mlsanityData to 7 Oct 2026

BLP-2023 Task 2: Sentiment Analysis

arXiv 2310.16183 ↗First posted 24 Oct 2023cs.CL cs.LGcited by 7

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Abstract (arXiv)

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, a total of 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 brief 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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 17 of its 52 references that are in the map. First posted on arXiv 24 Oct 2023.

Builds on

17 of 52 references.

References · 17

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  12. 2023Zero- and Few-Shot Prompting with LLMs: A Comparative Study with Fine-tuned Models for Bangla Sentiment Analysiscited by 20
5 more
  1. 2023BanglaBook: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviewscited by 14
  2. 2021A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Modelscited by 13
  3. 2020Sentiment Classification in Bangla Textual Content: A Comparative Studycited by 8
  4. 2023SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and its Evaluationcited by 8
  5. 2023RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using Weighted and Majority Voted Fine-Tuned Transformerscited by 1

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Cited by year

Citing papers per year: 2023: 3; 2024: 3; 2025: 1.

7 papers.