<![CDATA[Online reviews provide public feedback for higher education institutions, but overall star ratings cannot explain which institutional aspects shape public perception. This study aims to provide partial and aspect-specific digital reputation insights for five private higher education institutions in Padang City through aspect-based sentiment mapping of textual Google Reviews. Using Outscraper, 1,159 Google Review records were collected. After excluding 794 star-only reviews, 365 textual reviews were retained and transformed into 484 aspect-level records across five aspects: academic and lecturers, campus facilities, administrative services, environment and location, and general/others. The dataset was highly imbalanced, with 443 positive records (91.53%), 35 negative records (7.23%), and 6 neutral records (1.24%). Sentiment classification was evaluated using TF-IDF with Logistic Regression, TF-IDF with SVM, and IndoBERT through 5-fold stratified cross-validation. IndoBERT achieved the strongest performance, with an accuracy of 0.973, balanced accuracy of 0.710, macro F1-score of 0.760, and weighted F1-score of 0.971. The findings show that aspect-based sentiment mapping can support Google Review-based public perception monitoring by producing a university–aspect–sentiment map for the selected institutions. These findings are limited to textual Google Reviews from five selected institutions and should be validated using larger and more balanced datasets.]]>
Copyrights © 2026
