OffensiveLang: A Community-Based Implicit Offensive Language Dataset
The widespread presence of hateful languages on social media has resulted in adverse effects on societal well-being. As a result, addressing this issue with high priority has become very important. Hate speech or offensive languages exist in both explicit and implicit forms, with the latter being mo...
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IEEE
2024-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10786820/ |
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| author | Amit Das Mostafa Rahgouy Dongji Feng Zheng Zhang Tathagata Bhattacharya Nilanjana Raychawdhary Fatemeh Jamshidi Vinija Jain Aman Chadha Mary J. Sandage Lauramarie Pope Gerry V. Dozier Cheryl D. Seals |
| author_facet | Amit Das Mostafa Rahgouy Dongji Feng Zheng Zhang Tathagata Bhattacharya Nilanjana Raychawdhary Fatemeh Jamshidi Vinija Jain Aman Chadha Mary J. Sandage Lauramarie Pope Gerry V. Dozier Cheryl D. Seals |
| author_sort | Amit Das |
| collection | DOAJ |
| description | The widespread presence of hateful languages on social media has resulted in adverse effects on societal well-being. As a result, addressing this issue with high priority has become very important. Hate speech or offensive languages exist in both explicit and implicit forms, with the latter being more challenging to detect. Current research in this domain encounters several challenges. Firstly, the existing datasets primarily rely on the collection of texts containing explicit offensive keywords, making it challenging to capture implicitly offensive contents that are devoid of these keywords. Secondly, common methodologies tend to focus solely on textual analysis, neglecting the valuable insights that community information can provide. In this research paper, we introduce a novel dataset OffensiveLang, a community based implicit offensive language dataset generated by ChatGPT 3.5 containing data for 38 different target groups. Despite limitations in generating offensive texts using ChatGPT due to ethical constraints, we present a prompt-based approach that effectively generates implicit offensive languages. To ensure data quality, we evaluate the dataset with human. Additionally, we employ a prompt-based zero-shot method with ChatGPT and compare the detection results between human annotation and ChatGPT annotation. We utilize existing state-of-the-art models to see how effective they are in detecting such languages. The dataset is available here: <uri>https://github.com/AmitDasRup123/OffensiveLang</uri>. |
| format | Article |
| id | doaj-art-0bbc26f692444ce0a5384da1f3b7262e |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-0bbc26f692444ce0a5384da1f3b7262e2025-08-20T02:50:41ZengIEEEIEEE Access2169-35362024-01-011218566118567210.1109/ACCESS.2024.351322010786820OffensiveLang: A Community-Based Implicit Offensive Language DatasetAmit Das0https://orcid.org/0000-0003-4190-3903Mostafa Rahgouy1Dongji Feng2Zheng Zhang3https://orcid.org/0000-0003-1707-624XTathagata Bhattacharya4Nilanjana Raychawdhary5https://orcid.org/0009-0006-8479-1971Fatemeh Jamshidi6Vinija Jain7Aman Chadha8https://orcid.org/0000-0001-6621-9003Mary J. Sandage9Lauramarie Pope10Gerry V. Dozier11Cheryl D. Seals12University of North Alabama, Florence, AL, USAAuburn University, Auburn, AL, USAGustavus Adolphus College, Saint Peter, MN, USAMurray State University, Murray, KY, USAAuburn University at Montgomery, Montgomery, AL, USAAuburn University, Auburn, AL, USACalifornia State Polytechnic University at Pomona, Pomona, CA, USAStanford University, Stanford, CA, USAStanford University, Stanford, CA, USAAuburn University, Auburn, AL, USAAuburn University, Auburn, AL, USAAuburn University, Auburn, AL, USAAuburn University, Auburn, AL, USAThe widespread presence of hateful languages on social media has resulted in adverse effects on societal well-being. As a result, addressing this issue with high priority has become very important. Hate speech or offensive languages exist in both explicit and implicit forms, with the latter being more challenging to detect. Current research in this domain encounters several challenges. Firstly, the existing datasets primarily rely on the collection of texts containing explicit offensive keywords, making it challenging to capture implicitly offensive contents that are devoid of these keywords. Secondly, common methodologies tend to focus solely on textual analysis, neglecting the valuable insights that community information can provide. In this research paper, we introduce a novel dataset OffensiveLang, a community based implicit offensive language dataset generated by ChatGPT 3.5 containing data for 38 different target groups. Despite limitations in generating offensive texts using ChatGPT due to ethical constraints, we present a prompt-based approach that effectively generates implicit offensive languages. To ensure data quality, we evaluate the dataset with human. Additionally, we employ a prompt-based zero-shot method with ChatGPT and compare the detection results between human annotation and ChatGPT annotation. We utilize existing state-of-the-art models to see how effective they are in detecting such languages. The dataset is available here: <uri>https://github.com/AmitDasRup123/OffensiveLang</uri>.https://ieeexplore.ieee.org/document/10786820/Offensive languageChatGPTlarge language modelprompt engineering |
| spellingShingle | Amit Das Mostafa Rahgouy Dongji Feng Zheng Zhang Tathagata Bhattacharya Nilanjana Raychawdhary Fatemeh Jamshidi Vinija Jain Aman Chadha Mary J. Sandage Lauramarie Pope Gerry V. Dozier Cheryl D. Seals OffensiveLang: A Community-Based Implicit Offensive Language Dataset IEEE Access Offensive language ChatGPT large language model prompt engineering |
| title | OffensiveLang: A Community-Based Implicit Offensive Language Dataset |
| title_full | OffensiveLang: A Community-Based Implicit Offensive Language Dataset |
| title_fullStr | OffensiveLang: A Community-Based Implicit Offensive Language Dataset |
| title_full_unstemmed | OffensiveLang: A Community-Based Implicit Offensive Language Dataset |
| title_short | OffensiveLang: A Community-Based Implicit Offensive Language Dataset |
| title_sort | offensivelang a community based implicit offensive language dataset |
| topic | Offensive language ChatGPT large language model prompt engineering |
| url | https://ieeexplore.ieee.org/document/10786820/ |
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