Nitin Jindal
Impact in
- Information Systems top 0.2%
- Spam and Phishing Detection
- Artificial Intelligence top 0.5%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Topic Modeling
Papers in
-
- Sentiment Analysis and Opinion Mining 7
- Text and Document Classification Technologies 4
- Topic Modeling 3
- Advanced Text Analysis Techniques 1
-
- Spam and Phishing Detection 6
- Co-authors
- Bing Liu (7 shared papers)Bing Liu (1 shared paper)Ee‐Peng Lim (2 shared papers)Hady W. Lauw (1 shared paper)Viet-An Nguyen (1 shared paper)Natalie Glance (1 shared paper)Arjun Mukherjee (1 shared paper)Junhui Wang (1 shared paper)
- Journals
- Data Archiving and Networked Services (DANS) (1 paper)National Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesSingaporeAustria
In The Last Decade
Nitin Jindal
11 papers receiving 2.6k citations
Nitin Jindal's Hit Papers
Peers
Comparison fields: 5 of 67
- Information Systems 2.0k
- Artificial Intelligence 2.1k
- Signal Processing 442
- Computer Networks and Communications 494
- Sociology and Political Science 791
Countries citing papers authored by Nitin Jindal
This map shows the geographic impact of Nitin Jindal'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 Nitin Jindal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nitin Jindal more than expected).
Fields of papers citing papers by Nitin Jindal
This network shows the impact of papers produced by Nitin Jindal. 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 Nitin Jindal. The network helps show where Nitin Jindal may publish in the future.
Co-authors
The 22 scholars most cited alongside Nitin Jindal, 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 | Opinion spam and analysis Hit paper breakdown → | 2008 | 973 |
| 2 | Detecting product review spammers using rating behaviors Hit paper breakdown → | 2010 | 472 |
| 3 | 2007 | 288 | |
| 4 | 2006 | 264 | |
| 5 | 2010 | 220 | |
| 6 | Mining comparative sentences and relations | 2006 | 216 |
| 7 | 2007 | 155 | |
| 8 | 2011 | 147 | |
| 9 | 2007 | 32 | |
| 10 | 2010 | 10 | |
| 11 | 2020 | 4 |
About Nitin Jindal
Nitin Jindal is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Signal Processing, having authored 11 papers that have together received 2.8k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (7 papers), Spam and Phishing Detection (6 papers), Text and Document Classification Technologies (4 papers), Topic Modeling (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Network Security and Intrusion Detection (2 papers), Advanced Text Analysis Techniques (1 paper) and Remote-Sensing Image Classification (1 paper). The work is most often cited by research in Information Systems (2.0k citations), Artificial Intelligence (2.1k citations), Signal Processing (442 citations), Computer Networks and Communications (494 citations) and Sociology and Political Science (791 citations). Nitin Jindal has collaborated with scholars based in United States, Singapore and Austria. Frequent co-authors include Bing Liu, Bing Liu, Ee‐Peng Lim, Hady W. Lauw, Viet-An Nguyen, Natalie Glance, Arjun Mukherjee, Junhui Wang, Christin Seifert and Lucas Paletta. Their work appears in journals such as Data Archiving and Networked Services (DANS) and National Conference on Artificial Intelligence.
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.