I am Saatviga Sudhahar and this is my personal web site. I am a Post-doctoral Researcher in the Department of Computer Science, University of Bristol. I have wide interests in research areas including Data Science, Machine Learning, Natural Language Processing and Deep Learning. I am also interested in interdisciplinary research such as Computational Social Science and Digital Humanities.

I currently work for an European Research Council (ERC) Advanced Grant funded project “ThinkBig: Patterns in Big Data: Methods, Applications and Implications” under Professor Nello Cristianini. In this project I focus in the areas of Large scale news content analysis, Natural language generation, Machine Translation using statistical and recurrent neural network models and Language modelling in large scale. I’m very keen in the latest developments on Deep Learning for Natural Language Processing.

Recent Posts

  • Content Analysis of 150 years of British Periodicals

Previous studies have shown that it is possible to detect macroscopic patterns of cultural change over periods of centuries by analyzing large textual time series, specifically digitized books. This method promises to empower scholars with a quantitative and data-driven tool to study culture and society, but its power has been limited by the use of data from books and simple analytics based essentially on word counts.

This study addresses these problems by assembling a vast corpus of regional newspapers from the United Kingdom, incorporating very fine-grained geographical and temporal information that is not available for books. The corpus spans 150 years and is formed by millions of articles, representing 14% of all British regional outlets of the period. Read more..

  • Gender Representation in Online News

It has long been argued that women are under-represented and marginalised in relation to men in the world’s news media. In this research we analysed over two million articles to find out how gender is represented in online news. The study, which is the largest undertaken to date, found men’s views and voices are represented more in online news than women’s.

Modern AI, which is frequently in the news, is a great tool to support research and can automate tasks that would take humans an impossible amount of person-hours to complete. It is now possible to automate the task of recognising the gender of a face with a remarkable level of accuracy, and it is also possible to detect references to people in online text, along with their gender. Read more..

 

 

Recent Publications

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