actions combine to become the collective dynamics of society. Characterizing the groups that form spontaneously may reveal both how individuals self‐identify and how they will act together. Here we map the social, political, and geographical properties of news‐sharing communities on Twitter, a popular microblogging platform. We track user‐generated messages that contain links to New York Times online articles and we label users according to the topic of the links they share, their geographic location, and their self‐descriptive keywords. When users are clustered based on who follows whom in Twitter, we find social groups separate by whether they are interested in local (NY), national (US) or global (cosmopolitan) issues. The national group subdivides into liberal, conservative and other, the latter being a diverse but mostly business oriented group with sports, arts, and other splinters. The national political groups are based across the US but are distinct from the national group that is broadly interested in a variety of topics. A person who is cosmopolitan associates with others who are cosmopolitan, and a US liberal/conservative associates with others who are US liberal/conservative, creating separated social groups with those identities. The existence of “citizens” of local, national, and cosmopolitan communities is a basis for dialog and action at each of these levels of societal organization. © 2013 Wiley Periodicals, Inc. Complexity 19: 10–20, 2013

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  • Otros estudios han usado el contenido de la biografía como insumo para tipificar usuarios o detectar clústeres en torno a un enlace de noticia.

    “Otros estudios han realizado el procedimiento inverso, usando el contenido de la biografía como insumo para tipificar usuarios (Uddin et al., 2014) o detectar clústeres en torno a un enlace de una noticia del New York Times a partir de palabras reincidentes en las biografías (HerdaĞdelen et al., 2013).”

    From “Vital testimonio confirm󔦔: Polarización de fuentes y redes en el Caso Catrillanca en Twitter (2021) · cites this paper as HerdaĞdelen et al., 2013

    The Abstract (p. 5) says the clusters were generated from users’ follow relationships, with no identity or interest information used to create the network layout. Appendix D (pp. 14–15) says recurring biography words were analyzed afterward to characterize the clusters, not to detect them. The study also collected links to New York Times articles, rather than clustering users around one news link. (LLM, conf=0.88)

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Authors
HerdaĞdelen, A., Zuo, W., Gard‐Murray, A., & Bar‐Yam, Y.
Affiliations
New England Complex Systems Institute (US)
Corresponding author
Bar‐Yam, Yaneer
ORCID
Venue
Complexity
Publisher
Wiley
Published
2013-10-07
Volume
19
Issue
2
Pages
10-20
ISSN
  • 1076-2787 (ISSN-L)
  • 1099-0526
DOI
10.1002/cplx.21457
OpenAlex
W1979312256
Cited by
56
References
1
Citations by year
2026: 1 · 2025: 2 · 2024: 1 · 2023: 2 · 2021: 3 · 2020: 13 · 2019: 8 · 2018: 6 · 2017: 6 · 2016: 1 · 2015: 5 · 2014: 6 · 2013: 1 · 2012: 1
FWCI
12.85
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Complexity (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
Office of Naval Research
Topics
  • Social Sciences › Communication › Social Media and Politics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
Keywords
social identity, Twitter, microblogging, social media, political polarization, cosmopolitanism, local news, national news, New York Times, user-generated content, social networks, collective action, Arab Spring, Occupy movement

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