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Discourse processing in scientific articles and social media

Maria Liakata ( University of Warwick )
I will present an overview of work of mine on automatic generation of scientific discourse annotations (Hypothesis, Results, etc.) and how these have been used in a number of tasks including automatic summarisation and fine-grained querying of publications. I will also discuss our work on recognising rumours in conversation threads on social media and analysing target specific sentiment on Twitter.

Speaker bio

Maria Liakata is Assistant Professor at the Department of Computer Science at the University of Warwick and Exchange Assistant Professor at the Centre for Urban Science and Progress (CUSP) at New York University (NYU) since January 2013. She holds an IBM Faculty Award for studying “Emotion sensing using heterogeneous mobile phone data” and she is a co-investigator on the EU Project PHEME. Previously she held an Early Career Fellowship from the Leverhulme Trust (2010-2013) on reasoning with scientific articles, hosted at the European Bioinformatics Institute, Cambridge where she remains a visiting fellow. She has a natural language processing background and a DPhil from the University of Oxford on the topic of inducing domain theories from text. Her research interests include knowledge discovery from text, natural language processing for social media, sentiment analysis and emotion recognition from text, biomedical text mining and natural language processing for health and social good.

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