  Likert-style surveys are a widely used research instrument to assess
respondents' preferences, beliefs, or experiences. In this paper, we propose
and demonstrate how network analysis (NA) can be employed to model and evaluate
the interconnectedness of items in Likert-style surveys. We explore the
advantages of this approach by applying the methodology to the aspects of
student experience scale datasets and compare the results to the principal
component analysis. We successfully create a meaningful network based on survey
item response similarity and use modular analysis of the network to identify
larger themes built from the connections of particular aspects. The modular NA
of the network of survey items identifies important themes that highlight
differences in students' overall experiences. Our network analysis for
Likert-style surveys methodology is widely applicable and provides a new way to
investigate phenomena assessed by Likert-style surveys.
