This paper investigates a data-driven approach for predicting the number of responses to a LinkedIn post. Various features such as post content, company statistics (e.g., followers and connections), ...

In this paper, we have used various algorithms such as Gradient Boost Regression, Catboost Regression, Decision Tree Regression and K-neighbors Regression by categorizing predictions based on ...