Member
Gregoire Burel
Research Associate
Grégoire Burel is a research associate at the Knowledge Media Institute (KMi). His work involves the development and application of machine learning techniques and social semantics for the investigation of user behaviour in different settings (e.g. answering behaviour, energy consumption habits and emerging behaviour in emergency crisis), the development of visualisation tools and platforms (e.g. energyuse.eu, Sparks Prism) and ontological models (e.g. DoRES, EUse,Veracity, Curio).
He is currently involved in the EU founded COMRADES project where he is investigating the application of Deep Learning methods for identifying crisis-related content in social media. Previously, he developed the energyuse.eu platform for the DecarboNet EU project and studied answering behaviour in Question Answering (Q&A) communities for the ROBUST EU project.
Grégoire has recently obtained his PhD in predicting best answer in Q&A communities and has previously worked as a research assistant at the University of Sheffield on the EU funded WeKnowIt project where he worked on the development of an Emergency Response platform.
Keys: Social Semantic Web, Machine Learning, Economics, User Value, Natural Language Processing, Online Communities
News
14 Nov 2019
11 Jun 2019
23 Apr 2019
17 Dec 2018
03 Nov 2017
Publications
Burel, G., Farrell, T., Mensio, M., Khare, P. and Alani, H. (2020) Co-Spread of Misinformation and Fact-Checking Content during the Covid-19 Pandemic, Proceedings of the 12th International Social Informatics Conference (SocInfo), Pisa, Italy
Khare, P., Burel, G. and Alani, H. (2019) Relevancy Identification Across Languages and Crisis Types Relevancy Identification Across Languages and Crisis Types, 34, pp. 19-28
Khare, P., Burel, G. and Alani, H. (2018) Classifying Crises-Information Relevancy with Semantics, Extended Semantic Web Conference (ESWC) 2018, Heraklion, Crete
Burel, G. and Alani, H. (2018) Crisis Event Extraction Service (CREES) - Automatic Detection and Classification of Crisis-related Content on Social Media, 15th International Conference on Information Systems for Crisis Response and Management, Rochester, NY, USA
Burel, G., Saif, H. and Alani, H. (2017) Semantic Wide and Deep Learning for Detecting Crisis-Information Categories on Social Media, 16th International Semantic Web Conference, Vienna, Austria