This repository contains the source code for a Final Bachelor Project that investigates the effectiveness of advertisement placement on user engagement within a content-driven website.

The central research question of this project is: Does the location of an advertisement on a webpage significantly impact its effectiveness when paired with different types of content?

To answer the research question, a custom website was built from scratch. This platform served as a "live lab" to test how real users interact with ads based on their placement and the content they are viewing.

The experiment was designed around three key variables:

1. Content (Stories): The website hosts a diverse collection of stories to engage users.
2. Language: All content is available in both English and Persian, allowing for analysis of user behavior across different linguistic groups.
3. Ad Location: A set of custom-designed advertisements was systematically placed in numerous locations across the website. This included different pages and various positions on those pages (e.g., header, footer, sidebar, embedded within the story text).

This design created a wide variety of combinations, allowing for a comprehensive analysis of which placements performed best.

• Multi-Language Support: A fully functional website serving content in both English and Persian.
• Dynamic Content System: A backend (or static site structure) for managing and displaying a large collection of stories.
• Dynamic Ad Placement Engine: A system for programmatically inserting different advertisements into various, predefined locations on a page.
• (Assumption) Click/Interaction Tracking: A data collection mechanism (likely using JavaScript) to log user clicks on each ad. This system records which ad was clicked, its location on the page, and the story the user was reading, providing the raw data for the effectiveness evaluation.