Social media engagement of young people: A sentiment analysis using natural language processing

• Main Authors: Aranda, Elaine Marie, Navea, Roy Francis R.
• Format: text
• Published: Animo Repository 2022
• Subjects: Sentiment analysis; Natural language processing (Computer science); User-generated content; Computer Sciences; Psychology
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/11634
• Institution: De La Salle University

Mental health is an integral part of human existence and is most likely underestimated when it comes to human health. The thoughts that occupy the mind affects how a person feel and it corresponds to action which may have beneficial or harmful results. Thoughts are commonly expressed in words through written or verbal communication. In this study, the sentiments of young people are determined through the responses that they provide as they share their social media engagement experiences. With Natural Language Processing (NLP) and the implementation of Valence Aware Dictionary and s Entiment Reasoner (VADER), word clouds were produced containing significant words that indicate positive and negative sentiments. Results show common words in the positive sentiment as well as in the negative sentiment that support and represent the reality of the experience of young people as they engage in different social media activities.