Data Analytics on student response via social media on the educational landscape (learning, experience, humanization) during the COVID-19 pandemic

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.