@inproceedings{chakravarthi-etal-2023-exploring,
title = "Exploring Techniques to Detect and Mitigate Non-Inclusive Language Bias in Marketing Communications Using a Dictionary-Based Approach",
author = "Chakravarthi, Bharathi Raja and
Kumaresan, Prasanna Kumar and
Ponnusamy, Rahul and
McCrae, John P. and
Comerford, Michaela and
Megaro, Jay and
Keles, Deniz and
Feremenga, Last",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.ranlp-1.99",
pages = "918--925",
abstract = "We propose a new dataset for detecting non-inclusive language in sentences in English. These sentences were gathered from public sites, explaining what is inclusive and what is non-inclusive. We also extracted potentially non-inclusive keywords/phrases from the guidelines from business websites. A phrase dictionary was created by using an automatic extension with a word embedding trained on a massive corpus of general English text. In the end, a phrase dictionary was constructed by hand-editing the previous one to exclude inappropriate expansions and add the keywords from the guidelines. In a business context, the words individuals use can significantly impact the culture of inclusion and the quality of interactions with clients and prospects. Knowing the right words to avoid helps customers of different backgrounds and historically excluded groups feel included. They can make it easier to have productive, engaging, and positive communications. You can find the dictionaries, the code, and the method for making requests for the corpus at (we will release the link for data and code once the paper is accepted).",
}
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%0 Conference Proceedings
%T Exploring Techniques to Detect and Mitigate Non-Inclusive Language Bias in Marketing Communications Using a Dictionary-Based Approach
%A Chakravarthi, Bharathi Raja
%A Kumaresan, Prasanna Kumar
%A Ponnusamy, Rahul
%A McCrae, John P.
%A Comerford, Michaela
%A Megaro, Jay
%A Keles, Deniz
%A Feremenga, Last
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F chakravarthi-etal-2023-exploring
%X We propose a new dataset for detecting non-inclusive language in sentences in English. These sentences were gathered from public sites, explaining what is inclusive and what is non-inclusive. We also extracted potentially non-inclusive keywords/phrases from the guidelines from business websites. A phrase dictionary was created by using an automatic extension with a word embedding trained on a massive corpus of general English text. In the end, a phrase dictionary was constructed by hand-editing the previous one to exclude inappropriate expansions and add the keywords from the guidelines. In a business context, the words individuals use can significantly impact the culture of inclusion and the quality of interactions with clients and prospects. Knowing the right words to avoid helps customers of different backgrounds and historically excluded groups feel included. They can make it easier to have productive, engaging, and positive communications. You can find the dictionaries, the code, and the method for making requests for the corpus at (we will release the link for data and code once the paper is accepted).
%U https://aclanthology.org/2023.ranlp-1.99
%P 918-925
Markdown (Informal)
[Exploring Techniques to Detect and Mitigate Non-Inclusive Language Bias in Marketing Communications Using a Dictionary-Based Approach](https://aclanthology.org/2023.ranlp-1.99) (Chakravarthi et al., RANLP 2023)
ACL
- Bharathi Raja Chakravarthi, Prasanna Kumar Kumaresan, Rahul Ponnusamy, John P. McCrae, Michaela Comerford, Jay Megaro, Deniz Keles, and Last Feremenga. 2023. Exploring Techniques to Detect and Mitigate Non-Inclusive Language Bias in Marketing Communications Using a Dictionary-Based Approach. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 918–925, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.