Description
Analysis of Sentiments in IMDB Movie Reviews
As the number of internet users continues to grow, social media plays a significant role in influencing people’s online habits. This shift from traditional print media to digital media has led to a reliance on online reviews for products, services, and even movies on platforms like IMDb. Users express their sentiments and emotions through their reviews, providing valuable insights for others looking to make informed decisions. Sentiment analysis of IMDb movie reviews helps extract information on the popularity of a movie, audience emotions, and preferences, such as which age group is influenced by specific characters.
The process of sentiment analysis involves uncovering hidden emotions within customer reviews by analyzing keywords used in the text. This analysis is crucial for filmmakers to understand audience reactions and preferences, as they may differ from the intended message of the movie. By examining IMDb movie trailer reviews, directors and producers can gauge audience feedback and make necessary adjustments to their films. Emotions play a key role in the customer buying process, making it essential to focus on understanding and addressing customer sentiments in movie reviews.
Static Pages and Additional Sections:
The project “Sentiment Analysis of IMDB Movie Reviews” includes the following static pages:
- Home Page with a user-friendly interface
- An animated slider for image banners on the Home Page
- About Us page providing project information
- Contact Us page for user inquiries
Technology Used in the Project:
The project utilizes the following technologies:
- HTML for page layout design
- CSS for styling and design elements
- JavaScript for validation tasks and animations
- Python for implementing business logic
- MySQL as the database management system
- Django framework for project development
- Python libraries such as numpy, nltk, pyparsing, and PySocks
Supported Operating Systems:
The project can be configured on the following operating systems:
- Windows: Easily set up on Windows OS with Python 3, PIP, and Django installed
- Linux: Compatible with all versions of Linux operating systems
- Mac: Can be configured on Mac operating systems as well
