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In this paper, we propose an approach for the detection of clickbait posts in online social media (OSM).
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J. Song, S. Lee, and J. Kim · 2015
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P. Biyani, K. Tsioutsiouliklis, and J. Blackmer · 2016
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Stop clickbait: Detecting and preventing clickbaits in online news media
A. Chakraborty, B. Paranjape, S. Kakarla, and N. Ganguly · 2016
https://www.scoopwhoop.com/
Scoopwhoop website · 2017
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http://www.thesaurus.com/
Thesaurus website · 2017
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https://support.twitter.com/articles/166337
The twitter glossary · 2017
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http://www.viralnova.com/
Viralnova website · 2017
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http://viralstories.in/
Viralstories website · 2017
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https://wordnet.princeton.edu/4
Wordnet website · 2017
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A. Chakraborty, R. Sarkar, A. Mrigen, and N. Ganguly · 2017
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Botornot: A system to evaluate social bots
C. A. Davis, O. Varol, E. Ferrara, A. Flammini, and F. Menczer · 2016
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The advantage of simple paper abstracts
A. Letchford, T. Preis, and H. S. Moat · 2016
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https://www.buzzfeed.com/
Buzzfeed website · 2017
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https://translate.google.com/
Google translate website · 2017
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https://pypi.python.org/pypi/PyDictionary/1.3.4
Pydictionary 1.3.4 · 2017
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https://pypi.python.org/pypi/pytesseract
Pytesseract · 2017
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A. Elyashar, J. Bendahan, R. Puzis, and M.-A. Sanmateu · 2017
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B. D. Horne and S. Adali · 2017
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The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength
M. Potthast, T. Gollub, M. Hagen, and B. Stein · 2017
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Some like it hoax: Automated fake news detection in social networks
E. Tacchini, G. Ballarin, M. L. Della Vedova, S. Moret, and L. de Alfaro · 2017
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Clickbait: Fake news and role of the state
E. E. G. Tan and B. Ang · 2017
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