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Found 6 papers, 3 papers with code
Heuristic Feature Selection for Clickbait Detection
We study feature selection as a means to optimize the baseline clickbait detector employed at the Clickbait Challenge 2017.
Crowdsourcing a Large Corpus of Clickbait on Twitter
To address the urging task of clickbait detection, we constructed a new corpus of 38, 517 annotated Twitter tweets, the Webis Clickbait Corpus 2017.
Celebrity Profiling
Celebrities are among the most prolific users of social media, promoting their personas and rallying followers.
If there's a Trigger Warning, then where's the Trigger? Investigating Trigger Warnings at the Passage Level
Trigger warnings are labels that preface documents with sensitive content if this content could be perceived as harmful by certain groups of readers.
Analyzing Persuasion Strategies of Debaters on Social Media
Existing studies on the analysis of persuasion in online discussions focus on investigating the effectiveness of comments in discussions and ignore the analysis of the effectiveness of debaters over multiple discussions.
Language Models as Context-sensitive Word Search Engines
Context-sensitive word search engines are writing assistants that support word choice, phrasing, and idiomatic language use by indexing large-scale n-gram collections and implementing a wildcard search.
