Chris Eckl
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining 3
- Machine Learning in Healthcare 2
- Topic Modeling 2
- Advanced Text Analysis Techniques 2
- Cryptography and Data Security 1
- Health Information Management top 10%
- Artificial Intelligence in Healthcare 1
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- Complex Network Analysis Techniques 2
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- Mental Health via Writing 1
- Co-authors
- Amir HussainErik CambriaCatherine HavasiJames B. MunroTim BensonT.S. DurraniWarner V. SlackStephen J Leslie
- Journals
- Expert Systems with Applications (1 paper)Research Output (Edinburgh Napier University) (3 papers)
- Partner nations
- United KingdomUnited StatesSingapore
In The Last Decade
Chris Eckl
7 papers receiving 232 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 174
- Health Information Management 18
- Experimental and Cognitive Psychology 20
- Statistical and Nonlinear Physics 18
- General Social Sciences 4
Countries citing papers authored by Chris Eckl
This map shows the geographic impact of Chris Eckl'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 Chris Eckl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Eckl more than expected).
Fields of papers citing papers by Chris Eckl
This network shows the impact of papers produced by Chris Eckl. 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 Chris Eckl. The network helps show where Chris Eckl may publish in the future.
Co-authorship network
The 16 scholars most cited alongside Chris Eckl, 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 | 2024 | 0 | |
| 2 | 2013 | 2 | |
| 3 | 2012 | 67 | |
| 4 | Taking Refuge in Your Personal Sentic Corner | 2011 | 5 |
| 5 | 2011 | 14 | |
| 6 | 2010 | 90 | |
| 7 | Towards Crowd Validation of the UK National Health Service | 2010 | 25 |
| 8 | AffectiveSpace: Blending Common Sense and Affective Knowledge to Perform Emotive Reasoning | 2009 | 38 |
About Chris Eckl
Chris Eckl is a scholar working on Health Information Management, Artificial Intelligence, Statistical and Nonlinear Physics, Statistics and Probability and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 241 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (3 papers), Machine Learning in Healthcare (2 papers), Topic Modeling (2 papers), Advanced Text Analysis Techniques (2 papers), Complex Network Analysis Techniques (2 papers), Artificial Intelligence in Healthcare (1 paper), Cryptography and Data Security (1 paper) and Mental Health via Writing (1 paper). The work is most often cited by research in Artificial Intelligence (174 citations), Health Information Management (18 citations), Experimental and Cognitive Psychology (20 citations), Statistical and Nonlinear Physics (18 citations) and General Social Sciences (4 citations). Chris Eckl has collaborated with scholars based in United Kingdom, United States and Singapore. Frequent co-authors include Amir Hussain, Erik Cambria, Catherine Havasi, James B. Munro, Tim Benson, T.S. Durrani, Warner V. Slack, Stephen J Leslie, Peipei Yang and Christos Chrysoulas. Their work appears in journals such as Expert Systems with Applications and Research Output (Edinburgh Napier University).
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.