Skip to content

Latest commit

 

History

History
79 lines (54 loc) · 4.58 KB

README.md

File metadata and controls

79 lines (54 loc) · 4.58 KB
Raw

Cine_Sprite_Dash_Land_Home

CineSprite Developed by Pirate-Emperor, Cine_Sprite_Dash_Land_Home is a web-based dashboard application built using ReactJS. It provides movie producers with data-driven insights, recommendations for movie ideas, assistance in structuring movies, and integrates with IMDB API for fetching movie details.

Abstract

According to the Journal of Cultural Economics (2022), attendance frequency per capita found to be 3.89 in the year 2022 which had a decline of 1.90 since 2005 despite having doubled the number of titles produced which forces us to ponder on the quality of the titles produced in the current generation. Hence, in order to prevent redundancy of titles and user-based title production this project has been started. In other words, our main aim is to satisfy customers’ needs and provide them with content of the utmost quality.

In order to aid the everyone, we created a website called Cine Sprite, which is a Movie Database and Recommendation-Insight Generator System (MDRIGS), created for the specific purpose of generating and providing new title ideas to the producers by incorporating viewer’s data into the title-generator model. In fact, various OTT sites have already incorporated user-based title production but not all the entertainment industry has adopted this approach and so the purpose of the project is to spread this approach around the globe, specifically India, as the latter has the highest number of titles production than any countries.

Secondary Feature would be the ability to view basic information about titles (including movies, web series, anime) such as box office collection, popularity, casting, trailers, ratings etc., which helps in getting user’s habitual actions to improve model’s efficiency. It is designed as a one-stop destination for the user to access the titles that are Upcoming, Popular, Trending or Recommended.

Features

  • Movie Idea Recommendations: Offers recommendations for movie ideas based on trends, genres, and audience preferences.
  • Movie Structuring Assistance: Provides guidance on structuring movies, including plot development, character arcs, and scene organization.
  • Data-Driven Insights: Displays data visualizations and metrics related to movie performance, audience demographics, and market trends.
  • Content Management: Allows movie producers to manage movie projects, including scripts, casting, and production schedules.
  • Collaboration Tools: Facilitates collaboration among team members by providing project management features and communication tools.
  • IMDB API Integration: Fetches movie details and additional information from the IMDB API.
  • Web Automation: Gathers data and information through web automation techniques for content not available in the API.
  • Responsive Design: Ensures a seamless user experience across various devices and screen sizes.

Screenshots

screenshot1 screenshot2 screenshot3 screenshot4 screenshot5 screenshot6 screenshot7

Prerequisites

To run the project, you'll need:

  • Node.js
  • npm (Node Package Manager)

Installation

Clone the repository and navigate to the project directory:

git clone https://github.com/Pirate-Emperor/Cine_Sprite_Dash_Land_Home.git
cd Cine_Sprite_Dash_Land_Home

Install the required dependencies:

npm install

Usage

Start the development server:

npm start

The application will be accessible at http://localhost:3000/. You can navigate through the dashboard to access various features and insights related to movie production.

Data Source

The dashboard uses a combination of movie databases, industry reports, and user-generated content to provide insights and recommendations. It integrates with the IMDB API to fetch movie details and uses web automation techniques for data gathering.

Development

To enhance the project, you can modify the React components in the src directory. Some potential areas for improvement include:

  • Implementing machine learning models for generating movie ideas and predicting movie success.
  • Expanding the content management features to include budgeting, marketing, and distribution planning.
  • Enhancing collaboration tools with real-time updates, file sharing, and version control.
  • Incorporating user feedback and reviews to refine movie ideas and improve structuring assistance.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.