Daniel Cervone

10.3k citations
100 papers · 6.7k indexed · 2 hit papers · h-index 41

Daniel Cervone

98 papers receiving 6.0k citations

Hit Papers

Differential engagement of self-reactive influences in co...67519832026199720112505007501000

Peers

Daniel Cervone
Comparison fields: 5 of 165
  • Applied Psychology 1.4k
  • Experimental and Cognitive Psychology 1.7k
  • Social Psychology 2.5k
  • General Decision Sciences 212
  • Clinical Psychology 2.1k
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Citations per year

Countries citing papers authored by Daniel Cervone

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Cervone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Daniel Cervone, 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 Daniel Cervone Line = papers co-authored together Daniel Cervone links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20246
2 20231
3 20224
4 202110
5 202142
6 20193
7
Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition.
20186
8 201723
9 201714
10 201154
11 20102
12 200987
13 200828
14 200727
15 200643
16 200391
17
Advances in personality science.
2002187
18 20006
19 200065
20 1991116

About Daniel Cervone

Daniel Cervone is a scholar working on Applied Psychology, General Psychology, General Decision Sciences, Neuropsychology and Physiological Psychology and Experimental and Cognitive Psychology, having authored 100 papers that have together received 6.7k indexed citations. Recurring topics across this work include Behavioral Health and Interventions (28 papers), Personality Traits and Psychology (24 papers), Social and Intergroup Psychology (15 papers), Mental Health Research Topics (15 papers), Motivation and Self-Concept in Sports (12 papers), Cultural Differences and Values (12 papers), Personality Disorders and Psychopathology (9 papers) and Cognitive Abilities and Testing (8 papers). The work is most often cited by research in Applied Psychology (1.4k citations), Experimental and Cognitive Psychology (1.7k citations), Social Psychology (2.5k citations), General Decision Sciences (212 citations) and Clinical Psychology (2.1k citations). Daniel Cervone has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include Albert Bandura, Gian Vittorio Caprara, Philip K. Peake, Yuichi Shoda, William G. Shadel, Robert E. Wood, Walter Mischel, Walter Dill Scott, Jennifer Stock and Robert Becklen. Their work appears in journals such as Journal of Personality and Social Psychology, Cognitive Therapy and Research, Journal of Research in Personality, Personality and Social Psychology Bulletin and Personality and Individual Differences.

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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