Using Random Forest model to predict image engagement rate

Sammanfattning: The purpose of this research is to investigate if Google Cloud Vision API combined with Random Forest Machine Learning algorithm is advanced enough in order to make a software that would evaluate how much an Instagram photo contributes to the image of a brand. The data set contains images scraped from the public Instagram feed filtered by #Nike, together with the meta data of the post. Each image was processed by the Google Cloud Vision API in order to obtain a set of descriptive labels for the content of the image. The data set was sent to the Random Forest algorithm in order to train the predictor. The results of the research shows that the predictor can only guess the correct score in about 4% of cases. The results are not very accurate, which is mostly because of the limiting factors of the Google Cloud Vision API. The conclusion that was drawn is that it is not possible to create a software that can accurately predict the engagement rate of an image with the technology that is publicly available today.