Computational Assessment of Hyperpartisanship in News Titles

In this study, we conduct a computational analysis to quantify the extent and dynamics of partisanship in news titles. While some aspects are as expected, our study reveals new or nuanced differences between the three media groups. [PDF]

Authors

Hanjia Lyu*, Jinsheng Pan*, Zichen Wang*, Jiebo Luo

*: equal contribution

Published at ICWSM 2024

Contact

Hanjia Lyu ([email protected]), Jiebo Luo ([email protected])

Data

The set of 2,200 manually labeled headlines is available, with 2,000 entries in training_set.csv and 200 in testing_set, both located in /data. The dataset containing 1.8 million machine labeled headlines is stored in /data/headlines_by_year.

Citation

@inproceedings{hyperpartisan-icwsm24,
title={Computational Assessment of Hyperpartisanship in News Titles},
author={Hanjia Lyu and Jinsheng Pan and Zichen Wang and Jiebo Luo},
booktitle={Proceedings of the International AAAI Conference on Web and Social Media},
volume={18},
pages={999--1012},
year={2024},
url={https://ojs.aaai.org/index.php/ICWSM/article/view/31368},
DOI={10.1609/icwsm.v18i1.31368}
}

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