@inproceedings{hasan-etal-2023-blp,
title = "{BLP}-2023 Task 2: Sentiment Analysis",
author = "Hasan, Md. Arid and
Alam, Firoj and
Anjum, Anika and
Das, Shudipta and
Anjum, Afiyat",
editor = "Alam, Firoj and
Kar, Sudipta and
Chowdhury, Shammur Absar and
Sadeque, Farig and
Amin, Ruhul",
booktitle = "Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.banglalp-1.48",
doi = "10.18653/v1/2023.banglalp-1.48",
pages = "354--364",
abstract = "We present an overview of the BLP Sentiment Shared Task, organized as part of the inaugural BLP 2023 workshop, co-located with EMNLP 2023. The task is defined as the detection of sentiment in a given piece of social media text. This task attracted interest from 71 participants, among whom 29 and 30 teams submitted systems during the development and evaluation phases, respectively. In total, participants submitted 597 runs. However, only 15 teams submitted system description papers. The range of approaches in the submitted systems spans from classical machine learning models, fine-tuning pre-trained models, to leveraging Large Language Model (LLMs) in zero- and few-shot settings. In this paper, we provide a detailed account of the task setup, including dataset development and evaluation setup. Additionally, we provide a succinct overview of the systems submitted by the participants. All datasets and evaluation scripts from the shared task have been made publicly available for the research community, to foster further research in this domain.",
}
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<abstract>We present an overview of the BLP Sentiment Shared Task, organized as part of the inaugural BLP 2023 workshop, co-located with EMNLP 2023. The task is defined as the detection of sentiment in a given piece of social media text. This task attracted interest from 71 participants, among whom 29 and 30 teams submitted systems during the development and evaluation phases, respectively. In total, participants submitted 597 runs. However, only 15 teams submitted system description papers. The range of approaches in the submitted systems spans from classical machine learning models, fine-tuning pre-trained models, to leveraging Large Language Model (LLMs) in zero- and few-shot settings. In this paper, we provide a detailed account of the task setup, including dataset development and evaluation setup. Additionally, we provide a succinct overview of the systems submitted by the participants. All datasets and evaluation scripts from the shared task have been made publicly available for the research community, to foster further research in this domain.</abstract>
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%0 Conference Proceedings
%T BLP-2023 Task 2: Sentiment Analysis
%A Hasan, Md. Arid
%A Alam, Firoj
%A Anjum, Anika
%A Das, Shudipta
%A Anjum, Afiyat
%Y Alam, Firoj
%Y Kar, Sudipta
%Y Chowdhury, Shammur Absar
%Y Sadeque, Farig
%Y Amin, Ruhul
%S Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F hasan-etal-2023-blp
%X We present an overview of the BLP Sentiment Shared Task, organized as part of the inaugural BLP 2023 workshop, co-located with EMNLP 2023. The task is defined as the detection of sentiment in a given piece of social media text. This task attracted interest from 71 participants, among whom 29 and 30 teams submitted systems during the development and evaluation phases, respectively. In total, participants submitted 597 runs. However, only 15 teams submitted system description papers. The range of approaches in the submitted systems spans from classical machine learning models, fine-tuning pre-trained models, to leveraging Large Language Model (LLMs) in zero- and few-shot settings. In this paper, we provide a detailed account of the task setup, including dataset development and evaluation setup. Additionally, we provide a succinct overview of the systems submitted by the participants. All datasets and evaluation scripts from the shared task have been made publicly available for the research community, to foster further research in this domain.
%R 10.18653/v1/2023.banglalp-1.48
%U https://aclanthology.org/2023.banglalp-1.48
%U https://doi.org/10.18653/v1/2023.banglalp-1.48
%P 354-364
Markdown (Informal)
[BLP-2023 Task 2: Sentiment Analysis](https://aclanthology.org/2023.banglalp-1.48) (Hasan et al., BanglaLP 2023)
ACL
- Md. Arid Hasan, Firoj Alam, Anika Anjum, Shudipta Das, and Afiyat Anjum. 2023. BLP-2023 Task 2: Sentiment Analysis. In Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pages 354–364, Singapore. Association for Computational Linguistics.