The growth of financial texts in the wake of big data has challenged most organizations and brought escalating demands for analysis tools. In general, text streams are more challenging to handle than numeric data streams. Text streams are unstructured by nature, but they represent collective expressions that are of value in any financial decision. Sentiment analysis has turned out to be a complicated and strongly domain dependent task. For this task there are so many statistical and Pre-trained NLP models exist. In this paper we experimented with such existed and our proposed approach in statistical modelling.
sentiment-classification-over-financial-text's Introduction
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