A Community Driven Approach for click Bait Reporting

Click baits are primarily used by online content publishers. Their purpose is to allure readers to click on a link and subsequently visit other articles by the same publisher, in order to increase page views and ad revenue. Most of the time click baits are used for pointing to low quality articles or thin content. The user falls into the publishers' trap due to a misleading or incomplete title or content exaggeration. A bait article link might also appear on social network shares or within the search engines result page, the presence of such a link in 3rd party web sites having a negative impact on user experience. Hence, it is important to properly identify and report them. In this paper we present an academic research browser extension meant to be used in the click bait reporting process. The extension offers to users the possibility to explicitly report a click bait, a series of details about the bait link being extracted and logged for further analysis. Based on all the gathered data, our goal is to obtain a community driven click bait samples database that may subsequently be used as an input for different supervised learning algorithms for click bait detection.