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 …

Social media popularity and importance is on the increase due to people using it for various
types of social interaction across multiple channels. This systematic review focuses on the …

Predicting stock price movements is a challenging task. Previous studies mostly used
numerical features and news sentiments of target stocks to predict stock price movements …

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 …

Real-time market prediction tool tracking public opinion in specialized newsgroups and
informative market data persuades investors of financial markets. Previous works mainly …

Classification systems are evaluated in a countless number of papers. However, we find that
evaluation practice is often nebulous. Frequently, metrics are selected without arguments …

While state-of-the-art NLP models have been achieving the excellent performance of a wide
range of tasks in recent years, important questions are being raised about their robustness …

Understanding word-level emotion in terms of both category and intensity has always been
considered an essential step in addressing text emotion classification tasks. Existing studies …

Metaphors are figurative expressions frequently appearing daily. Given its significance in
downstream natural language processing tasks such as machine translation and sentiment …

In this survey, we address the key challenges in Large Language Models (LLM) research,
focusing on the importance of interpretability. Driven by increasing interest from AI and …