Overview:
The movie trend analysis tools are powerful software solutions designed to help individuals and organizations analyze the movie industry. By aggregating and processing large amounts of data from various sources, including box office results, movie ratings, social media engagement, and more, these tools present the data in a clear and concise format. Users can then quickly and easily identify trends and patterns, compare the performance of different films, analyze the success of specific genres, and even make predictions about future box office results. These tools are also customizable to meet the specific needs of a user or organization, with options for adjusting data sets, changing the format of reports, and adding custom calculations. Overall, movie trend analysis tools provide a comprehensive solution for anyone looking to gain a deeper understanding of the movie industry.
Visual Analytics:
Visual analytics is a data analysis approach that utilizes visual representations such as charts, graphs, and maps to gain insights and knowledge from data. By exploring and interacting with data using visualizations, users can identify patterns, relationships, and anomalies that may not be apparent from simply looking at raw data. Additionally, visual analytics can help to communicate findings more effectively by presenting complex data in a more understandable and intuitive way. Overall, the goal of visual analytics is to improve decision-making by enabling users to understand and explore data more effectively.
Project:
For this project, the team will develop a Shiny app as an interface to access the visualizations of movie data and support decision-making. The app will allow users to explore different movie genres and analyze trends in revenue, budget, and ratings. Users can interact with the data and explore the correlations between different variables. The app will also include a predictive model that can forecast the box office revenue of a new movie based on its genre and budget. Overall, this project aims to provide a user-friendly platform for movie trend analysis that leverages the power of visual analytics to support decision-making in the movie industry.
We are reachable at:
| Member | |
|---|---|
| Shi Chee Liang | clshi.2022@mitb.smu.edu.sg |
| Siddharth Singh | siddharths.2022@mitb.smu.edu.sg |
| Srivatsan M Srinivasan | srivatsanms.2022@mitb.smu.edu.sg |