Manuel Cebrián

7.9k citations
112 papers · 4.3k · 2 hit papers · h-index 32

Impact in

Papers in

Manuel Cebrián

108 papers receiving 4.1k citations

Manuel Cebrián's Hit Papers

Toward understanding the impact of artificial intelligence on labor 2019 · 430 citations
4300+3+6Years since publication100200300400

Peers

Manuel Cebrián
Comparison fields: 5 of 161
  • Transportation 672
  • Communication 520
  • Computer Science Applications 407
  • Statistical and Nonlinear Physics 804
  • Health Informatics 48
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Countries citing papers authored by Manuel Cebrián

Since Specialization
Citations

This map shows the geographic impact of Manuel Cebrián'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 Manuel Cebrián with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manuel Cebrián more than expected).

Fields of papers citing papers by Manuel Cebrián

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Manuel Cebrián. 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 Manuel Cebrián. The network helps show where Manuel Cebrián may publish in the future.

Co-authors

The 25 scholars most cited alongside Manuel Cebrián, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Manuel Cebrián Line = papers co-authored together Manuel Cebrián links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Rapid assessment of disaster damage using social media activity
Hit paper breakdown →
2016479
2
Toward understanding the impact of artificial intelligence on labor
Hit paper breakdown →
2019430
3 2010174
4 2011173
5 2011172
6 2013155
7 2018146
8 2013137
9 2018118
10 2015105
11 2015104
12 201397
13 201995
14 201191
15 201980
16 202077
17 201273
18 201472
19 201470
20 200568

About Manuel Cebrián

Manuel Cebrián is a scholar working on Statistical and Nonlinear Physics, Sociology and Political Science, Artificial Intelligence, Transportation and Communication, having authored 112 papers that have together received 4.3k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (38 papers), Opinion Dynamics and Social Influence (26 papers), Human Mobility and Location-Based Analysis (18 papers), Misinformation and Its Impacts (11 papers), Mobile Crowdsensing and Crowdsourcing (11 papers), Evolutionary Game Theory and Cooperation (10 papers), Computability, Logic, AI Algorithms (8 papers) and Data-Driven Disease Surveillance (7 papers). The work is most often cited by research in Transportation (672 citations), Communication (520 citations), Computer Science Applications (407 citations), Statistical and Nonlinear Physics (804 citations) and Health Informatics (48 citations). Manuel Cebrián has collaborated with scholars based in United States, Spain and Australia. Frequent co-authors include Esteban Moro, Alex Pentland, Iyad Rahwan, Pascal Van Hentenryck, James H. Fowler, Haohui Chen, Yury Kryvasheyeu, Anmol Madan, Nick Obradovich and Morgan R. Frank. Their work appears in journals such as PLoS ONE, Scientific Reports, EPJ Data Science, Nature Communications and Applied Network Science.

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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