TY - GEN
T1 - CATs are Fuzzy PETs
T2 - 13th International Conference on Language Resources and Evaluation Conference, LREC 2022
AU - Gavidia, Martha
AU - Lee, Patrick
AU - Feldman, Anna
AU - Peng, Jing
N1 - Funding Information:
We thank our annotators Raz Besaleli, Kira Horiuchi, Kelly Ortega, and Kenna Reagan for their time and attention to our corpus annotation task as well as Brad McNamee and Avery Field for their contributions to our PETs dataset. This material is based upon work supported by the National Science Foundation under Grant No. 1704113.
Publisher Copyright:
© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
PY - 2022
Y1 - 2022
N2 - Euphemisms have not received much attention in natural language processing, despite being an important element of polite and figurative language. Euphemisms prove to be a difficult topic, not only because they are subject to language change, but also because humans may not agree on what is a euphemism and what is not. Nonetheless, the first step to tackling the issue is to collect and analyze examples of euphemisms. We present a corpus of potentially euphemistic terms (PETs) along with example texts from the GloWbE corpus. Additionally, we present a subcorpus of texts where these PETs are not being used euphemistically, which may be useful for future applications. We also discuss the results of multiple analyses run on the corpus. Firstly, we find that sentiment analysis on the euphemistic texts supports that PETs generally decrease negative and offensive sentiment. Secondly, we observe cases of disagreement in an annotation task, where humans are asked to label PETs as euphemistic or not in a subset of our corpus text examples. We attribute the disagreement to a variety of potential reasons, including if the PET was a commonly accepted term (CAT).
AB - Euphemisms have not received much attention in natural language processing, despite being an important element of polite and figurative language. Euphemisms prove to be a difficult topic, not only because they are subject to language change, but also because humans may not agree on what is a euphemism and what is not. Nonetheless, the first step to tackling the issue is to collect and analyze examples of euphemisms. We present a corpus of potentially euphemistic terms (PETs) along with example texts from the GloWbE corpus. Additionally, we present a subcorpus of texts where these PETs are not being used euphemistically, which may be useful for future applications. We also discuss the results of multiple analyses run on the corpus. Firstly, we find that sentiment analysis on the euphemistic texts supports that PETs generally decrease negative and offensive sentiment. Secondly, we observe cases of disagreement in an annotation task, where humans are asked to label PETs as euphemistic or not in a subset of our corpus text examples. We attribute the disagreement to a variety of potential reasons, including if the PET was a commonly accepted term (CAT).
KW - euphemisms
KW - NLP
KW - politeness
UR - http://www.scopus.com/inward/record.url?scp=85144433382&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85144433382
T3 - 2022 Language Resources and Evaluation Conference, LREC 2022
SP - 2658
EP - 2671
BT - 2022 Language Resources and Evaluation Conference, LREC 2022
A2 - Calzolari, Nicoletta
A2 - Bechet, Frederic
A2 - Blache, Philippe
A2 - Choukri, Khalid
A2 - Cieri, Christopher
A2 - Declerck, Thierry
A2 - Goggi, Sara
A2 - Isahara, Hitoshi
A2 - Maegaard, Bente
A2 - Mariani, Joseph
A2 - Mazo, Helene
A2 - Odijk, Jan
A2 - Piperidis, Stelios
PB - European Language Resources Association (ELRA)
Y2 - 20 June 2022 through 25 June 2022
ER -