Puneet Mathur

1.1k citations
47 papers · 570 · h-index 12

Impact in

Papers in

Puneet Mathur

41 papers receiving 544 citations

Peers

Puneet Mathur
Comparison fields: 5 of 82
  • Artificial Intelligence 404
  • Applied Psychology 35
  • Communication 36
  • Management Science and Operations Research 63
  • Information Systems 104
Replace Luis Espinosa-Anke with:
Luis Espinosa-Anke United Kingdom
Eduardo Blanco United States
Kathy McKeown United States
Marcin Gruza Poland
Marco Polignano Italy
Abhilasha Ravichander United States
Piotr Miłkowski Poland
Guangchen Ruan United States
Pei-Yun Hsueh United States
Golnoosh Farnadi United States
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Citations per field
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Luis Espinosa-Anke · 1×
Citations per year

Countries citing papers authored by Puneet Mathur

Since Specialization
Citations

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

Fields of papers citing papers by Puneet Mathur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201881
2 201872
3 201868
4 202038
5 202036
6 202028
7 202125
8
201924
9 201923
10 202019
11 201617
12 201812
13 202111
14 201911
15 201810
16 20189
17 20209
18 20228
19 20217
20 20186

About Puneet Mathur

Puneet Mathur is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Communication and Social Psychology, having authored 47 papers that have together received 570 indexed citations. Recurring topics across this work include Hate Speech and Cyberbullying Detection (7 papers), Stock Market Forecasting Methods (6 papers), Topic Modeling (6 papers), Sentiment Analysis and Opinion Mining (5 papers), Mental Health via Writing (4 papers), Natural Language Processing Techniques (4 papers), Advanced Text Analysis Techniques (4 papers) and Social Media and Politics (3 papers). The work is most often cited by research in Artificial Intelligence (404 citations), Applied Psychology (35 citations), Communication (36 citations), Management Science and Operations Research (63 citations) and Information Systems (104 citations). Puneet Mathur has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Rajiv Ratn Shah, Ramit Sawhney, Debanjan Mahata, Raj Mohan Singh, Dinesh Manocha, Franck Dernoncourt, Roger Zimmermann, Arijit Chowdhury, Vlad I. Morariu and Quan Hung Tran. Their work appears in journals such as Leukemia Research, Indian Journal of Science and Technology, Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology, Applied Intelligence and Applied Clinical Informatics.

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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