%Aigaion2 BibTeX export from HES SO Valais Publications
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@INPROCEEDINGS{,
     author = {Liu, Zhan and Darbellay, Anne and Glassey Balet, Nicole and Vuille, Val{\'{e}}rie},
   keywords = {artificial intelligence, automated evaluation, gender-based violence, GPT-4, media content analysis, Natural Language Processing},
      month = dec,
      title = {Advancing Gender Equality in Media: Tackling Stereotypes and Biases with AI},
  booktitle = {16th International Conference on Intelligent Decision Technologies},
       year = {2024},
      pages = {413-424},
  publisher = {Springer Nature},
   location = {Madeira, Portugal},
        url = {https://link.springer.com/chapter/10.1007/978-981-97-7419-7_36},
        doi = {https://doi.org/10.1007/978-981-97-7419-7_36},
   abstract = {This study presents an innovative approach to evaluating media representations of gender-based violence by integrating Natural Language Processing (NLP) techniques with the advanced capabilities
of GPT-4, an Artificial Intelligence (AI)-based large language model. We developed a set of 27 expert-defined criteria to analyze a corpus of news articles, initially utilizing NLP methods for foundational text analysis. For more complex criteria, we employed GPT-4 and further enhanced its precision with fine-tuning. Our results indicate a significant increase in accuracy, achieving an overall 76\% accuracy rate in content evaluation, which is 9 percentage points higher than using NLP alone. This research introduces a novel media content analysis framework and paves the way for future enhancements in automated journalism assessment and ethical reporting.}
}