Tim Gollub


2018

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Crowdsourcing a Large Corpus of Clickbait on Twitter
Martin Potthast | Tim Gollub | Kristof Komlossy | Sebastian Schuster | Matti Wiegmann | Erika Patricia Garces Fernandez | Matthias Hagen | Benno Stein
Proceedings of the 27th International Conference on Computational Linguistics

Clickbait has become a nuisance on social media. To address the urging task of clickbait detection, we constructed a new corpus of 38,517 annotated Twitter tweets, the Webis Clickbait Corpus 2017. To avoid biases in terms of publisher and topic, tweets were sampled from the top 27 most retweeted news publishers, covering a period of 150 days. Each tweet has been annotated on 4-point scale by five annotators recruited at Amazon’s Mechanical Turk. The corpus has been employed to evaluate 12 clickbait detectors submitted to the Clickbait Challenge 2017. Download: https://webis.de/data/webis-clickbait-17.html Challenge: https://clickbait-challenge.org

2012

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The Impact of Spelling Errors on Patent Search
Benno Stein | Dennis Hoppe | Tim Gollub
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics