126 citations · 304 across the 10 of their papers we have counts for
5 papers · 1 filter
The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength
Martin Potthast, Tim Gollub, Matthias Hagen +1
Clickbait has grown to become a nuisance to social media users and social media operators alike. Malicious content publishers misuse social media to manipulate as many users as pos…
Wikipedia Text Reuse: Within and Without
Milad Alshomary, Michael Völske, Tristan Licht +4
We study text reuse related to Wikipedia at scale by compiling the first corpus of text reuse cases within Wikipedia as well as without (i.e., reuse of Wikipedia text in a sample o…
Safe Stream-Based Programming with Refinement Types
Benno Stein, Lazaro Clapp, Manu Sridharan +1
In stream-based programming, data sources are abstracted as a stream of values that can be manipulated via callback functions. Stream-based programming is exploding in popularity,…
Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation
Ivan Habernal, Henning Wachsmuth, Iryna Gurevych +1
Arguing without committing a fallacy is one of the main requirements of an ideal debate. But even when debating rules are strictly enforced and fallacious arguments punished, argue…
Heuristic Feature Selection for Clickbait Detection
Matti Wiegmann, Michael Völske, Benno Stein +2
We study feature selection as a means to optimize the baseline clickbait detector employed at the Clickbait Challenge 2017. The challenge's task is to score the "clickbaitiness" of…