Matching Items (3)
Filtering by

Clear all filters

133794-Thumbnail Image.png
Description
This creative project centers on creating evaluative writing about film, in the form of a film review blog. Preliminary writing was done, in which the distinction was made between critical film writing and movie reviewing, as well as an analysis of how film critics have honed in their criticism and

This creative project centers on creating evaluative writing about film, in the form of a film review blog. Preliminary writing was done, in which the distinction was made between critical film writing and movie reviewing, as well as an analysis of how film critics have honed in their criticism and what makes their content effective for their audience. The rest of the writing for this project consists of a total of 15 reviews for 15 different movies released in 2017 and 2018. In these reviews, there is a brief introduction of the plot and context in which the film is made, followed by an evaluative analysis of what made the film effective or ineffective in achieving its artistic goals. The reviews involve an amalgamation of the content and topics taught in the Film and Media Studies program at Arizona State University, from screenwriting to cinematography. This process of writing reviews and being edited by the Director and Second Reader allows for the opportunity to find a unique writing voice and create content that is accessible for the wide audience that would be reading the work. All of the writing completed for this project (except for the "My Favorite Film Critics" piece) is compiled together in a WordPress blog, in an easily readable and accessible format. The blog itself serves as a way to reach the desired audience, as well as entice them to engage with the writing and the films being written about. This includes providing images and trailers for each respective film, to add a visual component to the writing. The final product is a unique way to engage with the content taught in the Film and Media Studies program, while simultaneously building a portfolio of writing that will be expanded upon and continued in the future.
ContributorsPolich, Brennan Taylor (Author) / Green, Michael (Thesis director) / Bernstein, Gregory (Committee member) / Department of English (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
137212-Thumbnail Image.png
DescriptionA comprehensive look at the roles and responsibilities of producers in contemporary Hollywood. The experience I have as an Associate Producer on a current project is also chronicled while the ups and downs of film production are explored.
ContributorsGalen, Adam (Author) / Sandler, Kevin (Thesis director) / Green, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / Department of Marketing (Contributor) / Department of English (Contributor)
Created2014-05
137156-Thumbnail Image.png
Description
Due to the popularity of the movie industry, a film's opening weekend box-office performance is of great interest not only to movie studios, but to the general public, as well. In hopes of maximizing a film's opening weekend revenue, movie studios invest heavily in pre-release advertisement. The most visible advertisement

Due to the popularity of the movie industry, a film's opening weekend box-office performance is of great interest not only to movie studios, but to the general public, as well. In hopes of maximizing a film's opening weekend revenue, movie studios invest heavily in pre-release advertisement. The most visible advertisement is the movie trailer, which, in no more than two minutes and thirty seconds, serves as many people's first introduction to a film. The question, however, is how can we be confident that a trailer will succeed in its promotional task, and bring about the audience a studio expects? In this thesis, we use machine learning classification techniques to determine the effectiveness of a movie trailer in the promotion of its namesake. We accomplish this by creating a predictive model that automatically analyzes the audio and visual characteristics of a movie trailer to determine whether or not a film's opening will be successful by earning at least 35% of a film's production budget during its first U.S. box office weekend. Our predictive model performed reasonably well, achieving an accuracy of 68.09% in a binary classification. Accuracy increased to 78.62% when including genre in our predictive model.
ContributorsWilliams, Terrance D'Mitri (Author) / Pon-Barry, Heather (Thesis director) / Zafarani, Reza (Committee member) / Maciejewski, Ross (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-05