---
license: apache-2.0
configs:
- config_name: default
  data_files:
  - split: english_observations
    path: UX-comments_english_observations.jsonl
  - split: english_sentences
    path: UX-comments_english_sentences.jsonl
  - split: spanish_observations
    path: UX-comments_spanish_observations.jsonl
  - split: spanish_sentences
    path: UX-comments_spanish_sentences.jsonl
size_categories:
- n<2K
task_categories:
- text-classification
language:
- en
- es
---

# Cross-Domain Polarity Models to Evaluate User eXperience in E-learning


### Abstract

Virtual learning environments are growing in importance as fast as e-learning, which is becoming highly demanded by universities and students worldwide. 
This paper investigates how to automatically evaluate User eXperience in this domain using sentiment analysis techniques. 
For this purpose, a corpus has been built with the opinions of 583 users (107 English speakers and 476 Spanish speakers) about three learning management systems in different courses.
All the collected opinions were manually labeled with polarity information (positive, negative, or neutral) by three human annotators, both at the whole opinion and sentence levels.


### Dataset Information


|   | P  | NEU  | N  | Total  |
|---|---:|---:|---:|---:|
| Spanish Observations  | 338 | 53 | 85 | 476 |
| Spanish Sentences  | 404 | 41 | 142 | 587 |
| English Observations  | 56 | 21 | 30 | 107 |
| English Sentences  | 90 | 14 | 80 | 184 |
P=Positive; NEU=Neutral; N=Negative


### Citation Information

If you use this dataset, please cite the following paper:
```
@article{sanchis2021cross,
  title={Cross-Domain Polarity Models to Evaluate User eXperience in E-learning},
  author={Sanchis-Font, R. and Castro-Bleda, MJ. and Gonz{\'a}lez-Barba, J{\'A}. and Pla Santamar{\'\i}a, F. and Hurtado Oliver, LF.},
  journal={Neural Processing Letters},
  volume={53},
  pages={3199--3215},
  year={2021},
  doi={https://doi.org/10.1007/s11063-020-10260-5},
  url={http://hdl.handle.net/10251/176382},
}
```