transforEmotion: Sentiment Analysis for Text and Qualitative Data
Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines. The default pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> trained on the Stanford Natural Language Inference <https://nlp.stanford.edu/projects/snli/> and Multi-Genre Natural Language Inference <https://huggingface.co/datasets/multi_nli> datasets. Using similar models, zero-shot classification transformers have demonstrated superior performance relative to other natural language processing models <arXiv:1909.00161>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>}.
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
reticulate, pbapply, osfr, LSAfun, dplyr, remotes |
| Suggests: |
markdown, knitr, rmarkdown, rstudioapi |
| Published: |
2022-05-11 |
| Author: |
Alexander Christensen
 [aut, cre],
Hudson Golino
[aut] |
| Maintainer: |
Alexander Christensen <alexpaulchristensen at gmail.com> |
| License: |
GPL (≥ 3.0) |
| NeedsCompilation: |
no |
| Citation: |
transforEmotion citation info |
| Materials: |
NEWS |
| CRAN checks: |
transforEmotion results |
Documentation:
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