@inproceedings{merullo-etal-2019-investigating,
title = "Investigating Sports Commentator Bias within a Large Corpus of {A}merican Football Broadcasts",
author = "Merullo, Jack and
Yeh, Luke and
Handler, Abram and
Grissom II, Alvin and
O{'}Connor, Brendan and
Iyyer, Mohit",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1666",
doi = "10.18653/v1/D19-1666",
pages = "6355--6361",
abstract = "Sports broadcasters inject drama into play-by-play commentary by building team and player narratives through subjective analyses and anecdotes. Prior studies based on small datasets and manual coding show that such theatrics evince commentator bias in sports broadcasts. To examine this phenomenon, we assemble FOOTBALL, which contains 1,455 broadcast transcripts from American football games across six decades that are automatically annotated with 250K player mentions and linked with racial metadata. We identify major confounding factors for researchers examining racial bias in FOOTBALL, and perform a computational analysis that supports conclusions from prior social science studies.",
}
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<abstract>Sports broadcasters inject drama into play-by-play commentary by building team and player narratives through subjective analyses and anecdotes. Prior studies based on small datasets and manual coding show that such theatrics evince commentator bias in sports broadcasts. To examine this phenomenon, we assemble FOOTBALL, which contains 1,455 broadcast transcripts from American football games across six decades that are automatically annotated with 250K player mentions and linked with racial metadata. We identify major confounding factors for researchers examining racial bias in FOOTBALL, and perform a computational analysis that supports conclusions from prior social science studies.</abstract>
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%0 Conference Proceedings
%T Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts
%A Merullo, Jack
%A Yeh, Luke
%A Handler, Abram
%A Grissom II, Alvin
%A O’Connor, Brendan
%A Iyyer, Mohit
%Y Inui, Kentaro
%Y Jiang, Jing
%Y Ng, Vincent
%Y Wan, Xiaojun
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F merullo-etal-2019-investigating
%X Sports broadcasters inject drama into play-by-play commentary by building team and player narratives through subjective analyses and anecdotes. Prior studies based on small datasets and manual coding show that such theatrics evince commentator bias in sports broadcasts. To examine this phenomenon, we assemble FOOTBALL, which contains 1,455 broadcast transcripts from American football games across six decades that are automatically annotated with 250K player mentions and linked with racial metadata. We identify major confounding factors for researchers examining racial bias in FOOTBALL, and perform a computational analysis that supports conclusions from prior social science studies.
%R 10.18653/v1/D19-1666
%U https://aclanthology.org/D19-1666
%U https://doi.org/10.18653/v1/D19-1666
%P 6355-6361
Markdown (Informal)
[Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts](https://aclanthology.org/D19-1666) (Merullo et al., EMNLP-IJCNLP 2019)
ACL