Dr. Zoltán Kacsuk

Research Fellow

Publications

2022

  • Zoltan Kacsuk, Magnus Pfeffer, Simone Schroff and Martin Roth: Harmonizing Open Licenses among Online Databases of Enthusiast Communities: Challenges for the Legal Integration of Databases in the Japanese Visual Media Graph Project in Pop! Public. Open. Participatory, DOI 10.54590/pop.2022.005, 2022.
  • Martin Roth, Magnus Pfeffer and Zoltán Kacsuk: Developing the Japanese Visual Media Graph: An Open Knowledge Graph for Researchers Working on Japanese Anime, Manga and Otaku Culture in Digital Humanities 2022: Responding to Asian Diversity - Conference Abstracts, pp. 353-354, University of Tokyo Tokyo, 2022.
  • Magnus Pfeffer, Zoltan Kacsuk and Martin Roth: Japanese Visual Media Graph - Bündelung des Wissens von Fan-Gemeinschaften in einem domänenspezifischen Knowledge Graph in DHd 2022 Kulturen des digitalen Gedächtnisses. 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" (DHd 2022), Potsdam, pp. 151-155, DOI 10.5281/zenodo.6304590, Zenodo, 2022.

2021

  • Zoltan Kacsuk: The Making of an Epoch-Making Anime: Understanding the Landmark Status of Neon Genesis Evangelion in Otaku Culture in Anime Studies: Media-Specific Approaches to Neon Genesis Evangelion, pp. 215-246, DOI 10.16993/bbp.h, Stockholm University Press Stockholm, 2021.
  • Zoltan Kacsuk: Using Fan-Compiled Metadata for Anime, Manga and Video Game Research: Revisiting Azuma’s "Otaku: Japan’s Database Animals" Twenty Years On in Japan’s Contemporary Media Culture between Local and Global: Content, Practice and Theory, pp. 117-142, DOI 10.11588/crossasia.971.c12881, CrossAsia-eBooks Heidelberg , Berlin, 2021.

2020

  • Miklós Sebők and Zoltán Kacsuk: The Multiclass Classification of Newspaper Articles with Machine Learning: The Hybrid Binary Snowball Approach in Political Analysis, pp. 1-14, DOI 10.1017/pan.2020.27, Cambridge University Press, 2020.

2018

2017

Name: Zoltán Kacsuk
Email: JAVASCRIPT PROTECTED
Project: Japanese Visual Media Graph
Research topic: Geek and Otaku Culture, Manga and Comics, Text Mining and Machine Learning for the Social Sciences