地球资源数据云——数据资源详情
YouTube 上的孟加拉语数据集政治评论 |NLP
该数据集《Bangla Dataset on Youtube Political Comments |NLP》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：YouTube Comments on Political News in Bangladesh for Sentiment analysis/NLP Task 任务类型：文本多分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：bangla_political_comments.csv。 This dataset consists of YouTube comments predominantly collected from political news videos relevant to Bangladesh. The comments are written in Bengali, enriched with emojis that express a range of emotions and opinions. These comments provide unique insights into the public sentiment and reactions related to political events, figures, and policies within the country. This dataset can be highly useful for NLP tasks such as sentiment analysis, emotion detection, and opinion mining. It enables researchers to study public sentiment, emotional expression, and political opinions through text and emojis in Bengali. Key Features: Language: The comments are in Bengali, reflecting authentic language use with local expressions and cultural nuances.
摘要概览
该数据集《Bangla Dataset on Youtube Political Comments |NLP》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：YouTube Comments on Political News in Bangladesh for Sentiment analysis/NLP Task
任务类型：文本多分类。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：bangla_political_comments.csv。
This dataset consists of YouTube comments predominantly collected from political news videos relevant to Bangladesh. The comments are written in Bengali, enriched with emojis that express a range of emotions and opinions.
These comments provide unique insights into the public sentiment and reactions related to political events, figures, and policies within the country. This dataset can be highly useful for NLP tasks such as sentiment analysis, emotion detection, and opinion mining.
It enables researchers to study public sentiment, emotional expression, and political opinions through text and emojis in Bengali.
Key Features:
Language: The comments are in Bengali, reflecting authentic language use with local expressions and cultural nuances.