Detecting Hate, Offensive, and Regular Speech in Short Comments

Almeida, Thais Oliveira; Souza, Bruno Á.; Nakamura, Fabíola G.; Nakamura, Eduardo F.

doi:10.1145/3126858.3131576

Cited by 10 publications

(1 citation statement)

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“…We validated the classifiers against held-out, labeled data in 10-fold cross-validation and obtained an average accuracy of 79% across all the categories. Details on the intercoder agreement and the predictive performance are provided in Table 4 and 5 The classifier and the annotated data set on offensiveness have been validated in subsequent studies (Almeida, Souza, Nakamura, & Nakamura, 2017;Olteanu, Talamadupula, & Varshney, 2017).…”

Section: Validationmentioning

confidence: 99%

Brevity is the Soul of Twitter: The Constraint Affordance and Political Discussion

Jaidka

Zhou

Lelkes

2019

Journal of Communication

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Many hoped that social networking sites would allow for the open exchange of information and a revival of the public sphere. Unfortunately, conversations on social media are often toxic and not conducive to healthy political discussions. Twitter, the most widely used social network for political discussions, doubled the limit of characters in a tweet in November 2017, which provided an opportunity to study the effect of technological affordances on political discussions using a discontinuous time series design. Using supervised and unsupervised natural language processing methods, we analyzed 358,242 tweet replies to U.S. politicians from January 2017 to March 2018. We show that doubling the permissible length of a tweet led to less uncivil, more polite, and more constructive discussions online. However, the declining trend in the empathy and respectfulness of these tweets raises concerns about the implications of the changing norms for the quality of political deliberation.

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Section: Validationmentioning

confidence: 99%