Paper-Swipe

Photo by Tobias Fehrer

Built on the principles of convenience and efficiency, this tool helps you sift through a substantial list of items - whether they are research papers, articles, blog posts, or anything else - and classify them based on predetermined criteria. It’s like Tinder for research, only more enlightening!

The Power of Rapid Classification

Last winter, while working on a project that required me to classify around 10,000 entries, I yearned for a method to speed up the process. That’s when I conceptualized this tool, a platform as accessible as a website, and as simple to use as swiping left or right. I even found myself classifying entries while waiting in line at the bakery. It’s that versatile!

The Mechanics

You feed the tool a list of items you want to classify. This list can be structured in an Excel spreadsheet with columns like title, abstract, year, ID, type, and source. You also define your classification structure. For instance, ‘Relevant: Yes/No/Maybe,’ ‘Artefact: Yes/No,’ ‘Focus: Design Time/Run Time.’

Once this setup is done, you can start swiping! Just like Tinder, swipe left for ‘No’, and swipe right for ‘Yes’. You can save your classification as soon as you swipe or click one of the buttons. Personalization

The tool can also be tailored to your specific needs. You can set up keywords you want to be highlighted, specify the sort order of items, and even decide if you want to classify all items independently or collaboratively.

The end result? A simplified and organized classification structure that saves you countless hours and provides you with a solid foundation for your research analysis. Ready to Get Started?

I hope paper-swipe will streamline your research process and make it more enjoyable, just like it did for me. If you’re interested in trying it out or need help setting it up, don’t hesitate to reach out! Happy classifying!

Tobias Fehrer
Tobias Fehrer
Doctoral Candidate in IS

Within my research, I focus on topics in data-driven business process management in general and on process mining in particular.

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