@article{e42905ff8c934211825320d07d68811a,
title = "Detecting Clickbait Using User Emotions and Behaviors on Social Media",
abstract = " Clickbait are tabloid news articles which lure online users to click on them, in turn increasing the click-through-rate of the landing page. We build an Emotional Classifier (EC) to detect clickbait articles by leveraging the users{\texttrademark} emotions and behaviors ",
author = "Arjun Kadian and Vivek Singh and Anol Bhattacherjee",
note = "Description Clickbait are tabloid news articles which lure online users to click on them, in turn increasing the click-through-rate of the landing page. We build an Emotional Classifier (EC) to detect clickbait articles by leveraging the users{\texttrademark} emotions and behaviors DOWNLOADS Dec 13th, 12:00 AM Detecting Clickbait Using User Emotions and Behaviors on Social Media Clickbait are tabloid news articles which lure online users to click on them, in turn increasing the click-through-rate of the landing page.",
year = "2018",
month = jan,
day = "1",
language = "American English",
journal = "International Conference on Information Systems",
}