Prediction of Facebook Post Metrics using Machine Learning
This work addresses predicting social media post impact for societal benefit, but it is incremental as it applies existing methods to a known dataset.
The paper tackled predicting Facebook post metrics by evaluating three machine learning techniques—Support Vector Regression, Echo State Network, and Adaptive Network Fuzzy Inference System—on a public benchmark dataset, but no concrete performance numbers were provided.
In this short paper, we evaluate the performance of three well-known Machine Learning techniques for predicting the impact of a post in Facebook. Social medias have a huge influence in the social behaviour. Therefore to develop an automatic model for predicting the impact of posts in social medias can be useful to the society. In this article, we analyze the efficiency for predicting the post impact of three popular techniques: Support Vector Regression (SVR), Echo State Network (ESN) and Adaptive Network Fuzzy Inject System (ANFIS). The evaluation was done over a public and well-known benchmark dataset.