Difference between revisions of "Clickbait"
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==Backlash== | ==Backlash== | ||
| − | Social media | + | Social media websites have recognized the issues surrounding clickbaits and have made several attempts to be able to recognize them quickly and prevent them from gaining popularity. Facebook has recognized the problem and has made efforts to improve their newsfeed to "help people find the posts and links from publishers that are most interesting and relevant, and to continue to weed out stories that people frequently tell us are spammy and that they don’t want to see." <ref name="TWP">The Washington Post website: "What is ‘click bait’ and why Facebook wants to display less of it" https://www.washingtonpost.com/news/technology/wp/2014/08/26/what-is-click-bait-and-why-facebook-wants-to-display-less-of-it/?utm_term=.eccfff2e28b8</ref>. Facebook has created a system that detects clickbaits by identifyng phrases that are commonly used in clickbait headlines<ref name="Facebook">Facebook newsroom website: "News Feed FYI: Further Reducing Clickbait in Feed"http://newsroom.fb.com/news/2016/08/news-feed-fyi-further-reducing-clickbait-in-feed/</ref>. Other scholars have developed clickbait detection models and extensions to further help decrease how often they appear.<ref>Potthast, Martin; Köpsel, Sebatian; Stein, Benno; Hagen, Matthias (2016). ClickBait Detection Bauhaus-Universität Weimer</ref><ref>Abhijnan Chakraborty, Bhargavi Paranjape, Sourya Kakarla, Niloy Ganguly (2016). Stop Clickbait: Detecting and preventing clickbaits in online news media IEEE Xplore Digital Library</ref>. |
==Types== | ==Types== | ||
Revision as of 05:29, 19 February 2017
Clickbait refers to a certain kind of web content advertisement that is designed to entice its readers into clicking an accompanying link, they are usually found in social media sites in the form of short teaser messages [1] that are designed to attract the attention of people. They encourage people to click on them without giving much information about what the reader is going to find next and are often filled with stories that are fake, opinion-based, with little-to-no research done to back up the author’s points.[2][3][4]. Online news media outlets rely heavily on page views to generate ad revenue and use clickbaits to increase the amount of people that visit their page [5][6]. The presence of clickbait in social media create many ethical concern as they threaten to clog up social media channels, spreading misinformation, and creating controversy [7][8]
Backlash
Social media websites have recognized the issues surrounding clickbaits and have made several attempts to be able to recognize them quickly and prevent them from gaining popularity. Facebook has recognized the problem and has made efforts to improve their newsfeed to "help people find the posts and links from publishers that are most interesting and relevant, and to continue to weed out stories that people frequently tell us are spammy and that they don’t want to see." [2]. Facebook has created a system that detects clickbaits by identifyng phrases that are commonly used in clickbait headlines[9]. Other scholars have developed clickbait detection models and extensions to further help decrease how often they appear.[10][11].
Types
References
- ↑ Potthast, Martin; Köpsel, Sebatian; Stein, Benno; Hagen, Matthias (2016). ClickBait Detection Bauhaus-Universität Weimer
- ↑ 2.0 2.1 The Washington Post website: "What is ‘click bait’ and why Facebook wants to display less of it" https://www.washingtonpost.com/news/technology/wp/2014/08/26/what-is-click-bait-and-why-facebook-wants-to-display-less-of-it/?utm_term=.eccfff2e28b8
- ↑ Tech Crunch: "*** is a clickbait "https://techcrunch.com/2016/09/25/wtf-is-clickbait/"
- ↑ Click Bait Websites and the Age of Misinformation "https://jordandetmers.com/2014/09/11/click-bait-websites-and-the-age-of-misinformation/"
- ↑ Chakraborty, Abhijnan; Paranjape, Bhargavi; Kakarla, Sourya; Ganguly, Niloy (2016). Stop Clickbait: Detecting and Preventing Clickbaits in Online News Media Cornell University Library
- ↑ The dirty secrets of clickbait. This post will blow your mind! "https://econsultancy.com/blog/64399-the-dirty-secrets-of-clickbait-this-post-will-blow-your-mind/"
- ↑ Potthast, Martin; Köpsel, Sebatian; Stein, Benno; Hagen, Matthias (2016). ClickBait Detection Bauhaus-Universität Weimer
- ↑ Click Bait Websites and the Age of Misinformation "https://jordandetmers.com/2014/09/11/click-bait-websites-and-the-age-of-misinformation/"
- ↑ Facebook newsroom website: "News Feed FYI: Further Reducing Clickbait in Feed"http://newsroom.fb.com/news/2016/08/news-feed-fyi-further-reducing-clickbait-in-feed/
- ↑ Potthast, Martin; Köpsel, Sebatian; Stein, Benno; Hagen, Matthias (2016). ClickBait Detection Bauhaus-Universität Weimer
- ↑ Abhijnan Chakraborty, Bhargavi Paranjape, Sourya Kakarla, Niloy Ganguly (2016). Stop Clickbait: Detecting and preventing clickbaits in online news media IEEE Xplore Digital Library
