An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis

Article Computer Science, Information Systems

A survey on recommendation systems for financial services

Marwa Sharaf et al.

Summary: The recommendation system plays a crucial role in guiding users to find interesting content from a vast amount of information. This paper provides an overview of the recommendation system, its types, and its applications, with a specific focus on the finance recommendation system.

MULTIMEDIA TOOLS AND APPLICATIONS (2022)

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Article Computer Science, Information Systems

StockPred: a framework for stock Price prediction

Marwa Sharaf et al.

Summary: Stock price prediction is a challenging task, and this study proposes a framework using various learning models to predict stock prices. The experiments show that the CNN model performs the best in different circumstances.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

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Article Multidisciplinary Sciences

COVID-19 sentiment analysis via deep learning during the rise of novel cases

Rohitash Chandra et al.

Summary: Social scientists and psychologists are interested in how people express emotions during catastrophic events like COVID-19 pandemic. Advances in deep learning language models have shown promise in sentiment analysis. Different countries experienced varying peaks of new cases, affecting lockdowns and economy. People expressed sentiments on social media during stricter lockdowns, providing insight into human psychology. The framework presented in the paper uses deep learning models for sentiment analysis during the rise of novel COVID-19 cases in India and shows that while most tweets were optimistic, there were also expressions of annoyance towards the authorities' handling of the pandemic.

PLOS ONE (2021)

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Review Computer Science, Artificial Intelligence