Gabriel Lima
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 5%
- Ethics and Social Impacts of AI
Papers in
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- Ethics and Social Impacts of AI 10
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- Psychology of Moral and Emotional Judgment 8
- Neuroethics, Human Enhancement, Biomedical Innovations 2
- Co-authors
- Meeyoung Cha (15 shared papers)Nina Grgić-Hlača (6 shared papers)Chiyoung Cha (3 shared papers)Juhi Kulshrestha (2 shared papers)Onur Varol (2 shared papers)Yong‐Yeol Ahn (2 shared papers)Karandeep Singh (2 shared papers)Seungho Ryu (1 shared paper)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (3 papers)Journal of Medical Internet Research (1 paper)Heliyon (1 paper)PLoS ONE (1 paper)Frontiers in Robotics and AI (2 papers)
- Partner nations
- South KoreaGermanyUnited States
In The Last Decade
Gabriel Lima
20 papers receiving 380 citations
Peers
Comparison fields: 5 of 67
- Health Informatics 28
- Safety Research 115
- Health 51
- Cognitive Neuroscience 94
- Communication 33
Countries citing papers authored by Gabriel Lima
This map shows the geographic impact of Gabriel Lima'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 Gabriel Lima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Lima more than expected).
Fields of papers citing papers by Gabriel Lima
This network shows the impact of papers produced by Gabriel Lima. 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 Gabriel Lima. The network helps show where Gabriel Lima may publish in the future.
Co-authors
The 20 scholars most cited alongside Gabriel Lima, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 72 | |
| 2 | 2021 | 52 | |
| 3 | 2022 | 40 | |
| 4 | 2023 | 36 | |
| 5 | 2020 | 31 | |
| 6 | 2021 | 30 | |
| 7 | 2022 | 20 | |
| 8 | 2023 | 19 | |
| 9 | 2021 | 18 | |
| 10 | 2021 | 18 | |
| 11 | 2022 | 15 | |
| 12 | 2022 | 10 | |
| 13 | 2025 | 7 | |
| 14 | 2023 | 6 | |
| 15 | 2020 | 4 | |
| 16 | 2025 | 4 | |
| 17 | 2025 | 3 | |
| 18 | Explaining the Punishment Gap of AI and Robots. | 2020 | 2 |
| 19 | 2018 | 1 | |
| 20 | 2022 | 1 |
About Gabriel Lima
Gabriel Lima is a scholar working on Safety Research, Cognitive Neuroscience, Artificial Intelligence, Communication and Sociology and Political Science, having authored 21 papers that have together received 389 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (10 papers), Psychology of Moral and Emotional Judgment (8 papers), Misinformation and Its Impacts (5 papers), Hate Speech and Cyberbullying Detection (4 papers), Law, AI, and Intellectual Property (4 papers), Neuroethics, Human Enhancement, Biomedical Innovations (2 papers), Social Media and Politics (2 papers) and Vaccine Coverage and Hesitancy (1 paper). The work is most often cited by research in Health Informatics (28 citations), Safety Research (115 citations), Health (51 citations), Cognitive Neuroscience (94 citations) and Communication (33 citations). Gabriel Lima has collaborated with scholars based in South Korea, Germany and United States. Frequent co-authors include Meeyoung Cha, Nina Grgić-Hlača, Chiyoung Cha, Juhi Kulshrestha, Onur Varol, Yong‐Yeol Ahn, Karandeep Singh, Seungho Ryu, Лев Манович and Hyojin Chin. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Journal of Medical Internet Research, Heliyon, PLoS ONE and Frontiers in Robotics and AI.
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.