Emma Barker
- Artificial Intelligence
- Information Systems
- Computer Vision and Pattern Recognition
- Cognitive Neuroscience
- Molecular Biology
- Co-authors
- Robert GaizauskasAhmet AkerMonica Lestari ParamitaTom MercerMark HeppleJulio GonzaloJavier ArtilesJosef Steinberger
- Topics
- Natural Language Processing Techniques (9 papers)Topic Modeling (8 papers)Advanced Text Analysis Techniques (5 papers)
- Partner nations
- United KingdomCzechia
In The Last Decade
Emma Barker
14 papers receiving 65 citations
Peers
Comparison fields: 5 of 18
- Artificial Intelligence 56
- Information Systems 16
- Computer Vision and Pattern Recognition 9
- Cognitive Neuroscience 9
- Molecular Biology 5
Countries citing papers authored by Emma Barker
This map shows the geographic impact of Emma Barker'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 Emma Barker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma Barker more than expected).
Fields of papers citing papers by Emma Barker
This network shows the impact of papers produced by Emma Barker. 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 Emma Barker. The network helps show where Emma Barker may publish in the future.
Co-authorship network of co-authors of Emma Barker
This figure shows the co-authorship network connecting the top 25 collaborators of Emma Barker. A scholar is included among the top collaborators of Emma Barker based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emma Barker. Emma Barker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 6 | |
| 3 | What's the issue here?: Task-based evaluation of reader comment summarization systems | 3 |
| 4 | 8 | |
| 5 | 10 | |
| 6 | 7 | |
| 7 | 6 | |
| 8 | 3 | |
| 9 | Bootstrapping Term Extractors for Multiple Languages | 5 |
| 10 | 3 | |
| 11 | Assessing the Comparability of News Texts | 2 |
| 12 | Applying ISO-Space to Healthcare Facility Design Evaluation Reports | 5 |
| 13 | FlickLing: a Multilingual Search Interface for Flickr | 4 |
| 14 | Large-scale interactive evaluation of multilingual information access systems: the iCLEF Flickr challenge | 7 |
About Emma Barker
Emma Barker is a scholar working on Artificial Intelligence, Computer Science Applications and Cognitive Neuroscience, having authored 14 papers that have together received 75 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (8 papers) and Advanced Text Analysis Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (56 citations), Computer Science Applications (4 citations) and Information Systems (16 citations). Emma Barker has collaborated with scholars based in United Kingdom and Czechia. Frequent co-authors include Robert Gaizauskas, Ahmet Aker, Monica Lestari Paramita, Tom Mercer, Mark Hepple, Julio Gonzalo, Javier Artiles, Josef Steinberger, Udo Kruschwitz and Paul Clough. Their work appears in journals such as Memory & Cognition, Language Resources and Evaluation and Journal of Cognitive Psychology.
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.