John Bryden

1.5k total citations · 2 hit papers
25 papers, 753 citations indexed

About

John Bryden is a scholar working on Sociology and Political Science, Statistical and Nonlinear Physics and Communication. According to data from OpenAlex, John Bryden has authored 25 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Sociology and Political Science, 7 papers in Statistical and Nonlinear Physics and 6 papers in Communication. Recurrent topics in John Bryden's work include Misinformation and Its Impacts (11 papers), Opinion Dynamics and Social Influence (7 papers) and Social Media and Politics (6 papers). John Bryden is often cited by papers focused on Misinformation and Its Impacts (11 papers), Opinion Dynamics and Social Influence (7 papers) and Social Media and Politics (6 papers). John Bryden collaborates with scholars based in United Kingdom, United States and Italy. John Bryden's co-authors include Filippo Menczer, Francesco Pierri, Kai‐Cheng Yang, Netta Cohen, Matthew DeVerna, Vincent A. A. Jansen, David Axelrod, Christopher Torres-Lugo, Alessandro Flammini and Brea L. Perry and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

John Bryden

25 papers receiving 728 citations

Hit Papers

Online misinformation is linked to early COVID-19 vaccina... 2021 2026 2022 2024 2022 2021 40 80 120

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John Bryden United Kingdom 12 371 163 145 131 121 25 753
Laura C. Streichert United States 12 121 0.3× 79 0.5× 39 0.3× 33 0.3× 24 0.2× 28 556
Eric M. Clark United States 16 115 0.3× 67 0.4× 135 0.9× 45 0.3× 4 0.0× 46 956
Albert B. Kao United States 11 282 0.8× 5 0.0× 53 0.4× 29 0.2× 19 0.2× 17 766
Dustin J. Welbourne Australia 11 135 0.4× 24 0.1× 12 0.1× 74 0.6× 32 0.3× 19 765
Matti Näsi Finland 20 421 1.1× 54 0.3× 278 1.9× 215 1.6× 10 0.1× 90 1.2k
Takeo Katsuki United States 11 53 0.1× 25 0.2× 29 0.2× 8 0.1× 7 0.1× 15 582
Kazutoshi Sasahara Japan 12 165 0.4× 32 0.2× 103 0.7× 74 0.6× 2 0.0× 51 617
Joshua P. White Australia 10 118 0.3× 35 0.2× 21 0.1× 4 0.0× 280 2.3× 22 1.1k
Read United Kingdom 8 140 0.4× 4 0.0× 225 1.6× 7 0.1× 69 0.6× 22 873
Rebecca C. Tyson Canada 19 193 0.5× 29 0.2× 28 0.2× 8 0.1× 92 0.8× 64 1.7k

Countries citing papers authored by John Bryden

Since Specialization
Citations

This map shows the geographic impact of John Bryden's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John Bryden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Bryden more than expected).

Fields of papers citing papers by John Bryden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Bryden. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John Bryden. The network helps show where John Bryden may publish in the future.

Co-authorship network of co-authors of John Bryden

This figure shows the co-authorship network connecting the top 25 collaborators of John Bryden. A scholar is included among the top collaborators of John Bryden based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John Bryden. John Bryden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
DeVerna, Matthew, et al.. (2024). Identifying and characterizing superspreaders of low-credibility content on Twitter. PLoS ONE. 19(5). e0302201–e0302201. 6 indexed citations
2.
Pierri, Francesco, Matthew DeVerna, Kai‐Cheng Yang, et al.. (2023). One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study. Journal of Medical Internet Research. 25. e42227–e42227. 34 indexed citations
3.
Grabe, Maria Elizabeth, et al.. (2023). The Social Contagion Potential of Pro-Vaccine Messages on Black Twitter. Health Communication. 39(12). 2598–2609. 1 indexed citations
4.
Pierri, Francesco, Brea L. Perry, Matthew DeVerna, et al.. (2022). Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal. Scientific Reports. 12(1). 5966–5966. 144 indexed citations breakdown →
5.
Bryden, John, Eric Silverman, & Simon T. Powers. (2022). Modelling transitions between egalitarian, dynamic leader and absolutist power structures. PLoS ONE. 17(2). e0263665–e0263665. 1 indexed citations
6.
DeVerna, Matthew, et al.. (2021). CoVaxxy: A global collection of English-language Twitter posts about COVID-19 vaccines. 3 indexed citations
7.
DeVerna, Matthew, Francesco Pierri, David Axelrod, et al.. (2021). CoVaxxy: A global collection of English Twitter posts about COVID-19 vaccines. Europe PMC (PubMed Central). 7 indexed citations
8.
Bryden, John & Eric Silverman. (2019). Underlying socio-political processes behind the 2016 US election. PLoS ONE. 14(4). e0214854–e0214854. 7 indexed citations
9.
Bryden, John, Shaun P. Wright, & Vincent A. A. Jansen. (2018). How humans transmit language: horizontal transmission matches word frequencies among peers on Twitter. Journal of The Royal Society Interface. 15(139). 20170738–20170738. 7 indexed citations
10.
Wright, Shaun P., David Denney, Alasdair Pinkerton, Vincent A. A. Jansen, & John Bryden. (2016). Resurgent Insurgents: Quantitative Research Into Jihadists Who Get Suspended but Return on Twitter. SHILAP Revista de lepidopterología. 7(2). 1–1. 5 indexed citations
11.
Cinnirella, Marco, et al.. (2014). Twitter users change word usage according to conversation-partner social identity. Social Networks. 40. 84–89. 40 indexed citations
12.
Bryden, John, Sebastian Funk, & Vincent A. A. Jansen. (2013). Word usage mirrors community structure in the online social network Twitter. EPJ Data Science. 2(1). 32 indexed citations
13.
Ruiz‐González, Mario X., et al.. (2012). DYNAMIC TRANSMISSION, HOST QUALITY, AND POPULATION STRUCTURE IN A MULTIHOST PARASITE OF BUMBLEBEES. Evolution. 66(10). 3053–3066. 58 indexed citations
14.
Bryden, John, Sebastian Funk, Nicholas Geard, Seth Bullock, & Vincent A. A. Jansen. (2010). Stability in flux: community structure in dynamic networks. Journal of The Royal Society Interface. 8(60). 1031–1040. 28 indexed citations
15.
Bryden, John & Vincent A. A. Jansen. (2010). The impact of clonal mixing on the evolution of social behaviour in aphids. Proceedings of the Royal Society B Biological Sciences. 277(1688). 1651–1657. 6 indexed citations
16.
Wallis, Mick, et al.. (2009). Embodied conversations: performance and the design of a robotic dancing partner. Design Studies. 31(2). 99–117. 19 indexed citations
17.
Bryden, John, et al.. (2008). Building artificial personalities: expressive communication channels based on an interlingua for a human-robot dance. Artificial Life. 80–87. 5 indexed citations
18.
Bryden, John & Netta Cohen. (2008). Neural control of Caenorhabditis elegans forward locomotion: the role of sensory feedback. Biological Cybernetics. 98(4). 339–351. 54 indexed citations
19.
Bryden, John & Jason Noble. (2006). Computational modelling, explicit mathematical treatments, and scientific explanation. ePrints Soton (University of Southampton). 8 indexed citations
20.
Bryden, John & Netta Cohen. (2004). A Simulation Model of the Locomotion Controllers for the Nematode Caenorhabditis elegans. The MIT Press eBooks. 183–192. 19 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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