In the present information age, a wide and significant variety of social media platforms have
been developed and become an important part of modern life. Massive amounts of user …

Sentiment analysis (SA), also referred to as opinion mining, has become a widely used real-
world application of natural language processing in recent times. Its main goal is to identify …

Deep Learning has been successfully applied to many application domains, yet its
advantages have been slow to emerge for time series forecasting. For example, in the well …

A large community of research has been developed in recent years to analyze social media
and social networks, with the aim of understanding, discovering insights, and exploiting the …

The coronavirus outbreak has brought unprecedented measures, which forced the
authorities to make decisions related to the instauration of lockdowns in the areas most hit …

The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI)
has become overwhelming, making it quite challenging for academics and relevant …

Across the globe, there is a noticeable upward trend of incorporating sarcasm in everyday
life. This trend can be easily attributed to the frequent use of sarcasm in everyday life, but …

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 …

Twitter is one of the most popular microblogging and social networking platforms where
massive instant messages (ie tweets) are posted every day. Twitter sentiment analysis …

When forecasting financial time series, incorporating relevant sentiment analysis data into
the feature space is a common assumption to increase the capacities of the model. In …