Date Thesis Awarded

5-2020

Access Type

Honors Thesis -- Access Restricted On-Campus Only

Degree Name

Bachelors of Science (BS)

Department

Mathematics

Advisor

Junping Shi

Committee Members

Guannan Wang

Ayse Durukan Sonmez

Abstract

A mathematical model describing the trend of the movie revenue after its release is constructed based on the Bass Diffusion Model. % and the SIR epidemic model. The model takes account of the effect of the coefficient of innovation including media advertising, social media propaganda and the coefficient of imitation which are mainly the recommendation from people who have seen the movie. With this proposed model, we fit the historical revenue behavior of the 90 movies in the data set, and use statistical measure to test how well the model fits the data and how well the predictions can be. Finally based on the parameters generated from data fitting, we cluster the movies into different groups and find the common features for each group that can be used for future clustering and future predictions.

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