Text Analysis for Social Media Cybersecurity: the AMiCA Project

author: Els Lefever, LT³ Language and Translation Technology Team, Ghent University
published: June 6, 2017,   recorded: May 2017,   views: 1527
released under terms of: Creative Commons Attribution (CC-BY)


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


The text analysis part of the AMiCA project (http://www.amicaproject.be), a cooperation between the University of Antwerp and the University of Ghent, developed methods and software to help moderators detect occurrences of unwanted or dangerous situations in their social networks. More specifically, the project developed prototype systems for the detection of cyberbullying, suicide announcements, and sexually transgressive behavior. In this talk I will focus on the text analysis methods that were used for normalization of social media text, for profiling users, and for detecting dangerous content. I will describe the architectures and results of the three resulting applications.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: