John Cardiff
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Hate Speech and Cyberbullying Detection
- Advanced Text Analysis Techniques
- Marketing top 10%
Papers in
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- Topic Modeling 13
- Sentiment Analysis and Opinion Mining 8
- Advanced Text Analysis Techniques 8
- Semantic Web and Ontologies 7
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- Spam and Phishing Detection 8
- Web Data Mining and Analysis 8
- Co-authors
- Paolo Rosso (18 shared papers)Mikhail Alexandrov (12 shared papers)Javier Sánchez (1 shared paper)Luís Callarisa (1 shared paper)David Pinto (8 shared papers)Andrey Ignatov (2 shared papers)Giuseppe Santucci (5 shared papers)Tiziana Catarci (5 shared papers)
In The Last Decade
John Cardiff
52 papers receiving 438 citations
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 271
- Marketing 60
- Information Systems 149
- Signal Processing 47
- Toxicology 12
Countries citing papers authored by John Cardiff
This map shows the geographic impact of John Cardiff'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 John Cardiff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Cardiff more than expected).
Fields of papers citing papers by John Cardiff
This network shows the impact of papers produced by John Cardiff. 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 John Cardiff. The network helps show where John Cardiff may publish in the future.
Co-authors
The 15 scholars most cited alongside John Cardiff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 58 | |
| 2 | 2017 | 30 | |
| 3 | 2015 | 27 | |
| 4 | 2010 | 25 | |
| 5 | 2019 | 24 | |
| 6 | 2011 | 23 | |
| 7 | 2023 | 22 | |
| 8 | 2020 | 22 | |
| 9 | 1997 | 15 | |
| 10 | 2021 | 15 | |
| 11 | On the Difficulty of Clustering Microblog Texts for Online Reputation Management | 2011 | 13 |
| 12 | Classifying Misogynistic Tweets Using a Blended Model: the AMI Shared Task in IBEREVAL 2018 | 2018 | 13 |
| 13 | 2006 | 13 | |
| 14 | 2017 | 13 | |
| 15 | 2010 | 12 | |
| 16 | 2023 | 11 | |
| 17 | 1996 | 11 | |
| 18 | 2018 | 9 | |
| 19 | User Profile Construction in the TWIN Personality-based Recommender System | 2011 | 9 |
| 20 | 1997 | 8 |
About John Cardiff
John Cardiff is a scholar working on Artificial Intelligence, Information Systems, Sociology and Political Science, Computer Networks and Communications and Signal Processing, having authored 55 papers that have together received 471 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Spam and Phishing Detection (8 papers), Web Data Mining and Analysis (8 papers), Sentiment Analysis and Opinion Mining (8 papers), Advanced Text Analysis Techniques (8 papers), Misinformation and Its Impacts (7 papers), Semantic Web and Ontologies (7 papers) and Advanced Database Systems and Queries (7 papers). The work is most often cited by research in Artificial Intelligence (271 citations), Marketing (60 citations), Information Systems (149 citations), Signal Processing (47 citations) and Toxicology (12 citations). John Cardiff has collaborated with scholars based in Ireland, Spain and Mexico. Frequent co-authors include Paolo Rosso, Mikhail Alexandrov, Javier Sánchez, Luís Callarisa, David Pinto, Andrey Ignatov, Giuseppe Santucci, Tiziana Catarci, Paloma Martı́nez and Karin Verspoor. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Lecture notes in computer science, International Journal of Cooperative Information Systems, The VLDB Journal and Theory and applications of categories.
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.