TY  - CONF
T1  - Bringing Big Data into Media: A Decision-Making Model for Targeting Digital News Content
A1  - Liu, Zhan
A1  - Glassey Balet, Nicole
TI  - 2022 IEEE/ACIS 7th International Conference on Big Data, Cloud Computing, and Data Science (BCD)
Y1  - 2022
SP  - 218
EP  - 223
PB  - IEEE
CY  - Online
SN  - 978–1–6654–6582–3
UR  - https://ieeexplore.ieee.org/document/9900754
M2  - doi: https://doi.org/10.1109/BCD54882.2022.9900754
KW  - big data analytics
KW  - decision making
KW  - digital newspaper industry
KW  - media
KW  - news content
KW  - user behavior
N2  - 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.
ER  -