Papers by Anna Feldman
NollySenti: Leveraging Transfer Learning and Machine Translation for Nigerian Movie Sentiment Classification (2023.acl-short)
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| Challenge: | Africa has over 2000 indigenous languages but they are under-represented in NLP research due to lack of datasets. |
| Approach: | They propose to use a dataset to classify sentiments for cross-domain adaptation for Nigerian and other African languages. |
| Outcome: | The proposed dataset compares the performance of cross-domain adaptation from Twitter domain and cross-lingual adaptation from English domain. |
Designing a Russian Idiom-Annotated Corpus (L18-1)
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| Challenge: | a pilot experiment using the idiom-annotated corpus of Russian is described . corpora that could be used for training idiomatic classifiers are scarce, especially if one turns to other languages. |
| Approach: | They describe the development of an idiom-annotated corpus of Russian . the corpus is compiled from freely available online resources . |
| Outcome: | The proposed corpus is based on an online corpus of Russian texts . it is available for research purposes and can be used for linguistic studies and pedagogy . |
FEED PETs: Further Experimentation and Expansion on the Disambiguation of Potentially Euphemistic Terms (2023.starsem-1)
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Patrick Lee, Iyanuoluwa Shode, Alain Trujillo, Yuan Zhao, Olumide Ojo, Diana Plancarte, Anna Feldman, Jing Peng
| Challenge: | Existing work on euphemism disambiguation tasks has focused on transformers . euphorias are expressions that soften the message they convey, therefore dictionary-based approaches are ineffective . |
| Approach: | They propose to annotate PETs for vagueness and use transformers to classify PETs . they perform euphemism disambiguation experiments in three different languages . |
| Outcome: | The proposed models perform well in English euphemism disambiguation task . preliminary results will be used to launch future work . |
CATs are Fuzzy PETs: A Corpus and Analysis of Potentially Euphemistic Terms (2022.lrec-1)
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| Challenge: | Euphemisms are a difficult topic because they are subject to language change and humans may not agree on what is a euphemist. |
| Approach: | They analyze a corpus of potentially euphemistic terms (PETs) and examples from the GloWbE corpus to examine their meanings. |
| Outcome: | The proposed corpus of potentially euphemistic terms and examples from the GloWbE corpus show that PETs generally decrease negative and offensive sentiment. |
MEDs for PETs: Multilingual Euphemism Disambiguation for Potentially Euphemistic Terms (2024.findings-eacl)
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Patrick Lee, Alain Chirino Trujillo, Diana Cuevas Plancarte, Olumide Ojo, Xinyi Liu, Iyanuoluwa Shode, Yuan Zhao, Anna Feldman, Jing Peng
| Challenge: | Euphemisms are a linguistic device used to soften or neutralize language that may otherwise be harsh or awkward to state directly. |
| Approach: | They train a multilingual transformer model to disambiguate potentially euphemistic terms in multilingual and cross-lingual settings. |
| Outcome: | The proposed model performs better than monolingual models on the disambiguation task compared to monolingual ones in multilingual and cross-lingual settings. |