Sentiment analysis on students stress and depression due to Online Distance Learning during the COVID-19 pandemic / Nur Syafirah Izzati Samsari, Masurah Mohamad and Ali Selamat

• Main Authors: Samsari, Nur Syafirah Izzati (Author), Mohamad, Masurah (Author), Selamat, Ali (Author)
• Format: Book
• Published: Universiti Teknologi MARA, Perak, 2022-05.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/61725/1/61725.pdf; Sentiment analysis on students stress and depression due to Online Distance Learning during the COVID-19 pandemic / Nur Syafirah Izzati Samsari, Masurah Mohamad and Ali Selamat. (2022) Mathematical Sciences and Informatics Journal (MIJ) <https://ir.uitm.edu.my/view/publication/Mathematical_Sciences_and_Informatics_Journal_=28MIJ=29/>, 3 (1). pp. 66-74. ISSN 2735-0703
• Keywords: QA Mathematics; Analysis; Analytical methods used in the solution of physical problems

Recently, more young people are suffering from mental illness especially stress and depression during the COVID-19 pandemic. The different between how bad the mental health condition depends on the ways each individual handle and overcome it. Besides, factor that leads stress and depression also plays an important roles in order to know the level of the stress and depression. A person's age and background are also among the factors that cause stress and depression. For instance, stress and depression of students mostly happen because of their study especially during COVID-19 pandemic where schools and universities are closed, and online learning need to be implemented. This study analyses on the number of students that were affected from the COVID-19 pandemic during online distance learning. Two keywords "stress and depression" were used to extract the data from the Twitter. Sentiment analysis has been conducted in the analysis process and Naïve Bayes classifier was applied to classify the data into the predefined categories. 571 out of 2291 students experienced depression, 872 experienced high levels of stress and 848 were diagnosed with early-stage stress. The obtained results are visualized using polar area diagram to ease the readers' understanding.