Aspect-Based Sentiment Dataset of Tourism Reviews in Central Java, Indonesia – Labeled Using Rule-Based Method

This dataset collection contains Google Reviews from ten tourist destinations located in Central Java, Indonesia, each manually annotated using a rule-based aspect-based sentiment analysis (ABSA) approach. The destinations include both cultural and recreational sites such as temples, mosques, beaches, historical landmarks, and family attractions. Each review has been labeled based on three primary tourism aspects: Amenities Attractions Accessibility In addition to the aspect category, each label is also assigned a sentiment polarity: Positive, Negative, or Neutral. This structured sentiment labeling enables detailed analysis of tourist perceptions and supports downstream tasks such as tourism recommender systems, public service evaluation, and sentiment-aware destination ranking. Included Destinations: Borobudur Temple (borobudur_labeled.xlsx) Kota Lama Semarang (kotalama_labeled.xlsx) Lawang Sewu Museum (lawangsewu_labeled.xlsx) Masjid Agung Demak (masjid agung demak_labeled.xlsx) Owabong Water Park (owabong_labeled.xlsx) Pantai Jatimalang (pantai jatimalang_labeled.xlsx) Pantai Marina (pantai marina_labeled.xlsx) Prambanan Temple (prambanan_labeled.xlsx) Dusun Semilir (semilir_labeled.xlsx) Sunan Kalijaga Tomb (sunan kalijaga_labeled.xlsx) Columns in Each Dataset File Include: Author: Reviewer name Author Description: Reviewer level/status on Google Date: Timestamp of review Rating: Star rating (1–5) Review: Original review text Review_clean: Preprocessed text Labels: List of (Aspect, Sentiment) pairs using rule-based classification Labeling Method:Reviews were labeled using rule-based pattern recognition, combining predefined tourism keywords with polarity detection rules in both Indonesian and English. Intended Use: This dataset is designed for academic research and development in: Multilingual Aspect-Based Sentiment Analysis (ABSA) Tourism sentiment trend analysis Recommender Systems Smart tourism decision support systems (DSS)