Automatic Predictions Using LDA for Learning through Social Networking Services
Christos Troussas, Akrivi Krouska, Maria K. Virvou · 2017
Social Networking Services can serve as a great platform for learning. As such, the use of Facebook in learning contexts can be proved beneficial. Following this direction, this paper presents a prototype Facebook application for learning which is supported by Latent Dirichlet allocation (LDA). LDA is a generative model that allows sets of observations to be explained by unobserved groups that clarify why some parts of the data are similar. Hence, making automatic predictions about the interests of students can be made by collecting their preferences and characteristics. Hence, by tracking user interests, accurate recommendations can be made. The experimental results, presented in this paper, reinforce the view that automatic predictions using LDA to students in social networks can be a powerful idea in personalizing instruction.