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Machine Learning applications in the Social Sciences and the Humanities (SSH)

Dienstag, 12.03.2019

Machine Learning, a recurrent and obvious topic in Science and Technology, will also radically change the way research is carried out in the Social Sciences and the Humanities in a near future.

The conference will take place on October 17 and 18 2019.

A close cooperation between SSH scholars and computer scientists could have a huge impact on both SSH and STEM related research topics. On the one hand, social scientists and humanities scholars may not be able to design and implement themselves the machine learning algorithms they need for their research. On the other, computer scientists cannot progress in their work without the active theoretical and practical support of SSH scholars. The role of a linguist, a historian or a social scientist should be thus to help computer scientists outperform current machine learning models by offering them theoretical approaches both could adapt together to improve their accuracy.  This one day conference to be held at the University of Würzburg and co-organised by the universities of Würzburg and Salamanca will explore the practical possibilities Machine Learning offers to selected research fields within SSH such as linguistics, literature, musicology, history, sociology and others. Since the conference is aimed at SSH scholars, presentations should only outline the proposed machine learning model briefly and in a comprehensible way. Conference speakers should concentrate on explaining how training algorithms and computers to perform large-scale automated analysis of data could make us progress in a given SSH research field. It is intended to publish the proceedings in a prominent book series. It is also hoped that out of the conference a research network might emerge that will develop larger projects and aim for European funding.
Abstracts (title, 200 word outline) to be sent by 01 April 2019 to the organisers: Brigitte Burrichter (brigitte.burrichter(at)uni-wuerzburg.de)   and Raúl Sánchez Prieto (raulsanchez(at)usal.es).


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