Vedika Gupta

1.4k citations
53 papers · 732 · h-index 15

Impact in

Papers in

Vedika Gupta

48 papers receiving 697 citations

Peers

Vedika Gupta
Comparison fields: 5 of 125
  • Artificial Intelligence 314
  • Modeling and Simulation 35
  • Health Informatics 8
  • Computer Networks and Communications 116
  • Computer Vision and Pattern Recognition 88
Replace Roseline Oluwaseun Ogundokun with:
Roseline Oluwaseun Ogundokun Nigeria
Nasser Alshammari Saudi Arabia
Piotr Bródka Poland
Carmela Comito Italy
Shuo Yu China
Sadique Ahmad Pakistan
Basant Agarwal India
Vibhakar Mansotra India
María Óskarsdóttir Iceland
Sanjay Chakraborty India
Vedika Gupta relative to Roseline Oluwaseun Ogundokun Nigeria Roseline Oluwaseun Ogundokun's profile →
Citations per field
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Roseline Oluwaseun Ogundokun · 1×
Citations per year

Countries citing papers authored by Vedika Gupta

Since Specialization
Citations

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

Fields of papers citing papers by Vedika Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005117
2 202158
3 202156
4 202255
5 202154
6 201934
7 202133
8 202130
9 202125
10 202225
11 202123
12 202020
13 202319
14 201715
15 202214
16 202313
17 202112
18 202411
19 202211
20 20249

About Vedika Gupta

Vedika Gupta is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Management Science and Operations Research and Management Information Systems, having authored 53 papers that have together received 732 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (9 papers), Hate Speech and Cyberbullying Detection (7 papers), Advanced Text Analysis Techniques (5 papers), Big Data and Business Intelligence (4 papers), Topic Modeling (4 papers), Human Pose and Action Recognition (3 papers), Natural Language Processing Techniques (3 papers) and Stock Market Forecasting Methods (3 papers). The work is most often cited by research in Artificial Intelligence (314 citations), Modeling and Simulation (35 citations), Health Informatics (8 citations), Computer Networks and Communications (116 citations) and Computer Vision and Pattern Recognition (88 citations). Vedika Gupta has collaborated with scholars based in India, Malaysia and United States. Frequent co-authors include Nikita Jain, Senthilkumar Mohan, Vivek Kumar Singh, Ali Ahmadian, Matthew Millard, Nils Gura, Hans Eberle, Sheueling Chang Shantz, Массимилиано Феррара and KC Santosh. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Multimedia Tools and Applications, Geoheritage, Information Processing & Management and Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery.

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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