Open Steam in a browser, navigate to your "All Games" page, and use the Developer Console (Ctrl+Shift+J) to run a script that extracts the titles into a downloadable text block.
For papers involving statistics (e.g., price trends or genre distribution), tools like Excel or Python's Matplotlib are great for turning that huge text list into readable charts. Download STEAM HUGE LIST txt
Sites like SteamDB track this information. For a pre-formatted research dataset, check platforms like Kaggle for "Steam Store Data," which often includes titles, tags, and reviews in .csv or .txt format. 2. Exporting Your Personal Steam Library Open Steam in a browser, navigate to your
Huge lists often contain "hidden" entries like soundtracks or legacy tools. You may need to filter these out using a script or spreadsheet software to focus on actual games. For a pre-formatted research dataset, check platforms like
You can use the Steam Backlog Organizer on GitHub to download your library directly into a .csv file. 3. Developing Your Paper
When using this data in an academic paper, keep these tips in mind:
Attribute your data source. If using the API, cite Valve's Steamworks Documentation .