sentimentdata
Sentimentdata refers to datasets that contain texts paired with sentiment labels, created to support the development and evaluation of sentiment analysis systems. These datasets are used to train machine learning models to classify or quantify the emotional tone of text, such as positive, negative, or neutral judgments, and sometimes to assign more granular scores.
Typical content and structure include raw text samples (for example product reviews, social media posts, or
Collection and annotation are central to sentimentdata. Data are drawn from publicly available sources or licensed
Uses and applications include training sentiment classifiers, benchmarking algorithms, cross-domain evaluation, and sentiment-aware content filtering. Ethical
Notable examples commonly referenced in the field include IMDb movie reviews, the Stanford Sentiment Treebank, Yelp