Data Analytics on student response via social media on the educational landscape (learning, experience, humanization) during the COVID-19 pandemic - Zaiful Anuar, Muhamad Zarif (IRC, 2020)
Ever since the start of the COVID-19 Pandemic, students of tertiary educational institutions have been faced with multiple challenges navigating their studies and living situations. In particular, Universiti Teknologi Petronas (UTP) students had problems adapting to the various changes brought forth by management such as the changing mode of learning, having to return to campus, accommodation and accommodating to course fees whilst suffering economic setbacks. This study aims to analyse the student’s perspective on how their respective universities are handling the pandemic in an academic, social and welfare context. Specifically, it investigates how UTP students view the efforts being put forth by the university management in terms of managing student academic progress, quality of life and promotion of UTP whilst coping with the ongoing pandemic. To uncover unfiltered student opinions, one Facebook page was selected, UTP Community page managed by the Student Representative Council. All comments from particularly selected posts are retrieved via a data extraction tool. Then, a sentiment analysis of the comments is carried out using machine learning algorithms such as Support Vector Machine to analyse the sentiments conveyed by the students via their comments. A comparative analysis between the two algorithms is also conducted. The results of the study are still in progress and will be presented during the viva presentation.