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Potthast et al., 2018 - Google Patents

Crowdsourcing a large corpus of clickbait on twitter

Potthast et al., 2018

View PDF
Document ID
1800665317935561867
Author
Potthast M
Gollub T
Komlossy K
Schuster S
Wiegmann M
Fernandez E
Hagen M
Stein B
Publication year
Publication venue
Proceedings of the 27th international conference on computational linguistics

External Links

Snippet

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 …
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    • G06F17/30864Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
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