Bambara Language Dataset for Sentiment Analysis

本研究介绍了首个基于Common Crawl的Bambara语言情感分析数据集，由iCompass创建。该数据集包含3046条句子，主要来源于西非地区，特别是马里，用于分析当地社交媒体用户的情感表达。数据集的创建过程包括数据收集、预处理和手动情感标注，确保了数据的质量和代表性。该数据集旨在支持机器学习和深度学习模型在非洲语言情感分析领域的应用，解决非洲语言在自然语言处理研究中的代表性不足问题。

This study introduces the first Bambara language sentiment analysis dataset based on Common Crawl, created by iCompass. Comprising 3,046 sentences primarily sourced from West Africa, particularly Mali, this dataset is designed for analyzing sentiment expressions of local social media users. The dataset's creation process includes data collection, preprocessing, and manual sentiment annotation, ensuring its data quality and representativeness. This dataset aims to support the application of machine learning and deep learning models in the field of African language sentiment analysis, addressing the underrepresentation issue of African languages in natural language processing research.