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@INPROCEEDINGS{,
     author = {Liu, Zhan and Glassey Balet, Nicole},
   keywords = {big data analytics, decision making, digital newspaper industry, media, news content, user behavior},
      month = aug,
      title = {Bringing Big Data into Media: A Decision-Making Model for Targeting Digital News Content},
  booktitle = {2022 IEEE/ACIS 7th International Conference on Big Data, Cloud Computing, and Data Science (BCD)},
       year = {2022},
      pages = {218-223},
  publisher = {IEEE},
   location = {Online},
       isbn = {978–1–6654–6582–3},
        url = {https://ieeexplore.ieee.org/document/9900754},
        doi = {https://doi.org/10.1109/BCD54882.2022.9900754},
   abstract = {The purpose of this study is to investigate how big data analytics technology affects decision-making in the media industry, with a focus on digital newspapers. To achieve this goal, we propose a decision-making model to identify the relationship between audiences and news topics using big data analysis and classification, intending to help news practitioners optimize their marketing strategies. To evaluate our model, we conducted a case study using a Swiss local newspaper. Preliminary results indicate that audience reading time and volume have been significantly increased after implementing the decision that based on the model’s analysis. The study also provides some guidelines for editors and journalists to target their digital news content.}
}