FinnSentiment: a Finnish social media corpus for sentiment polarity annotation

Abstract

AbstractSentiment analysis and opinion mining are essential tasks with many prominent application areas, e.g., when researching popular opinions on products or brands. Sentiments expressed in social media can be used in brand name monitoring and indicating fake news. In our survey of previous work, we note that there is no large-scale social media data set with sentiment polarity annotations for Finnish. This publication aims to remedy this shortcoming by introducing a 27,000-sentence data set annotated independently with sentiment polarity by three native annotators. We had three annotators annotate the whole data set, which provides a unique opportunity for further studies of annotator behavior over the sample annotation order. We analyze their inter-annotator agreement and provide two baselines to validate the usefulness of the data set.