Peter A. Gloor

200 papers receiving 4.9k citations

Peter A. Gloor's Hit Papers

In the shades of the uncanny valley: An experimental study of human–chatbot interaction 2018 · 401 citations
4010+5+10Years since publication100200300400

Peers

Peter A. Gloor
Comparison fields: 5 of 185
  • Communication 607
  • Computer Science Applications 348
  • Psychiatry and Mental health 559
  • Management of Technology and Innovation 293
  • Information Systems and Management 276
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Countries citing papers authored by Peter A. Gloor

Since Specialization
Citations

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

Fields of papers citing papers by Peter A. Gloor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter A. Gloor. 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 Peter A. Gloor. The network helps show where Peter A. Gloor may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 214 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”
Hit paper breakdown →
2011413
2
In the shades of the uncanny valley: An experimental study of human–chatbot interaction
Hit paper breakdown →
2018401
3 2019210
4
Contributions of electroencephalography and electrocorticography to the neurosurgical treatment of the epilepsies.
1975208
5
Swarm Creativity: Competitive Advantage through Collaborative Innovation Networks
2006188
6 2013154
7 1983124
8 2006107
9
Localization of epileptic foci.
198598
10 200384
11 198283
12
Capturing Individual and Group Behavior with Wearable Sensors
200982
13 200975
14 200772
15 200772
16 196171
17 200962
18 200661
19 198158
20 201754

About Peter A. Gloor

Peter A. Gloor is a scholar working on Communication, Sociology and Political Science, Statistical and Nonlinear Physics, Social Psychology and Experimental and Cognitive Psychology, having authored 214 papers that have together received 5.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (28 papers), Knowledge Management and Sharing (28 papers), Digital Marketing and Social Media (15 papers), Epilepsy research and treatment (14 papers), Team Dynamics and Performance (12 papers), EEG and Brain-Computer Interfaces (11 papers), Opinion Dynamics and Social Influence (11 papers) and Innovation and Knowledge Management (11 papers). The work is most often cited by research in Communication (607 citations), Computer Science Applications (348 citations), Psychiatry and Mental health (559 citations), Management of Technology and Innovation (293 citations) and Information Systems and Management (276 citations). Peter A. Gloor has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Leon Ciechanowski, Aleksandra Przegalińska, Hauke Fuehres, Mikołaj Magnuski, Detlef Schoder, Kai Fischbach, Andrea Fronzetti Colladon, Alex Pentland, Jean Gotman and D. Olguı́n. Their work appears in journals such as Electroencephalography and Clinical Neurophysiology, Journal of the Association for Information Systems, Future Internet, American Journal of Ophthalmology and Neurology.

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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