Data · dataset · 2026
Aspect-Based Sentiment Analysis on Generative AI
Listed in Teesside University Research Data Repository
This dataset contains 1001 app reviews related to generative AI tools, collected from app stores, social media, review sites, and existing publicly available datasets.
Description
It is designed for aspect-based sentiment analysis and includes columns for full review text, argument (a specific text span corresponding to a single aspect), identified aspects, sentiment labels, source of the data, and the AI tool being reviewed. A single review may appear in multiple rows when it contains multiple aspects; in such cases, each row represents a unique argument–aspect pair derived from the same review.
All personal identifiers have been removed to ensure privacy. Basic preprocessing was performed, including the removal of unnecessary columns and rows and minor text edits. The dataset is intended for research in sentiment analysis, natural language processing, and related tasks.
Read the rest (4 more)
Version 3 update: This version adds new records to the dataset. A combined file with 1001 total entries (the original data plus the new records) is included. The original file is kept for reference and reproducibility.
For any new analyses, users should use the merged file. Version 4 update: This update expands the dataset to 1,948 unique argument–aspect pairs. We performed a thorough deep cleaning process.
This process removed all recycled baseline rows. All licensing guidelines are met and the final dataset is completely original. Please use this merged updated file for all current benchmark training and evaluation.
Version 5 update:
Links
Where it is published
- DOI doi.org/10.17632/n3wm4xbs5n.5 ↗
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
- From keywords
- Artificial intelligence · Computer Science & AI · Earth & Environmental Science · Humanities · Natural language processing
- Inferred from text
- Text 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/n3wm4xbs5n.5 | 17 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 | |
| concepts[modality].local:modality:text | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| 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 |