Rating Offensive Words in Three Television Program Contexts

By Barry Sapolsky, Daniel M. Shafer, Barbara K. Kaye. 2010

26 citations recorded by the source corpus.

Subfields: Communication, Social Psychology, Sentiment & Opinion Analysis

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

1. Klint Qinami
2. Xuhui Zhou
3. Noah A. Smith
4. Jia Deng
5. Yejin Choi
6. Laura Vianna
7. Olga Russakovsky
8. Swabha Swayamdipta

In Social Psychology

1. Yejin Choi
2. Noah A. Smith
3. Jia Deng
4. Maarten Sap
5. Li Fei-Fei

In Sentiment & Opinion Analysis

1. Klint Qinami
2. Jia Deng
3. Yejin Choi
4. Olga Russakovsky
5. Kaiyu Yang
6. Li Fei-Fei

Citations in the corpus

• Towards fairer datasets: filtering and balancing the distribution of the people subtree in the ImageNet hierarchy (2019, background): “[66] rate the ofensiveness of words in TV programs.”
• Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection (2021, background): “Given that vulgarity can be considered noncanonical or impolite language (Jay and Janschewitz, 2008; Sapolsky et al., 2010; DeFrank and Kahlbaugh, 2019), we hypothesize that annotators who score high on LINGPURISM, TRADITIONALISM, and who are more conservative will rate vulgar posts as more offensiv”
• A New ANEW: Evaluation of a Word List for Sentiment Analysis in Microblogs (2011, background): “The word list initiated from a set of obscene words [7, 8] as well as a few positive words.”