Have I Shared Fake News? - Shiny Contest Submission

Have I Shared Fake News?

Authors: Steve Rathje

Abstract: Have you shared fake news on Twitter? "Have I Shared Fake News" is a Shiny App that will tell you! It will also tell you how many right-leaning, left-leaning, or hyper-partisan/low-quality news sites you have shared. You can share your fake news "score" with your friends, see how much fake/low-quality websites that other people with public Twitter handles have shared, and see a list of the fake news "scores" of all US congress-members. Additionally, you can receive feedback on the amount of positive, negative, polarizing, and moral language you have used on Twitter.

Full Description: Have you shared fake news on Twitter? The Shiny app "Have I Shared Fake News" will tell you!

It will also tell you how many right-leaning, left-leaning, or hyper-partisan/low-quality news sites you have shared.

You can also see how much fake/low-quality news other people with public Twitter handles have shared.

On one page of the app are the fake news "scores" of all US congress-members:

Additionally, you can see the kind of language you've used on your Twitter profile (e.g., positive, negative, moral-emotional, or polarizing).

Using the app "Have I Shared Fake News?" will also help us conduct research on social media if you consent to participating in our study, though you may also use the app without having any data stored if you choose.

We hope this app helps you learn about your social media news diet and share content that aligns with your values. You can also share your social media "reputation" with your friends, and hopefully encourage others to share more thoughtful content online.

For more information, see this Twitter thread: https://twitter.com/steverathje2/status/1391803584262643712?s=20


Keywords: Twitter, Social Media, Misinformation, Education, Research
Shiny app: Have I Shared Fake News?
Repo: GitHub - stevesteve2/HaveISharedFakeNews: ShinyApp
RStudio Cloud: RStudio Cloud

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4 Likes

commendable work ! what are the parameters to filter fake news

Have a look at the repo. The methodology is implemented there. The dictionaries show how sites and words get categorized.