Can Machine Learning Help Identify Radicalization Among Students?
Student radicalization on college campuses is a growing concern, with the same processes happening even in high schools now. Education institutions often are wonderful places for lively discussion about the world, however at times students can become ill informed via online spaces. While computers are supposed to be used in such institutions for educational purposes, students often surf the web there. There are also cases where personal devices (laptops and mobile devices) are used at school for browsing activity. What would seem like a harmless activity may be isolating, polarizing, and radicalizing students.
Numerous studies over the years have concluded the speed at which people can become polarized online. Researchers from the Kellogg School of Management in collaboration with the IMT School for Advanced Studies Lucca produced a comprehensive study of Facebook and YouTube users. What they discovered was the speed at which people became polarized, which was often at their 50th like or comment. YouTube and Facebook are just two places students visit and fall into ideological silos. Twitter, Reddit, Tumblr, and many other social spaces are breeding grounds for radicalization. Thankfully as technology is advancing, identifying and preventing radicalization may become more streamlined. >> Click to Continue reading on Education Technology Insights