Ajita John
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Information Systems top 5%
- Sociology and Political Science
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Dorée Duncan SeligmannHari SundaramMunmun De ChoudhuryVinodkumar PrabhakaranSameer PatilAlfred KobsaYuheng HuYu‐Ru Lin
- Topics
- Complex Network Analysis Techniques (12 papers)Opinion Dynamics and Social Influence (9 papers)Advanced Text Analysis Techniques (4 papers)
- Journals
- Information and Software TechnologyACM Transactions on Information SystemsInternational Journal of Parallel Programming
- Partner nations
- United StatesBermudaNetherlands
In The Last Decade
Ajita John
25 papers receiving 381 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 176
- Statistical and Nonlinear Physics 153
- Information Systems 120
- Sociology and Political Science 97
- Computer Vision and Pattern Recognition 65
Countries citing papers authored by Ajita John
This map shows the geographic impact of Ajita John'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 Ajita John with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ajita John more than expected).
Fields of papers citing papers by Ajita John
This network shows the impact of papers produced by Ajita John. 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 Ajita John. The network helps show where Ajita John may publish in the future.
Co-authorship network of co-authors of Ajita John
This figure shows the co-authorship network connecting the top 25 collaborators of Ajita John. A scholar is included among the top collaborators of Ajita John 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 Ajita John. Ajita John is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 9 | |
| 3 | 8 | |
| 4 | Who Had the Upper Hand? Ranking Participants of Interactions Based on Their Relative Power | 15 |
| 5 | 6 | |
| 6 | 13 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 58 | |
| 10 | 45 | |
| 11 | 85 | |
| 12 | 9 | |
| 13 | 10 | |
| 14 | An Activity-based Perspective of Collaborative Tagging | 6 |
| 15 | 2 | |
| 16 | 20 | |
| 17 | 4 | |
| 18 | Collaborative Tagging and Expertise in the Enterprise | 59 |
| 19 | 1 | |
| 20 | Extraction of Parallelism from Constraint Specifications. | 1 |
About Ajita John
Ajita John is a scholar working on Statistical and Nonlinear Physics, Communication and Software, having authored 25 papers that have together received 429 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (12 papers), Opinion Dynamics and Social Influence (9 papers) and Advanced Text Analysis Techniques (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (153 citations), Communication (56 citations) and Artificial Intelligence (176 citations). Ajita John has collaborated with scholars based in United States, Bermuda and Netherlands. Frequent co-authors include Dorée Duncan Seligmann, Hari Sundaram, Munmun De Choudhury, Munmun De Choudhury, Vinodkumar Prabhakaran, Sameer Patil, Alfred Kobsa, Yuheng Hu, Yu‐Ru Lin and Kunal Singh. Their work appears in journals such as Information and Software Technology, ACM Transactions on Information Systems and International Journal of Parallel Programming.
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.