Date of Award
Master of Arts (AM/MA)
Social networks have changed the way that we obtain information. Content creators and, specifically news article authors, have in interest in predicting the popularity of content, in terms of the number of shares, likes, and comments across various social media platforms. In this thesis, I employ several statistical learning methods for prediction. Both regression-based and classification-based methods are compared according to their predictive ability, using a database from the UCI Machine Learning Repository.
Chair and Committee
Nan Lin, Jimin Ding
Liu, Ziyi, "Statistical Models to Predict Popularity of News Articles on Social Networks" (2017). Arts & Sciences Electronic Theses and Dissertations. 1052.
Permanent URL: https://doi.org/10.7936/K7Z036MM