Sentiment and Data Analysis of Mental Health Hotline in Thailand Based on Social Media by Machine Learning

Abstract

Introduction

            The Thai Mental Health Hotline has been utilized to help people with their mental health issues, bridging the gap in mental health access. However, no previous article has identified its drawbacks. Thus, this evidence on social media response might reflect real world feedback and show substantial impediments to providing mental health care via telepsychiatry in Thailand.

Objective

Our research aims to describe and analyze feedback on social media about receiving mental health services from the Thai Mental Health Hotline by using sentiment analysis, machine learning, visualization of data, and text analytics.

Method

            Thai Mental Health Hotline comments were gathered manually from Facebook and Pantip, and automatically from Twitter by using related keywords. Data preparation and sentimental analysis were applied to interpret all comments by using WangchanBERTa, the latest and largest Thai language NLP model. Exploratory Data Analysis was performed through Python and Excel to clean and investigate trends of feedback by time. The negative opinion was focused to identify causes of adverse outcomes. The overall data was visualized to discuss and conclude the outcome.

Result

            From 555 comments gathered from 2013-2020, 52.40% of the comments are neutral, followed by negative at 35.05%, and positive at 12.55%. The number of comments from social media were low from 2013 - 2019, and then rose extremely to climax (213 comments) during 2020. Focused on the complaints, most of them are about absent response issues (79.47% out of all negative response), service quality (13.16% out of all negative response) and others.

Conclusion

The peak of comment in 2020 may be influenced by Covid-19. Moreover, aside from neutral reactions, data suggest that there are more negative than positive responses. To deal with negative feedback, including absent response and poor service quality, more psychologists should be provided, and more expenditure should be spent on training consultants.