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Date(s) - 19/11/2015
2:00 pm - 4:00 pm

ASB Ground Floor Seminar Room


NLP techniques for processing scientific articles and sentiment in social media

Maria Liakata

Assistant Professor, Department of Computer Science, University of Warwick and Exchange Assistant Professor, CUSP, New York University


I will present an overview of recent work of mine which exploits automatically generated scientific discourse annotations such as Hypothesis, Results, Conclusion, Method and more  to create summaries for the articles, provide more efficient search and automatically characterise article type (e.g. review article, research paper, etc.).
I will also discuss our work in social media analysis for identifying sentiment targeted to specific entities.


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 DPhil from the University of Oxford on the topic of inducing domain theories. Her research interests include knowledge discovery from text, biomedical text mining, natural language processing for social media, sentiment analysis and emotion recognition from text, and natural language processing for mental health applications.

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