Data · dataset · 2026
BanTABSA: A Temporally and Geographically Annotated Bangla Aspect-Based Sentiment Analysis Dataset for Hotel Reviews
Listed in Teesside University Research Data Repository
BanTABSA is a manually annotated dataset of Bengali hotel reviews designed for Aspect-Based Sentiment Analysis (ABSA), fine-grained opinion mining, and spatio-temporal NLP research.
Description
The dataset comprises 1,242 reviews yielding 3,633 aspect-opinion-sentiment triplets collected across 31 hotel establishments in 9 districts of Bangladesh, aggregated from Facebook groups, TripAdvisor, Booking.com, and guest surveys spanning review dates from 2017 to 2026.
Key features of BanTABSA: • Fine-Grained Annotations: Contains aspect-opinion-sentiment triplets across 24 aspect categories and 3 sentiment polarities (positive, negative, neutral). • Geo-Temporal Grounding: Each review is paired with a standardized ISO-8601 timestamp and hotel/district location identifiers, enabling temporal decay and geographical sentiment studies. • Benchmark Evaluation: Accompanied by baseline classification evaluations across TF-IDF, FastText, IndicBERTv2, XLM-RoBERTa, and BanglaBERT models.
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Files included in this release: 1. BanTABSA.csv: Primary dataset containing all reviews, ratings, timestamps, location metadata, and JSON-formatted triplets. 2. README.md: Data schema, column descriptions, taxonomy details, and Python usage code. 3. survey_questionnaire.pdf: The guest survey instrument used during data collection.
Links
Where it is published
- DOI doi.org/10.17632/btk4wbsrng.7 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/btk4wbsrng.7 | 18 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:460208 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Natural Language Processing'] |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |