[agents] Invitation for Collaboration - ML-NLPEmot: Machine Learning-Natural Language Processing Event-Based Emotion Detection Proactive Framework Addressing Mental Health

[Leila Ismail]

Dear Colleagues,

Please check our new published paper ML-NLPEmot: Machine Learning-Natural Language Processing Event-Based Emotion Detection Proactive Framework Addressing Mental Health:

https://ieeexplore.ieee.org/document/10360126

An annotated dataset is available for researchers working on sentiments and emotion detection:

https://github.com/INDUCE-Lab/ML-SocMedEmot

Please feel free to reach out with your invaluable comments and for research collaboration.

"
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-Natural Language Processing-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 governance in monitoring public response and guide it to put in place strategies such as targeted monitoring of mental health, to react to a rise in negative emotions in response to lockdowns, or information campaigns, for instance in response to elevated rates of fear in response to vaccination programs. We evaluate our framework by extracting 15,455 tweets. We annotate and categorize the emotions into 11 categories based on Plutchik's study of emotion and extract the features using a combination of Bag of Words and Term Frequency-Inverse Document Frequency. We filter 813 COVID-19 vaccine-related tweets and use them to demonstrate our framework's effectiveness. Numerical evaluation of emotions prediction using Random Forest and Logistic Regression shows that our framework predicts emotions with an accuracy up to 95.5%.

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Best regards,
Leila

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Leila Ismail, Ph.D.
Associate Professor, Dept. of Computer Science & Software Engineering
Founding Director of Intelligent Distributed Computing & Systems (INDUCE) Laboratory

College of Information Technology, United Arab Emirates University
P.O.Box 15551, Al-Ain, United Arab Emirates
Telephone: +971-3-7135530 (Office)
Email: leila at uaeu.ac.ae<mailto:leila at uaeu.ac.ae>



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