Publications by authors named "Moein Shahiki Tash"
Article Synopsis
- The study investigates how hope acts as a coping mechanism and utilizes Natural Language Processing (NLP) tools to analyze social media posts about hope, focusing on psycholinguistic and emotional features.
- It identifies various cognitive and emotional characteristics associated with different types of hope expressed online and explores the potential to classify these types using machine learning algorithms.
- Models like LightGBM and CatBoost were found to outperform traditional methods, showing notable improvements in efficiency through hyperparameter tuning.
This paper provides an extensive examination of a sizable dataset of English tweets focusing on nine widely recognized cryptocurrencies, specifically Cardano, Binance, Bitcoin, Dogecoin, Ethereum, Fantom, Matic, Shiba, and Ripple. Our goal was to conduct a psycholinguistic and emotional analysis of social media content associated with these cryptocurrencies. Such analysis can enable researchers and experts dealing with cryptocurrencies to make more informed decisions.
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