Dan Calacci
Impact in
- Transportation top 5%
- Urban Transport and Accessibility
- Human Mobility and Location-Based Analysis
Papers in
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- Digital Economy and Work Transformation 5
- Crime Patterns and Interventions 1
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- Sharing Economy and Platforms 4
- Co-authors
- Alex Pentland (5 shared papers)Xiaowen Dong (1 shared paper)Esteban Moro (1 shared paper)Kent Larson (2 shared papers)Takahiro Yabe (1 shared paper)Andrés Monroy‐Hernández (2 shared papers)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (3 papers)IEEE Multimedia (1 paper)interactions (1 paper)Nature Communications (1 paper)Scientific Data (1 paper)
- Partner nations
- United StatesUnited KingdomSpain
In The Last Decade
Dan Calacci
10 papers receiving 249 citations
Dan Calacci's Hit Papers
Peers
Comparison fields: 5 of 63
- Transportation 116
- Modeling and Simulation 13
- Marketing 25
- Sociology and Political Science 103
- Computer Science Applications 10
Countries citing papers authored by Dan Calacci
This map shows the geographic impact of Dan Calacci'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 Dan Calacci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Calacci more than expected).
Fields of papers citing papers by Dan Calacci
This network shows the impact of papers produced by Dan Calacci. 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 Dan Calacci. The network helps show where Dan Calacci may publish in the future.
Co-authors
The 6 scholars most cited alongside Dan Calacci, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Mobility patterns are associated with experienced income segregation in large US cities Hit paper breakdown → | 2021 | 150 |
| 2 | 2018 | 30 | |
| 3 | 2022 | 24 | |
| 4 | 2022 | 21 | |
| 5 | 2023 | 8 | |
| 6 | 2022 | 8 | |
| 7 | 2023 | 4 | |
| 8 | 2022 | 4 | |
| 9 | 2024 | 3 | |
| 10 | 2025 | 2 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 |
About Dan Calacci
Dan Calacci is a scholar working on Sociology and Political Science, Marketing, Artificial Intelligence, Safety Research and Transportation, having authored 12 papers that have together received 254 indexed citations. Recurring topics across this work include Digital Economy and Work Transformation (5 papers), Sharing Economy and Platforms (4 papers), Ethics and Social Impacts of AI (2 papers), Human Mobility and Location-Based Analysis (2 papers), Complex Network Analysis Techniques (1 paper), Semantic Web and Ontologies (1 paper), Crime Patterns and Interventions (1 paper) and Team Dynamics and Performance (1 paper). The work is most often cited by research in Transportation (116 citations), Modeling and Simulation (13 citations), Marketing (25 citations), Sociology and Political Science (103 citations) and Computer Science Applications (10 citations). Dan Calacci has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Alex Pentland, Xiaowen Dong, Esteban Moro, Kent Larson, Takahiro Yabe and Andrés Monroy‐Hernández. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, IEEE Multimedia, interactions, Nature Communications and Scientific Data.
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.