- Jieping Luo
- Zhuqi Yue
- FTD
This data science endeavor delves deeply into the multifaceted realm of the film industry. It seeks comprehensive insights into aspects of film investment, release timing, the influential role of talent, strategic marketing, and the socio-cultural elements affecting box office outcomes.
- Mitigate investment risks in the movie industry.
- Streamline decision-making processes for stakeholders, from investors to filmmakers.
The project harnesses a plethora of datasets, including:
- Historical box office figures
- Production outlays
- Film attributes (genre, duration, rating, etc.)
- Talent metrics (actors and directors)
- Marketing outlays
- Socio-economic indicators
- Descriptive Statistics: For discerning historical trends and patterns in the film industry.
- Predictive Modeling: For box office and trend projections, offering actionable insights and recommendations.
- Key Analytical Models:
- Regression modeling for box office predictions
- Sentiment analytics for audience feedback assessment
- Time series forecasting for identifying and projecting market trends
- Comprehensive insights into historical and current film industry trends.
- Predictive models for box office outcomes and market trends.
- Recommendations for film investors and producers on investment strategies, talent selection, and release strategies.
Instructions for contributing to the project, if it's open for contributions.