Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment

By Kevin Munger. 2017

317 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Communication, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/d339b6ecd08aee99dcda85400250f96dc7515581

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Citations in the corpus

The Psychology of Fake News. (2021, background): “More so than many other domains, when studying fake news and misinformation it is often possible to combine traditional laboratory experiments with large-scale social media data [71,109] – or even to conduct actual field experiments on-platform [21,110,111].”
Generating Counter Narratives against Online Hate Speech: Data and Strategies (2020, methodology): “Several CN methods to counter hatred are outlined and tested by Benesch (2014), Munger (2017), and Mathew et al. (2019).”
Community Interaction and Conflict on the Web (2018, background): “forms has focused primarily on controversies [3, 13, 20, 21, 45, 52] and anti-social behavior, in the form of trolling [11, 12, 42], sockpuppetry [39], harassment and cyberbullying [8, 23, 32, 35, 55, 66, 79], vandalism [43], hate speech [9, 15, 51, 56, 72], and others [17, 24, 40, 41, 44, 46, 54, 6”
A Just and Comprehensive Strategy for Using NLP to Address Online Abuse (2019, background): “Munger (2017) developed a simple, but effective, computational intervention for the use of toxic language (the n-word), where a human-looking bot account would reply with a ﬁxed comment about the harm such language caused and an appeal to empathy, leading to long-term behavior change in the…”
Thou shalt not hate: Countering Online Hate Speech (2018, methodology): “The BoWV approach uses the average of the GloVe (Pennington, Socher, and Manning 2014) word embeddings to represent a sentence.”
The MAD Model of Moral Contagion: The Role of Motivation, Attention, and Design in the Spread of Moralized Content Online (2019, background): “For instance, a field study on Twitter found that criticism via direct messages from the in-group, but not the out-group, reduced people’s use of racial slurs in online communications (Munger, 2017).”
CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech (2019, background): “Still, manual intervention against hate speech is a toil of Sisyphus, and automatizing the countering procedure would increase the efficacy and effectiveness of hate countering (Munger, 2017).”