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20172026
most citedAutomatic Detection of Fake News

379 citations · 586 across the 27 of their papers we have counts for

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Showing 2020 · cs.CLShow all

7 papers · 2 filters

cs.CL2020

The Grievance Dictionary: Understanding Threatening Language Use

Isabelle van der Vegt, Maximilian Mozes, Bennett Kleinberg +1

This paper introduces the Grievance Dictionary, a psycholinguistic dictionary which can be used to automatically understand language use in the context of grievance-fuelled violenc…

cs.CL2020★ 4 cited

Too good to be true? Predicting author profiles from abusive language

Isabelle van der Vegt, Bennett Kleinberg, Paul Gill

The problem of online threats and abuse could potentially be mitigated with a computational approach, where sources of abuse are better understood or identified through author prof…

cs.CL2020★ 2 cited

Manipulating emotions for ground truth emotion analysis

Bennett Kleinberg

Text data are being used as a lens through which human cognition can be studied at a large scale. Methods like emotion analysis are now in the standard toolkit of computational soc…

cs.CL2020★ 88 cited

Measuring Emotions in the COVID-19 Real World Worry Dataset

Bennett Kleinberg, Isabelle van der Vegt, Maximilian Mozes

The COVID-19 pandemic is having a dramatic impact on societies and economies around the world. With various measures of lockdowns and social distancing in place, it becomes importa…

cs.CL2020

Women worry about family, men about the economy: Gender differences in emotional responses to COVID-19

Isabelle van der Vegt, Bennett Kleinberg

Among the critical challenges around the COVID-19 pandemic is dealing with the potentially detrimental effects on people's mental health. Designing appropriate interventions and id…

cs.CL2020

Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples

Maximilian Mozes, Pontus Stenetorp, Bennett Kleinberg +1

Recent efforts have shown that neural text processing models are vulnerable to adversarial examples, but the nature of these examples is poorly understood. In this work, we show th…