no code implementations • Findings (ACL) 2022 • Erenay Dayanik, Andre Blessing, Nico Blokker, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa, Sebastian Pado
Many tasks in text-based computational social science (CSS) involve the classification of political statements into categories based on a domain-specific codebook.
no code implementations • ACL (spnlp) 2021 • Erenay Dayanik, Andre Blessing, Nico Blokker, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa, Sebastian Padó
The analysis of public debates crucially requires the classification of political demands according to hierarchical claim ontologies (e. g. for immigration, a supercategory “Controlling Migration” might have subcategories “Asylum limit” or “Border installations”).
no code implementations • LREC 2022 • Nadja Schauffler, Toni Bernhart, Andre Blessing, Gunilla Eschenbach, Markus Gärtner, Kerstin Jung, Anna Kinder, Julia Koch, Sandra Richter, Gabriel Viehhauser, Ngoc Thang Vu, Lorenz Wesemann, Jonas Kuhn
We present the steps taken towards an exploration platform for a multi-modal corpus of German lyric poetry from the Romantic era developed in the project »textklang«.
no code implementations • LREC 2020 • Gabriella Lapesa, Andre Blessing, Nico Blokker, Erenay Dayanik, Sebastian Haunss, Jonas Kuhn, Sebastian Pad{\'o}
DEbateNet-migr15 is a manually annotated dataset for German which covers the public debate on immigration in 2015.
1 code implementation • ACL 2019 • Sebastian Pad{\'o}, Andre Blessing, Nico Blokker, Erenay Dayanik, Sebastian Haunss, Jonas Kuhn
Understanding the structures of political debates (which actors make what claims) is essential for understanding democratic political decision making.
no code implementations • ACL 2019 • Andre Blessing, Nico Blokker, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa, Sebastian Pad{\'o}
This paper describes the MARDY corpus annotation environment developed for a collaboration between political science and computational linguistics.
no code implementations • WS 2017 • Andre Blessing, Nora Echelmeyer, Markus John, Nils Reiter
This paper presents an approach to extract co-occurrence networks from literary texts.
no code implementations • LREC 2014 • Andre Blessing, Jonas Kuhn
We present a web-based application which is called TEA (Textual Emigration Analysis) as a showcase that applies textual analysis for the humanities.