We introduce FinLin, a novel corpus containing investor reports, company reports, news articles, and microblogs from StockTwits, targeting multiple entities stemming from the automobile industry and covering a 3-month period. FinLin was annotated with a sentiment score and a relevance score in the range [-1.0, 1.0] and [0.0, 1.0], respectively. The annotations also include the text spans selected for the sentiment, thus, providing additional insight into the annotators' reasoning. Overall, FinLin aims to complement the current knowledge by providing a novel and publicly available financial sentiment corpus and to foster research on the topic of financial sentiment analysis and potential applications in behavioural science.
@article{arxiv.2003.04073,
title = {A Multi-Source Entity-Level Sentiment Corpus for the Financial Domain: The FinLin Corpus},
author = {Tobias Daudert},
journal= {arXiv preprint arXiv:2003.04073},
year = {2020}
}