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# ethnograph-view # crosspost
Digital ethnography is the practice of observing and analysing people’s interactions in online environments — such as forums, social media groups, and game communities — to understand their culture and behaviour. This project aims to develop a user-friendly, browser-based tool that supports this process for students, social scientists, and journalists. **crosspost** is a browser-based tool designed to support *digital ethnography*, the study of how people interact, communicate, and form culture in online spaces such as forums, social media platforms, and comment-driven communities.
The project aims to make it easier for students, researchers, and journalists to collect, organise, and explore online discourse in a structured and ethical way, without requiring deep technical expertise.
By combining data ingestion, analysis, and visualisation in a single system, crosspost turns raw online interactions into meaningful insights about how conversations emerge, evolve, and spread across platforms.
## Goals for this project ## Goals for this project
- Collect data ethically: enable users to link/upload text, images, and interaction data (messages etc) from specified online communities. Potentially and automated method for importing (using APIs or scraping techniques) could be included as well. - Collect data ethically: enable users to link/upload text, images, and interaction data (messages etc) from specified online communities. Potentially and automated method for importing (using APIs or scraping techniques) could be included as well.
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Beyond programming, the project involves applying ethical research principles, handling data responsibly, and designing for non-technical users. By the end, the project will demonstrate how computer science can bridge technology and social research — turning raw online interactions into meaningful cultural insights. Beyond programming, the project involves applying ethical research principles, handling data responsibly, and designing for non-technical users. By the end, the project will demonstrate how computer science can bridge technology and social research — turning raw online interactions into meaningful cultural insights.
## Scope
This project focuses on:
- Designing a modular data ingestion pipeline
- Implementing backend data processing and storage
- Integrating lightweight NLP-based analysis
- Building a simple, accessible frontend for exploration and visualisation
# Requirements # Requirements
- **Python** ≥ 3.9 - **Python** ≥ 3.9