Prediction of the impact of Facebook posts with machine learning

  • Germán Harvey Alférez Salinas
  • Adlay Stephany Levy Méndez
Palabras clave: Facebook, Machine Learning, prediction, web application


Facebook is the most popular social network. It is seen as entertainment and also as a tool. This tool can help businesses to advertise themselves and see how much scope they have. In this research work we use Machine Learning to automatize the prediction of the success of posts to be published on Facebook. As a case study, we used information collected from the Facebook page of Montemorelos University. In order to predict the success of Facebook posts, we developed a web application. This web application allows users to upload a data set of the performance of a Facebook page. Our tool uses this information to train 4 classification models with 4 dierent Machine Learning algorithms. Then, it chooses the model with the highest accuracy and shows the result of the most accurate one. Then, the user can use this model to predict the impact of a new post.

Cómo citar
Alférez Salinas, G. H., & Levy Méndez, A. S. (2020). Prediction of the impact of Facebook posts with machine learning. anuario2020, 1(1), 84-91. Recuperado a partir de

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