CLiQS Python module

CLiQS Python module provides implementation of multilingual crisis social media summarization model.

Please, if you use CLiQS for your research consider citing:

Fedor Vitiugin, Carlos Castillo: Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive Approach Using Transformers. In ACM Hypertext 2022. ACM Press. https://doi.org/10.1145/3511095.3531279

Installation

1. Install the module via pip:

pip install cliqs

2. Download LASER and CLiQS models:

python -m laserembeddings download-models
python -m cliqs download-models

3. Before running the script, please check installation of SpaCy models for language that you plan to use.

python -m spacy download fr_core_news_sm # for French

Test use

Download test data 'example.csv' file and put in the current directory.

Example of use:

import pandas as pd
from cliqs import CliqSum

sum = CliqSum()

tweets = pd.read_csv('example.csv')
summary = sum.summarize(tweets, 'Damage', 'fr')

print(summary)

cyclone seroja a touché terre en Australie, entre Kalbarri et northampton, l'oeil est encore bien dessiné mais devrait rapidement se déstructurer. cyclone seroja devrait prendre le dessus et atteindre le stade de cyclone 65kt ce WE avant de toucher terre sur côte ouest Australie dimanche soir.

• example.csv —- data file with three columns: id, text, en_text (translation of texts to English).
• Damage -- information category. Current version supports 6 categories: Casualties, Damage, Danger, Sensor, Service aand Weather.
• fr -- language of texts in file.

Resources

Code for training custom models — CLiQS-CM GitHub repository

Dataset for text classification — tweets dataset

Dataset for summary evaluation — summaries dataset