Jake Ryland Williams
- Artificial Intelligence top 5%
- Sociology and Political Science top 10%
- Information Systems top 10%
- Social Psychology
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Christopher M. DanforthPeter Sheridan DoddsAndrew J. ReaganBrian F. TivnanJames P. BagrowSuma DesuEric M. ClarkLewis Mitchell
- Topics
- Misinformation and Its Impacts (3 papers)Complex Network Analysis Techniques (3 papers)Opinion Dynamics and Social Influence (3 papers)
- Cited by
- Artificial IntelligenceExperimental and Cognitive PsychologyStatistical and Nonlinear Physics
- Partner nations
- United StatesAustraliaLithuania
In The Last Decade
Jake Ryland Williams
14 papers receiving 475 citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 203
- Sociology and Political Science 189
- Information Systems 85
- Social Psychology 76
- Experimental and Cognitive Psychology 71
Countries citing papers authored by Jake Ryland Williams
This map shows the geographic impact of Jake Ryland Williams'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 Jake Ryland Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jake Ryland Williams more than expected).
Fields of papers citing papers by Jake Ryland Williams
This network shows the impact of papers produced by Jake Ryland Williams. 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 Jake Ryland Williams. The network helps show where Jake Ryland Williams may publish in the future.
Co-authorship network of co-authors of Jake Ryland Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Jake Ryland Williams. A scholar is included among the top collaborators of Jake Ryland Williams 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 Jake Ryland Williams. Jake Ryland Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | 9 | |
| 4 | 0 | |
| 5 | 9 | |
| 6 | 20 | |
| 7 | 62 | |
| 8 | 1 | |
| 9 | 16 | |
| 10 | 8 | |
| 11 | 47 | |
| 12 | 16 | |
| 13 | 34 | |
| 14 | Human language reveals a universal positivity biasbreakdown → | 252 |
| 15 | 7 | |
| 16 | 5 |
About Jake Ryland Williams
Jake Ryland Williams is a scholar working on Statistical and Nonlinear Physics, Applied Psychology and Human-Computer Interaction, having authored 16 papers that have together received 494 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (3 papers), Complex Network Analysis Techniques (3 papers) and Opinion Dynamics and Social Influence (3 papers). The work is most often cited by research in Artificial Intelligence (203 citations), Experimental and Cognitive Psychology (71 citations) and Statistical and Nonlinear Physics (60 citations). Jake Ryland Williams has collaborated with scholars based in United States, Australia and Lithuania. Frequent co-authors include Christopher M. Danforth, Peter Sheridan Dodds, Andrew J. Reagan, Brian F. Tivnan, James P. Bagrow, Suma Desu, Eric M. Clark, Lewis Mitchell, Morgan R. Frank and Karine Megerdoomian. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.
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.