JOSA ML trainer

Train JOSA (Jopara Sentiment Analysis) corpus with traditional machine learning algorithms.

Install

Virtualenv

First create a virtual environment in the root dir by running:

python3 -m venv venv

then activate the virtual env with

source venv/bin/activate

(to get out of the virtualenv, run deactivate)

Dependencies

install all the dependencies with

pip install -r requirements.txt

also make sure to download nltk's corpus by running those line in python interpreter:

import nltk
nltk.download()

Paths

• Corpus: corpus-dir/ds/
  • Files in Corpus: sa3_train.txt, sa3_dev.txt, sa3_test.txt (format: one line per tweet; tweet ||| class)
• Log: log_dir
• Model: models

Train Unbalanced / Balanced corpus

cd src
python main.py "y" "corpus-dir/" "SVC" --train_cat > "log_dir/sa3_SVC`date '+%Y_%m_%d__%H_%M_%S'`.log"
python main.py "y" "corpus-dir/" "SVC" --train_cat --balanced > "log_dir/sa3_SVCBal`date '+%Y_%m_%d__%H_%M_%S'`.log"
python main.py "y" "corpus-dir/" "CNB" --train_cat > "log_dir/sa3_CNB`date '+%Y_%m_%d__%H_%M_%S'`.log"
python main.py "y" "corpus-dir/" "CNB" --train_cat --balanced > "log_dir/sa3_CNBBal`date '+%Y_%m_%d__%H_%M_%S'`.log"

How do I cite this work?

Please, cite this paper On the logistical difficulties and findings of Jopara Sentiment Analysis:

Marvin M. Agüero-Torales, David Vilares, Antonio G. López-Herrera (2021). On the logistical difficulties and findings of Jopara Sentiment Analysis. In Proceedings on CALCS 2021 (co-located with NAACL 2021) - Fifth Workshop on Computational Approaches to Linguistic Code Switching, to appear (June).

BibTeX format pending