Skip to content

DetecTroll is an app that was created during 24-hours Hackathon. The main goal of this app is to check tweets added by twitter users for toxicity, insults, profanity, threats such as intention to inflict pain or violence against an individual or group.

License

Notifications You must be signed in to change notification settings

karol-wolski/detectroll

 
 

Repository files navigation

DetecTroll

Project Overview

This is a team project created during the Hack a Troll hackathon, where we received the audience award! 🥇

detecTroll was created to help identify troll accounts on Twitter and raise awareness about toxic behavior on the Internet.

Live demo

http://detectroll.herokuapp.com/

Best viewed on mobile screens, as we didn't have enough time to fully design a desktop UI.

Team

  • Michał Ćwiękała - mentor
  • Krystian Gaczyński - frontend, UI
  • Mateusz Binięda - frontend
  • Karol Wolski - frontend
  • Krzysztof Mackiewicz - backend, API integration
  • Filip Glura - backend

Technologies

APIs

  • Twitter API
  • Perspective API

Frontend

  • React
  • React Router
  • React Hook Form
  • Axios
  • SCSS modules

Backend

  • Express

DetecTroll uses Twitter API to get 3 latest tweets by the specified user and send their content to Perspective API where the messages are evaluated in 4 categories: insult, profanity, threat, toxicity. These values are then used to calculate the total "troll score" and display a custom message, for example "Others may feel threatened by your words!"

Installation

git clone https://github.com/mcwiekala/detectroll.git
npm install
npm run start:dev

About

DetecTroll is an app that was created during 24-hours Hackathon. The main goal of this app is to check tweets added by twitter users for toxicity, insults, profanity, threats such as intention to inflict pain or violence against an individual or group.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 32.8%
  • TypeScript 32.7%
  • SCSS 27.0%
  • HTML 4.9%
  • CSS 2.6%