The application of Artificial Intelligence (AI) to financial investment is a research area that
has attracted extensive research attention since the 1990s, when there was an accelerated …

This study employs a fresh perspective to investigate the causal relationship between
uncertainty, measured via the two proxies of Economic Policy Uncertainty (EPU) and the …

For changing semantics, ontological and information presentation, as well as computational
linguistics for Asian social networks, are one of the most essential platforms for offering …

Natural language processing in specific domains such as financial markets requires the
knowledge of domain ontology. Therefore, developing a domain-specific lexicon to improve …

Digital transformation offers unprecedented opportunities to access data on hard-to-
measure social aspects. In this digital era, social media platforms have become critical data …

Although different studies are caried out by deep learning models for financial markets
sentiment analysis, there is a lack of specific embedding method that regards the domain …

Previous Sentiment Analysis (SA) studies have demonstrated that exploring sentiment cues
from multiple synchronized modalities can effectively improve the SA results. Unfortunately …

Today, the use of social networking data has attracted a lot of academic and commercial
attention in predicting the stock market. In most studies in this area, the sentiment analysis of …

During the past 20 years, due to climate change, the government and the private sector have
significantly focused on relying on non-fossil fuel-based methods for their energy needs …

Stock price prediction is challenging due to the non-stationary fluctuation of stock price,
which can be influenced by the stochastic trading behaviors in the market. In recent years …