Hi Streamlit Community!
I’m excited to share a project I’ve been working on: an open-source Streamlit app that helps users identify fake or predatory research papers and journals. As a Software Engineer at Snowflake, I recently investigated the global black market for fake research authorship-a growing problem that impacts academia and even immigration systems.
What does the app do?
- Checks journal metadata and indexing status
- Flags suspicious publication patterns
- Uses machine learning and open datasets to assess legitimacy
- Offers a simple, user-friendly interface for anyone to vet papers or journals
Why did I build this?
During my research, I discovered several international “paper mills” selling authorship in fake journals. This undermines academic integrity and can even be used for visa fraud. I wanted to create a tool that empowers researchers, students, and institutions to quickly check the credibility of research publications.
Try it out!
Live Demo Link
How it works:
- Paste a DOI, journal name, or paper title
- Instantly get a legitimacy score and detailed analysis
- See supporting evidence and links to trusted databases
I’d love your feedback!
- Does the app catch the kinds of issues you’ve seen?
- What features would you like to see next?
- Interested in collaborating or contributing?
Let’s work together to make research more transparent and trustworthy. Thanks for checking it out!
- Abhishek Bakare
- Email: abakre5@gmail.com
Linkedin(LinkedIn](https://www.linkedin.com/in/abhishekbakare/)