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D-Index & Metrics

Computer Science

D-Index
36
Citations
9632
World Ranking
11005
National Ranking
694

Overview

Diana Maynard is a researcher affiliated with the University of Sheffield in the United Kingdom. Their work primarily spans the fields of Computer Science and Social Sciences, with a notable focus on Artificial Intelligence and Sociology and Political Science. Their research interests include misinformation and its impacts, topic modeling, spam and phishing detection, social media and politics, advanced malware detection techniques, advanced text analysis techniques, and hate speech and cyberbullying detection.

Maynard has contributed to a significant body of research that addresses various aspects of information dissemination and digital communication, particularly in the context of social media and misinformation. Their recent papers showcase a range of topics and methodologies applied within artificial intelligence and communication studies.

  • "Classification aware neural topic model for COVID-19 disinformation categorisation," 2021, PLoS ONE
  • "Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food," 2021, Frontiers in Artificial Intelligence
  • "Similarity-Aware Multimodal Prompt Learning for fake news detection," 2023, Information Sciences
  • "Pro-Environmental Campaigns via Social Media: Analysing Awareness and Behaviour Patterns," 2020, Forschungszentrum L3S
  • "Cross-modal augmentation for few-shot multimodal fake news detection," 2025, Engineering Applications of Artificial Intelligence

Their frequent coauthors include Xingyi Song, Ye Jiang, Xiaoman Xu, Kalina Bontcheva, and Yimin Wang, reflecting collaboration across multiple interdisciplinary projects. These collaborations have contributed to a breadth of work in topics such as fake news detection, topic modeling, and social media analysis.

  • Xingyi Song
  • Ye Jiang
  • Xiaoman Xu
  • Kalina Bontcheva
  • Yimin Wang

The venues where Maynard's work has appeared include journals and conferences that focus on both artificial intelligence and social sciences. These publication outlets include arXiv, Frontiers in Artificial Intelligence, Information Sciences, Engineering Applications of Artificial Intelligence, and PLoS ONE.

  • arXiv (Cornell University)
  • Frontiers in Artificial Intelligence
  • Information Sciences
  • Engineering Applications of Artificial Intelligence
  • PLoS ONE

Their research contributions emphasize the intersection of advanced computational techniques and practical social issues such as misinformation, sustainability, and environmental awareness through digital platforms.

Best Publications

  • A framework and graphical development environment for robust NLP tools and applications.

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva;Valentin Tablan

  • Text Processing with GATE

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva

  • GATE: an Architecture for Development of Robust HLT applications

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva;Valentin Tablan

  • The Semantic Web - ISWC 2008

    Amit P. Sheth;Steffen Staab;Michael Dean;Massimo Paolucci

  • Analysis of named entity recognition and linking for tweets

    Leon Derczynski;Diana Maynard;Giuseppe Rizzo;Giuseppe Rizzo;Marieke van Erp

  • Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.

    Diana Maynard;Mark Greenwood

  • The Semantic Web - ISWC 2009

    Abraham Bernstein;David R. Karger;Tom Heath;Lee Feigenbaum

  • Automatic detection of political opinions in tweets

    Diana Maynard;Adam Funk

  • Evolving GATE to meet new challenges in language engineering

    Kalina Bontcheva;Valentin Tablan;Diana Maynard;Hamish Cunningham

  • TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text

    Kalina Bontcheva;Leon Derczynski;Adam Funk;Mark Greenwood

  • Named Entity Recognition from Diverse Text Types

    Diana Maynard;Valentin Tablan;Cristian Ursu;Yorick Wilks

  • Ontology-based information extraction for business intelligence

    Horacio Saggion;Adam Funk;Diana Maynard;Kalina Bontcheva

  • Metrics for Evaluation of Ontology-based Information Extraction

    Diana Maynard;Wim Peters;Yaoyong Li

  • NLP Techniques for Term Extraction and Ontology Population

    Diana Maynard;Yaoyong Li;Wim Peters

  • Developing Language Processing Components with GATE (a User Guide)

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva;Valentin Tablan

  • Architectural elements of language engineering robustness

    Diana Maynard;Valentin Tablan;Hamish Cunningham;Cristian Ursu

  • Shallow Methods for Named Entity Coreference Resolution

    Kalina Bontcheva;Marin Dimitrov;Diana Maynard;Valentin Tablan

  • Microblog-genre noise and impact on semantic annotation accuracy

    Leon Derczynski;Diana Maynard;Niraj Aswani;Kalina Bontcheva

  • Identifying terms by their family and friends

    Diana Maynard;Sophia Ananiadou

  • Proceedings of the 8th International Semantic Web Conference

    Abraham Bernstein;David R. Karger;Tom Heath;Lee Feigenbaum

  • Information Extraction: Algorithms and Prospects in a Retrieval Context Marie-Francine Moens (Katholieke Universiteit Leuven) Springer (Information retrieval series, edited by W. Bruce Croft), 2006, xiii+246 pp; ISBN 978-1-4020-4987-3, $119.00

    Diana Maynard

Frequent Co-Authors

Kalina Bontcheva
Kalina Bontcheva University of Sheffield
Hamish Cunningham
Hamish Cunningham University of Sheffield
Horacio Saggion
Horacio Saggion Pompeu Fabra University
Sophia Ananiadou
Sophia Ananiadou University of Manchester
Yorick Wilks
Yorick Wilks Florida Institute for Human and Machine Cognition
Christian Bizer
Christian Bizer University of Mannheim
Isabelle Augenstein
Isabelle Augenstein University of Copenhagen
Harith Alani
Harith Alani The Open University
Enrico Motta
Enrico Motta The Open University
Paul Baker
Paul Baker Lancaster University

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