Financial Sentiment Analysis (FSA) is an important domain application of sentiment analysis
that has gained increasing attention in the past decade. FSA research falls into two main …

Recently, ChatGPT has drawn great attention from both the research community and the
public. We are particularly interested in whether it can serve as a universal sentiment …

Large language models (LLMs) have drastically changed the possible ways to design
intelligent systems, shifting the focus from massive data acquisition and new model training …

Machine learning (ML) has transformed the financial industry by enabling advanced
applications such as credit scoring, fraud detection, and market forecasting. At the core of …

The recent COVID-19 pandemic represents an unprecedented worldwide event to study the
influence of related news on the financial markets, especially during the early stage of the …

The increasing interest around emotions in online texts creates the demand for financial
sentiment analysis. Previous studies mainly focus on coarse-grained document-/sentence …

This survey presents an in-depth review of the transformative role of Natural Language
Processing (NLP) in finance, highlighting its impact on ten major financial applications:(1) …

Financial market predictions utilize historical data to anticipate future stock prices and
market trends. Traditionally, these predictions have focused on the statistical analysis of …

Sentiment lexicons are important tools for research involving opinion mining and sentiment
analysis. They are highly inter-operable, and address critical limitations of learning-based or …

In the financial domain, conducting entity-level sentiment analysis is crucial for accurately
assessing the sentiment directed toward a specific financial entity. To our knowledge, no …