Andrew Yates

3.2k citations
86 papers · 1.2k indexed · h-index 20

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Sentiment Analysis and Opinion Mining
    • Advanced Text Analysis Techniques
    • Information Retrieval and Search Behavior
    • Spam and Phishing Detection

Papers in

    • Topic Modeling 50
    • Natural Language Processing Techniques 19
    • Advanced Text Analysis Techniques 10
    • Sentiment Analysis and Opinion Mining 6
    • Information Retrieval and Search Behavior 11
    • Recommender Systems and Techniques 9
    • Web Data Mining and Analysis 6

Andrew Yates

77 papers receiving 1.1k citations

Peers

Andrew Yates
Comparison fields: 5 of 124
  • Artificial Intelligence 783
  • Information Systems 360
  • Applied Psychology 47
  • Computer Vision and Pattern Recognition 165
  • Signal Processing 58
Replace Valentin Tablan with:
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Citations per field
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Citations per year

Countries citing papers authored by Andrew Yates

Since Specialization
Citations

This map shows the geographic impact of Andrew Yates'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 Andrew Yates with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Yates more than expected).

Fields of papers citing papers by Andrew Yates

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Yates. 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 Andrew Yates. The network helps show where Andrew Yates may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Andrew Yates, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andrew Yates Line = papers co-authored together Andrew Yates links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20241
4 20241
5 20242
6 20240
7 20244
8 20241
9 20231
10 20237
11 20231
12 20239
13 20233
14 20237
15 202034
16 202010
17 201824
18
Effects of Sampling on Twitter Trend Detection
20165
19
A Framework for Public Health Surveillance
20141
20
Query Reformulation for Clinical Decision Support Search
20145

About Andrew Yates

Andrew Yates is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, General Social Sciences and Management Science and Operations Research, having authored 86 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (50 papers), Natural Language Processing Techniques (19 papers), Biomedical Text Mining and Ontologies (15 papers), Information Retrieval and Search Behavior (11 papers), Advanced Text Analysis Techniques (10 papers), Recommender Systems and Techniques (9 papers), Sentiment Analysis and Opinion Mining (6 papers) and Web Data Mining and Analysis (6 papers). The work is most often cited by research in Artificial Intelligence (783 citations), Information Systems (360 citations), Applied Psychology (47 citations), Computer Vision and Pattern Recognition (165 citations) and Signal Processing (58 citations). Andrew Yates has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Jimmy Lin, Rodrigo Nogueira, Gerhard Weikum, Nazli Goharian, Kashyap Popat, Subhabrata Mukherjee, Ophir Frieder, Arman Cohan, Kai Hui and Luca Soldaini. Their work appears in journals such as Information Retrieval, ACM Transactions on Information Systems, Proceedings of the Royal Society B Biological Sciences, Language Resources and Evaluation and Journal of the Association for Information Science and Technology.

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.

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