The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Twitter and Facebook are not representative of the general population: Political attitudes and demographics of British social media users
Open accessAbstract
A growing social science literature has used Twitter and Facebook to study political and social phenomena including for election forecasting and tracking political conversations. This research note uses a nationally representative probability sample of the British population to examine how Twitter and Facebook users differ from the general population in terms of demographics, political attitudes and political behaviour. We find that Twitter and Facebook users differ substantially from the general population on many politically relevant dimensions including vote choice, turnout, age, gender, and education. On average social media users are younger and better educated than non-users, and they are more liberal and pay more attention to politics. Despite paying more attention to politics, social media users are less likely to vote than non-users, but they are more likely to support the left leaning Labour Party when they do vote. However, we show that these apparent differences mostly arise due to the demographic composition of social media users. After controlling for age, gender, and education, no statistically significant differences arise between social media users and non-users on political attention, values or political behaviour.
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Cites
Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
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Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data
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Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data
Barberá, P. (2015) · Political Analysis · doi:10.1093/pan/mpu011 · Cited by 982 · cited 2×
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BackgroundUnderstanding the Demographics of Twitter Users
Mislove, A., Lehmann, S., Ahn, Y.-Y., Onnela, J.-P., & Rosenquist, J. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14168 · Cited by 759
Summary Report of the AAPOR Task Force on Non-probability Sampling
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Studying political microblogging: Twitter users in the 2010 Swedish election campaign
Larsson, A. O., & Moe, H. (2012) · New Media & Society · doi:10.1177/1461444811422894 · Cited by 597
Understanding the Political Representativeness of Twitter Users
Barberá, P., & Rivero, G. (2015) · Social Science Computer Review · doi:10.1177/0894439314558836 · Cited by 379
Forecasting elections with non-representative polls
Wang, W., Rothschild, D., Goel, S., & Gelman, A. (2015) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2014.06.001 · Cited by 371
140 characters to victory?: Using Twitter to predict the UK 2015 General Election
Burnap, P., Gibson, R., Sloan, L., Southern, R., & Williams, M. (2016) · Electoral Studies · doi:10.1016/j.electstud.2015.11.017 · Cited by 207
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Cited by
Fake news on Twitter during the 2016 U.S. presidential election
Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019) · Science · doi:10.1126/science.aau2706 · Cited by 1,803
Social Media and Political Agenda Setting
Gilardi, F., Gessler, T., Kubli, M., & Müller, S. (2022) · Political Communication · doi:10.1080/10584609.2021.1910390 · Cited by 401
Misinformation on Misinformation: Conceptual and Methodological Challenges
Altay, S., Berriche, M., & Acerbi, A. (2023) · Social Media + Society · doi:10.1177/20563051221150412 · Cited by 299
Ohme, J., Araujo, T., Boeschoten, L., Freelon, D., Ram, N., Reeves, B. B., & Robinson, T. N. (2024) · Communication Methods and Measures · doi:10.1080/19312458.2023.2181319 · Cited by 208
Misinformation on Misinformation: Conceptual and Methodological Challenges
Altay, S., Berriche, M., & Acerbi, A. (2021) · doi:10.31234/osf.io/edqc8 · Cited by 62
Metadata
- Authors
- Mellon, J., & Prosser, C.
- Venue
- Research & Politics
- Publisher
- SAGE Publications
- Published
- 2017-07
- Volume
- 4
- Issue
- 3
- ISSN
- 2053-1680 (ISSN-L)
- OpenAlex
- W2464870181
- Cited by
- 396
- References
- 18
- FWCI
- 56.22
- Type
- journal article
- Language
- en
- Open access
- gold
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