This project centres on facework as a linguistic resource in preventive, diagnostic and curative aspects of mental health in response to life stressors. This is in view of national and global indicators on mental health, the considerable neglect of mental health in Nigeria, and the important role of communication in dealing with life stressors.
Take care of your Emotional and psychological well-being
Preventive, diagnostic, and curative; Mental health encompasses the well-being of an individual's emotional, psychological, and social state.
The knowledge and understanding of mental health issues, including their prevalence, symptoms, and available support systems.
The mental health sentiment analysis application utilizes advanced algorithms to analyze and interpret the emotional tone and sentiment expressed in text data, providing valuable insights into the emotional states of individuals or groups.
The knowledge and understanding of mental health issues, including their prevalence, symptoms, and available support systems.
Preventive, diagnostic, and curative; Mental health encompasses the well-being of an individual's emotional, psychological, and social state.
The emotional sentiment analysis application utilizes advanced algorithms to analyze and interpret the emotional tone and sentiment expressed in text data, providing valuable insights into the emotional states of individuals or groups.
Detecting and categorizing triggers of emotional stress, enabling targeted interventions.
Data was scraped from popular social media platforms, Twitter and Reddit, based on known stressors, resulting in datasets of at least 1000 text data per stressor, using a Python scraper library.
The scraped data for each stressor was saved as a CSV file and underwent preprocessing, including removing unnecessary characters and tokenizing the text using the pandas library in Python.
Sentiment analysis involved determining the emotional state of the text by assigning sentiment values to each word based on a sentiment lexicon and classifying the text into True positive, True negative, False positive, and False negative categories based on the presence of stressors and the sentiment expressed.
Suitable machine learning models for classification were identified, the identified models were trained and tested using the dataset, which was divided into training and testing data
The trained models were used for classifying text by inputting the text related to a specific stressor and generating the analysis results for the user on a webpage.
The emotional sentiment analysis application utilizes advanced algorithms to analyze and interpret the emotional tone and sentiment expressed in text data, providing valuable insights into the emotional states of individuals or groups.
We are committed to a long-term mission to optimise mental health through effective communication. Our leadership team encompasses experts from the fields of English Language and Communication, Psychiatry, Clinical Psychology, and Information Communication Technology. This strategic partnership forms the bedrock of our multidisciplinary collaboration, as we endeavor to chart the right course, ensuring that our efforts yield impactful outcomes in the realm of mental well-being.
Email: bolanlekassal@gmail.com
Qualification: PhD
Institution: Federal University of Agriculture, Abeokuta
Email: ayosisdelexus@yahoo.com
Qualification: PhD
Institution: : University of Ibadan, Ibadan
Email: chinaguhec@funaab.edu.ng
Qualification: PhD
Institution: Federal University of Agriculture, Abeokuta
Email: amosusunday@yahoo.com
Qualification: BSc.
Institution: Neuropsychiatric Hospital, Aro, Abeokuta, Nigeria
Email: lanresodeinde@yahoo.com
Qualification: PhD.
Institution: Neuropsychiatric Hospital, Aro, Abeokuta, Nigeria
Email: monaolapo@yahoo.co.uk
Qualification: MSc.
Institution: Neuropsychiatric Hospital, Aro, Abeokuta, Nigeria
Email: adeyemiya@funaab.edu.ng
Qualification: MSc.
Institution: Federal University of Agriculture, Abeokuta
Email: agosuoss@funaab.edu.ng
Qualification: MSc.
Institution: Federal University of Agriculture, Abeokuta