Srinivas Pykl
Impact in
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- Hate Speech and Cyberbullying Detection
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
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- Humor Studies and Applications
Papers in
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- Natural Language Processing Techniques 3
- Sentiment Analysis and Opinion Mining 2
- Topic Modeling 2
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- Psychological Well-being and Life Satisfaction 1
- Cultural Differences and Values 1
- Co-authors
- Amitava Das (5 shared papers)Björn Gambäck (3 shared papers)Tanmoy Chakraborty (3 shared papers)Thamar Solorio (2 shared papers)Parth Patwa (2 shared papers)Chhavi Sharma (1 shared paper)William G. Scott (1 shared paper)P. Viswanath (1 shared paper)
- Partner nations
- IndiaNorwayUnited States
In The Last Decade
Srinivas Pykl
5 papers receiving 218 citations
Peers
Comparison fields: 5 of 29
- Artificial Intelligence 212
- Social Psychology 49
- Communication 14
- Signal Processing 16
- Information Systems 33
Countries citing papers authored by Srinivas Pykl
This map shows the geographic impact of Srinivas Pykl'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 Srinivas Pykl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srinivas Pykl more than expected).
Fields of papers citing papers by Srinivas Pykl
This network shows the impact of papers produced by Srinivas Pykl. 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 Srinivas Pykl. The network helps show where Srinivas Pykl may publish in the future.
Co-authors
The 12 scholars most cited alongside Srinivas Pykl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 109 | |
| 2 | 2020 | 69 | |
| 3 | Aggression and Misogyny Detection using BERT: A Multi-Task Approach | 2020 | 38 |
| 4 | 2019 | 17 | |
| 5 | HiLT@IECSIL-FIRE-2018: A Named Entity Recognition System for Indian Languages. | 2018 | 1 |
| 6 | “A pessimist sees the difficulty in every opportunity; an optimist sees the opportunity in every difficulty” – Understanding the psycho-sociological influences to it | 2017 | 1 |
About Srinivas Pykl
Srinivas Pykl is a scholar working on Artificial Intelligence, Social Psychology, Experimental and Cognitive Psychology, Statistical and Nonlinear Physics and Demography, having authored 6 papers that have together received 235 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Topic Modeling (2 papers), Complex Network Analysis Techniques (1 paper), Psychological Well-being and Life Satisfaction (1 paper), Cultural Differences and Values (1 paper), Workplace Spirituality and Leadership (1 paper) and Language, Metaphor, and Cognition (1 paper). The work is most often cited by research in Artificial Intelligence (212 citations), Social Psychology (49 citations), Communication (14 citations), Signal Processing (16 citations) and Information Systems (33 citations). Srinivas Pykl has collaborated with scholars based in India, Norway and United States. Frequent co-authors include Amitava Das, Björn Gambäck, Tanmoy Chakraborty, Thamar Solorio, Parth Patwa, Chhavi Sharma, William G. Scott, P. Viswanath, Sudipta Kar and Gustavo Aguilar. Their work appears in journals such as IEEE Computational Intelligence Magazine.
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.