I am a Post Doctoral Research Assistant working with Dr. Maria Liakata funded by the Alan Turing Institute in London.

Research

My research is focused on Rumour Stance and Veracity Classification in social media conversations. Veracity classification means a task of identifying whether a given conversation discusses a True, False or Unverified rumour. Stance classification implies determining the attitude of responses discussing a rumour towards its veracity as either Supporting, Denying, Questioning or Commenting. In my work I study the relations between these tasks, as patterns of support and denial can be indicative of the final veracity label. As the input data is in the form of conversations discussing rumours, I utilise the conversation structure to enhance predictive models. I work with deep learning models as this approach allows flexible architectures and has benefits of representation learning. Recurrent and recursive neural networks allow to model time sequences and/or conversation tree-like structures.

You can see a short video about my PhD research here:

Research interests

My general research interests are Machine Learning, Data Mining, Deep Learning, Natural Language Processing and Image Processing.

Publications

• Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik. Stance classification in rumours as a sequential task exploiting the tree structure of social media conversations // Proceedings of the International Conference on Computational Linguistics. – Association for Natural Language Processing (ANLP), 2016.
• Elena Kochkina, Maria Liakata, and Isabelle Augenstein. 2017. Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM. In Proceedings of SemEval. ACL
• Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein. Discourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers - Information Processing & Management, 2017.
• Elena Kochkina, Maria Liakata, Arkaitz Zubiaga. All-in-one: Multi-task Learning for Rumour Verification // Proceedings of the 27th International Conference on Computational Linguistics (COLING), 2018
• Gorrell, G., Bontcheva, K., Derczynski, L., Kochkina, E., Liakata, M., & Zubiaga, A. (2018). RumourEval 2019: Determining Rumour Veracity and Support for Rumours. arXiv preprint arXiv:1809.06683, 2018
• Madabushi H. T., Kochkina E., Castelle M. Cost-Sensitive BERT for Generalisable Sentence Classification on Imbalanced Data //Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda. – 2019
• Elena Kochina and Maria Liakata, Estimating predictive uncertainty for rumour verification models // To appear in proceedings of Annual Conference of the Association for Computational Linguistics (ACL), 2020

Teaching

• CS918 Natural Language Processing (Term II in 2015/16, 2016/17, 2017/18, Lab Demonstations, Introduction Seminars on Neural Networks)
• CS130 Mathematics for Computer Scientists I (Term I, 2015/16, Small Group Seminars)
• CS909 Data Mining (Term II, 2015/16, Lab Demonstrations)

Seminars and Reading groups

• Member of Natural Language Processing Interest Group @ Turing Institute (Email if you are interested to attend any of the meetings)
• I am a part of the Statistics and Machine Learning Reading Group.
• I am a member of the Natural Language Processing Reading Group
• I helped organise and record WISC seminars in 2015-2016.
• I helped organise Bridges Summer School on Big Data and Networks in Social Sciences 2016.

Education

• 2015 - 2019: PhD in Urban Science, University of Warwick
• 2017 - 2019: Visiting student, The Alan Turing Institute, London, UK
• 2016 - 2017: Enrichment student, The Alan Turing Institute, London, UK

• 2013-2015: MSc in Complex Systems Science, University of Warwick, UK; Chalmers University, Sweden

  Thesis 1: Application of Digital Image Inpainting in Electrochemical Scanning Probe Microscopy, supervised by Prof. Patrick Unwin and Dr. Kim McKelvey

  Thesis 2: Analysis and Evaluation of Classification Models for Disease Detection Using Human Gut Metagenomic Data, supervised by Dr. Fredrik Karlsson

• 2012 - 2015: MSc in Applied Mathematics and Informatics, Lobachevsky State University of Nizhny Novgorod, Russia
• 2008-2012: BSc in Applied Mathematics and Informatics, Lobachevsky State University of Nizhny Novgorod, Russia

Elena Kochkina

E dot Kochkina at warwick dot ac dot uk

The Alan Turing Institute, British Library, London, NW1 2DB