Predicting News Article Popularity with Multi Layer Perceptron Algorithm

Arie Rachmad Syulistyo, Vira Meliana Agustin, Dwi Puspitasari

Abstract


Nowadays, news media seems to have been digitized. One of them is printed news which has now turned into online news. The increasing use of social media has made people interested in reading news online. News needs to attract readers with their headlines. Various online news media businesses want to know the future demand of readers, as well as whether the released news can reach more readers so that the news becomes popular. Therefore, with the increasing interest in online news today, this paper will analyze the performance of the Neural Network Algorithm and other artificial intelligence techniques in predicting the popularity of news articles that can help the media to know whether their news will become popular. The news article popularity prediction system can increase its revenue if there are advertisements in the news. The test results show that the accuracy of the Multi Layer Perceptron is 76% and Random Forest gives an accuracy of 70%.

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References


J. Boumans, D. Trilling, R. Vliegenthart, and H. Boomgaarden, “The Agency Makes the (Online) News World Go Round: The Impact of News Agency Content on Print and Online News,” Int. J. Commun., vol. 12, pp. 1768–1789, 2018.

H. Ren and Q. Yang, “Predicting and Evaluating the Popularity of Online News,” Conf. Proc., 2015, [Online]. Available: https://pdfs.semanticscholar.org/9e91/6a3469e9e2fc5f0c8f927d7d1d05f5575729.pdf%0Ahttp://cs229.stanford.edu/proj2015/328_report.pdf.

P. Meesad, “Thai Fake News Detection Based on Information Retrieval, Natural Language Processing and Machine Learning,” SN Comput. Sci., vol. 2, no. 6, pp. 1–17, 2021, doi: 10.1007/s42979-021-00775-6.

J. Rezaeenour, M. Y. Eili, E. Hadavandi, and M. H. Roozbahani, “Developing a new hybrid intelligent approach for prediction online news popularity,” Int. J. Inf. Sci. Manag., vol. 16, no. 1, pp. 71–87, 2018.

D. Hardt, D. Hovy, and S. Lamprinidis, “Predicting news headline popularity with syntactic and semantic knowledge using multi-task learning,” Proc. 2018 Conf. Empir. Methods Nat. Lang. Process. EMNLP 2018, pp. 659–664, 2018, doi: 10.18653/v1/d18-1068.

P. Rathord, D. A. Jain, and C. Agrawal, “A Comprehensive Review on Online News Popularity Prediction using Machine Learning Approach,” Smart Moves J. Ijoscience, vol. 5, no. 1, p. 7, 2019, doi: 10.24113/ijoscience.v5i1.181.

H. A. Khoirunissa, A. R. Widyaningrum, and A. P. A. Maharani, “Comparison of Random Forest, Logistic Regression, and Multilayer Perceptron Methods on Classification of Bank Customer Account Closure,” Indones. J. Appl. Stat., vol. 4, no. 1, p. 14, 2021, doi: 10.13057/ijas.v4i1.41461.

F. Namous, A. Rodan, and Y. Javed, “Online News Popularity Prediction,” ITT 2018 - Inf. Technol. Trends Emerg. Technol. Artif. Intell., no. Itt, pp. 180–184, 2019, doi: 10.1109/CTIT.2018.8649529.

S. A. Salloum, M. Al-Emran, A. A. Monem, and K. Shaalan, “Using text mining techniques for extracting information from research articles,” Stud. Comput. Intell., vol. 740, pp. 373–397, 2018, doi: 10.1007/978-3-319-67056-0_18.

M. A. Rosid, A. S. Fitrani, I. R. I. Astutik, N. I. Mulloh, and H. A. Gozali, “Improving Text Preprocessing for Student Complaint Document Classification Using Sastrawi,” IOP Conf. Ser. Mater. Sci. Eng., vol. 874, no. 1, 2020, doi: 10.1088/1757-899X/874/1/012017.




DOI: https://doi.org/10.33633/jais.v7i2.6826

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Journal of Applied Intelligent System (e-ISSN : 2502-9401, p-ISSN : 2503-0493) is published by Department of Informatics Universitas Dian Nuswantoro Semarang and IndoCEISS.

  

 

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