ML-SocMedEmot: Machine Learning Event-based Social Media Emotion Detection Proactive Framework Addressing Mental Health: A Novel Twitter Dataset and Case Study of COVID-19
Leila Ismail,
Nada Shahin,
Huned Materwala
et al.
Abstract:Global rapidly evolving events, e.g., COVID-19, are usually followed by countermeasures and policies. As a reaction, the public tends to express their emotions on social media platforms. Therefore, predicting emotional responses to events is critical to put a plan to avoid risky behaviors. This paper proposes a machine learning-based framework to detect public emotions based on social media posts in response to specific events. It presents a precise measurement of population-level emotions which can aid govern… Show more
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