Matthew Shardlow

1.7k total citations
43 papers, 802 citations indexed

About

Matthew Shardlow is a scholar working on Artificial Intelligence, Molecular Biology and General Health Professions. According to data from OpenAlex, Matthew Shardlow has authored 43 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 5 papers in Molecular Biology and 4 papers in General Health Professions. Recurrent topics in Matthew Shardlow's work include Text Readability and Simplification (28 papers), Topic Modeling (26 papers) and Natural Language Processing Techniques (26 papers). Matthew Shardlow is often cited by papers focused on Text Readability and Simplification (28 papers), Topic Modeling (26 papers) and Natural Language Processing Techniques (26 papers). Matthew Shardlow collaborates with scholars based in United Kingdom, United States and Poland. Matthew Shardlow's co-authors include Sophia Ananiadou, Marcos Zampieri, Raheel Nawaz, Azadeh Nikfarjam, Graciela Gonzalez‐Hernandez, Abeed Sarker, Ioannis Korkontzelos, John McNaught, M. Cooper and Richard Evans and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and ACM Computing Surveys.

In The Last Decade

Matthew Shardlow

40 papers receiving 737 citations

Peers

Matthew Shardlow
Manas Gaur United States
Cédrick Fairon Belgium
Goran Topić Japan
Mark Hepple United Kingdom
Samuel Brody United States
Samuel Bayer United States
Rodney D. Nielsen United States
Stephen Pulman United Kingdom
Tomaž Erjavec Slovenia
Marie Meteer United States
Manas Gaur United States
Matthew Shardlow
Citations per year, relative to Matthew Shardlow Matthew Shardlow (= 1×) peers Manas Gaur

Countries citing papers authored by Matthew Shardlow

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Shardlow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Shardlow

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Shardlow. A scholar is included among the top collaborators of Matthew Shardlow 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 Matthew Shardlow. Matthew Shardlow is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ranasinghe, Tharindu, et al.. (2024). MultiLS: An End-to-End Lexical Simplification Framework. 1–11. 1 indexed citations
2.
3.
Kamiran, Faisal, et al.. (2024). SATS: simplification aware text summarization of scientific documents. Frontiers in Artificial Intelligence. 7. 1375419–1375419.
4.
Ranasinghe, Tharindu, et al.. (2024). Deep learning approaches to lexical simplification: A survey. Journal of Intelligent Information Systems. 63(1). 111–134. 4 indexed citations
5.
Shardlow, Matthew, Suppawong Tuarob, Raheem Sarwar, et al.. (2023). Generative image captioning in Urdu using deep learning. Journal of Ambient Intelligence and Humanized Computing. 14(6). 7719–7731. 7 indexed citations
6.
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Saggion, Horacio, et al.. (2022). Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification. 271–283. 17 indexed citations
8.
Nguyen, Nhung T. H., et al.. (2022). UoM&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification. 218–224. 2 indexed citations
9.
Nawaz, Raheel, Matthew Shardlow, Georgios Kontonatsios, et al.. (2022). Leveraging AI and Machine Learning for National Student Survey: Actionable Insights from Textual Feedback to Enhance Quality of Teaching and Learning in UK’s Higher Education. Applied Sciences. 12(1). 514–514. 18 indexed citations
10.
Li, Zihao, Matthew Shardlow, & Saeed‐Ul Hassan. (2022). An Investigation into the Effect of Control Tokens on Text Simplification. 154–165.
11.
Štajner, Sanja, et al.. (2022). Lexical simplification benchmarks for English, Portuguese, and Spanish. Frontiers in Artificial Intelligence. 5. 991242–991242. 18 indexed citations
12.
Shardlow, Matthew, Richard Evans, Gustavo Henrique Paetzold, & Marcos Zampieri. (2021). SemEval-2021 Task 1: Lexical Complexity Prediction. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 1–16. 44 indexed citations
13.
Cooper, M. & Matthew Shardlow. (2020). CombiNMT: An Exploration into Neural Text Simplification Models. Language Resources and Evaluation. 5588–5594. 10 indexed citations
14.
Khan, Muhammad Usman Shahid, et al.. (2019). Bot detection using a single post on social media. 215–220. 31 indexed citations
15.
Shardlow, Matthew, et al.. (2018). A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience. Neuroinformatics. 17(3). 391–406. 16 indexed citations
16.
Korkontzelos, Ioannis, Azadeh Nikfarjam, Matthew Shardlow, et al.. (2016). Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts. Journal of Biomedical Informatics. 62. 148–158. 122 indexed citations
17.
Przybyła, Piotr, Matthew Shardlow, Sophie Aubin, et al.. (2016). Text mining resources for the life sciences. Database. 2016. 38 indexed citations
18.
Shardlow, Matthew. (2014). Out in the Open: Finding and Categorising Errors in the Lexical Simplification Pipeline. Language Resources and Evaluation. 1583–1590. 37 indexed citations
19.
Shardlow, Matthew. (2013). A Comparison of Techniques to Automatically Identify Complex Words.. Research Explorer (The University of Manchester). 103–109. 62 indexed citations
20.
Shardlow, Matthew. (2013). The CW Corpus: A New Resource for Evaluating the Identification of Complex Words. Meeting of the Association for Computational Linguistics. 69–77. 16 indexed citations

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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