Muni-Muni: Mood Analyzer and Screening Tests for the National Center of Mental Health using Sentiment Analysis

  • John Kcero C. Aujero College of Computer Studies, FEU – Institute of Technology, Manila, Philippines
  • Nico Manuel R. Cruz College of Computer Studies, FEU - Institute of Technology, Manila, Philippines
  • Jason Joie H. Padilla College of Computer Studies, FEU - Institute of Technology, Manila, Philippines
  • Mary Elysa D. Pineda College of Computer Studies, FEU - Institute of Technology, Manila, Philippines
  • John Benedict C. Legaspi College of Computer Studies, FEU - Institute of Technology, Manila, Philippines
  • Heintjie N. Vicente College of Computer Studies, FEU - Institute of Technology, Manila, Philippines

Abstract

Purpose – In the technological era we are living in today, advancement and innovation became mainstream that almost everything we do is now easier and more efficient. Psychological welfare is a vital part of one’s life yet most often than not, it is disregarded, especially in the Philippines.

Method – For this reason, this project aims to develop a web and mobile application, under the guidance of the National Center for Mental Health, that will promote mental health to the users. The system took advantage of Sentiment Analysis where the application analyzed the text input of the users and process the information using Lexicon Based Approach that produced polarity results such as Positive, Neutral, and Negative.

Results – Overall, the entire system is based on Cognitive Behavioral Therapy (CBT) and Dialectical Behavior Therapy (DBT) used by behavioral specialists. To test the effectiveness of the software, the proponents surveyed 40 students and 10 behavioral field professionals. Using the PERFS model, the result showed a weighted mean of 4.61 score which was equivalent to the Excellent tier.

Conclusion – The developers' client, National Center for Mental Health, was looking for tools, aids, and platforms to raise the mental health awareness of Filipinos and this Capstone Project is the solution.

Recommendation – The Sentiment Analysis utilized in the system is only at the entry-level. It can only understand the direct context of the English language. A plethora of words and phrases were not properly recognized either being by Negation of Words, Sarcasm, Proverbs, Jargon Words, and Emojis among others.

Research Implications – If future developers will decide to continue this project and follow the recommendations of the proponents, they can help and guide more users in improving their mental health, especially in today’s time.

Published
2022-02-13
How to Cite
AUJERO, John Kcero C. et al. Muni-Muni: Mood Analyzer and Screening Tests for the National Center of Mental Health using Sentiment Analysis. International Journal of Computing Sciences Research, [S.l.], v. 6, p. 1019-1031, feb. 2022. ISSN 2546-115X. Available at: <//stepacademic.net/ijcsr/article/view/295>. Date accessed: 21 dec. 2024.
Citation Formats
Issue
Vol 6 (2022): Vol 6
Section
Special Issue Part 1: NRCCET 2021
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