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 …

Investors are constantly aware of the behaviour of stock markets. This affects their emotions
and motivates them to buy or sell shares. Financial sentiment analysis allows us to …

Research on sentic computing has received intensive attention in recent years, as indicated
by the increased availability of academic literature. However, despite the growth in literature …

In this manuscript, we propose a Machine Learning approach to tackle a binary classification
problem whose goal is to predict the magnitude (high or low) of future stock price variations …

Extracting sentiment from news text, social media and blogs has recently gained increasing
interest in economics and finance. Despite many successful applications of sentiment …

Deciphering user purchase preferences, their likes and dislikes is a very tricky task even for
humans, making its automation a very complex job. This research work augments heuristic …

Sentiment analysis aims to identify the way in which sentiments are expressed in texts. State-
of-the-art approaches base their analyses solely on the given text, which complicates the …

Long short-term memory (LSTM) or gated recurrent units (GRUs) are usually employed to
recurrently learn variable-length sentence representations with long-range dependency in …

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) …

This paper presents a state-of-the-art approach for sentiment polarity classification. Our
approach relies on an ensemble of Bidirectional Long Short-Term Memory networks …