| Vol-2661 urn:nbn:de:0074-2661-7 Copyright © 2020 for the individual papers by the papers' authors. Copyright © 2020 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# ChAT 2020
Chat Analytics for Twitch 2020

### Proceedings of ECML-PKDD 2020 ChAT Discovery Challenge on Chat Analytics for Twitch
co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2020 (ECML-PKDD 2020)

### Ghent, Belgium (virtual due to Covid-19 pandemic), September 18, 2020.

Edited by

### Konstantin Kobs (1)
Martin Potthast (2)
Albin Zehe (1)
Matti Wiegmann (3)
Benno Stein (3)
Andreas Hotho (1)

(1) Julius-Maximilians Universität Würzburg, Germany
(2) Universität Leipzig, Germany
(3) Bauhaus-Universität Weimar, Germany

## Table of Contents

- Towards Predicting the Subscription Status of Twitch.tv Users - ECML-PKDD ChAT Discovery Challenge 2020
  Konstantin Kobs, Martin Potthast, Matti Wiegmann, Albin Zehe, Benno Stein, Andreas Hotho

### Participant Papers

- Team voyTECH: User Activity Modeling with Boosting Trees
  Immanuel Bayer, Anastasios Zouzias
- Detecting Potential Subscribers on Twitch: A Text Mining Approach with XGBoost - Discovery Challenge ChAT: CoolStoryBob
  Marvin Gärtner, Andreas Theissler, Marc Fernandes
- StinkyCheese: Chat-Based Model for Subscription Classification
  Túlio Corrêa Loures, Gustavo Lúcius Fernandes, Fernanda G. Araújo, Karen S. Martins, Pedro O. S. Vaz-de-Melo

2020-09-01: submitted by Konstantin Kobs, metadata incl. bibliographic data published under Creative Commons CC0
2020-09-02: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|