Intern
Romanistik

Machine Learning applications in the Social Sciences and the Humanities (17.–18.10.2019)

Workshop in cooperation with the Coimbra Group (Working Group "Social Sciences & Humanities")

Organisation: Prof. Dr. Brigitte Burrichter, Prof. Dr. Raúl Sánchez Prieto

Date: 17–18 October 2019
Venue: Gebäude 21, Hubland Nord (University of Wuerzburg Graduate Schools), 00.006

 

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.

A close cooperation between SSH scholars and computer scientists could have a huge impact on both SSH and STEM (Science, Technology, Engineering and Mathematics) 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 conference will explore the practical possibilities Machine Learning offers to selected research fields within SSH, particularly linguistics, literature, musicology, and sociology. Since the conference is aimed at SSH scholars, presentations will only outline the proposed machine learning model briefly and in a comprehensible way.

Programme

Thursday, 17 October 2019

14:00-16:30

Opening

Jezek, Elisabetta/ Poggiolini, Ilaria/ Figini, Silvia/ Ceravolo, Flavio (Pavia):
Annotating textual data for machine learning (SS and HH, general)

Frank Puppe/ Christoph Wick/ Andreas Haug (Würzburg):
Experiences from the Application of Semiautomatic Workflow Systems Based on Deep Learning Methods for Challenging Optical Character and Music Recognition (OCR, OMR) (HH, Musicology)

16:30-17:00 Coffee break
17:00-19:00

Ben Ahmed, Olfa/ Fernandez-Maloigne, Christine (Poitiers):     CANCELLED
Deep learning for the Social Sciences: facial expressions and emotions. (SS, Psychology)

Pekka Räsänen/ Markus Kaakinen/ Atte Oksanen (Turku/Helsinki/Tampere):
Individuals, identities, and social networks: Using machine learning techniques to analyse how users identify with their social media networks. (SS, Sociology)

19:30 Dinner

Friday, 18 October 2019

9:00-11:00

Raúl Sánchez Prieto/ Andrea Galván (Salamanca):
Using Support Vector Machines for the analysis of language perception. A text act based model. (HH, Linguistics)

Gintautas Tamulevičius/ Audrius Valotka (Vilnius):
Machine learning for the Lithuanian language: state-of-the-art and challenges. (HH, Linguistics)

11:00-11:30 Coffee break
11:30-14:00

Leonard Konle (Würzburg):
Machine Learning in Computational Literary Studies. An Overview of methods and applications

Final discussion