It’s been a long time coming and I feel that the time is right
What I mean is that I’m leaving university…after I hand in the rest of my deadlines and sit my final exams
(and the lease of my extortionate
accommodation runs out).
Essentially, I’m leaving university because in less than three months I will have completed my degree.
If you’re feeling slightly underwhelmed, it may be due to the fact I just clickbaited you.
What is clickbait?
This is any form of strategically devised content such as a headline, title, image or caption which lures us to click on a link to a particular piece of internet content. Oxford dictionary defines it as ‘content whose main purpose is to attract attention and encourage visitors to click on a link to a particular web page’ (Oxford Dictionary, n.d.).
The key to consider is the centrality and nature of the baiter’s intent. Clickbait can be plainly deceptive, or less Machiavellian and what some commentators have called ‘creative hyperbole’ where baiters utilise creative licence or exaggeration to encourage engagement with a post (Connell, 2017).
Clickbaiting on Youtube
Youtube is one of the social media platforms where the (omni)presence of click-baiting has resulted in much discussion and at times, vitriol towards the tactic. In this video-rich context content creators aim to incite Youtube audiences to click and watch their videos thoroughly to increase advertising revenue and likelihood of higher ranking on Youtube’s search engine. The aim of many channels is to increase the number of video viewers and eventual subscribers who are individuals who have expressed the desire to be alerted about further uploads as and when they occur. This is key as viewership and subscriber-counts translate to a channel’s influence which is a kind of digital currency which can be utilised by content creators to secure promotional deals and product partnerships with companies who contribute to their financial income.
Importantly, Youtube’s algorithm promotes videos which quickly receive a high volume of clicks after uploading to its trending page (TV TWO Team, 2017; Dean, 2018). As you may already be able to see where this is going, Youtube has become a hotbed for clickbait video titles and thumbnails due to the issues seen in the flow diagram below:
Clickbait on Youtube typically operates through strategically devised video titles and complementary thumbnails and is present across genres e.g. from gaming to beauty channels as well as in lifestyle, daily vlog circles.
Observe a few examples below:
An intriguing title for makeup lovers
'Challenge-accepted’ inducing videos for football-heads
To a title which turned out to be entirely untruthful – although notably, the vlogger was presenting an important reflection on the burden of enduring hate from online trolls.
How does clickbait work?
To achieve engagement, clickbait titles and thumbnails utilise the method of framing coined by Tversky and Kahneman (1981). This is where the construal of a particular option as causing a greater loss than gain, exploits the human tendency towards loss aversion and leads them to select the other option. Asch (1952) noted decades prior to this that individuals’ response to an object is determined by its construal, not by personal beliefs held about the object. Specifically, clickbait titles and their accompanying thumbnails often imply that a viewer will be missing out on extremely interesting or generally vital information if they do not click and watch a video and so even if the viewer is acquainted with these tactics, loss aversion operating under the guise of curiosity kicks in, we fall prey and we click. There is also the idea of 'misleading inference', identified by Pratkanis (2007). This refers to a mechanism at play in all clickbait attempts as they intentionally rely upon inferences or assumptions which are reasonably made from the bait provided, which are however, not accurate.
The final example above goes so far as to operate on viewers’ consciousness of potential loss of the content creator’s presence on Youtube (an effective ploy even if not personally invested in the Youtuber i.e. if not a subscriber).
Why does it work?
Familiarity with the ploy of clickbait does not seem to affect people’s likelihood to click videos where titles are suspected to be misleading: these videos still garner huge view counts – perhaps due to differing reasons for subscribers compared to non-subscriber viewers:
For subscribers of channels uploading clickbait material, the mere exposure effect (Zajonc, 1968) where individuals increase in liking ratings of objects/individuals because they become familiar to them may be at play, leading people to click videos as they like the individual and would watch anyway. The issue of commitment may also influence this as the decision to subscribe to a channel implicitly leads to desires to act in ways consistent with this choice, perhaps leading to abiding by expectation to click irrespective of feelings towards clickbait methods. Findings by Sherman (1980) relating to the impact of prior commitment to volunteer for the American Cancer Society on follow-through rate support this idea.
For general non-committed Youtube users, Muchnik, Aral and Taylor (2013) provide a reason for susceptibility being increased dependence on the online aggregated view of others which affects our decision-making. This introduces the notion of view counts acting as a means of social proof, a concept examined by Cialdini (2009) and defined as when individuals look to the behaviour of others to justify or offer direction for their own. Two key principles which most affect the operation of social proof are situational uncertainty and similarity with relevant others. In this case, determining whether to view a clickbait video is affected by the ambiguity of video title/thumbnail (thoughts such as ‘is this legit?’ and ‘pfffrt no way will I really cry if I watch this’ may be the last to cross the minds of baited clickers). Choosing whether to watch is also affected by observing what similar others are doing (Festinger, 1954) and this can be ascertained by simply looking at view counts relative to video upload-date or checking the trending videos section.
This is supported by a study by Salganik et al. (2006) in which researchers demonstrated the strength of social influence in determining musical success. An artificial online music market was created where over 14,000 participants were allocated to one of two groups: one where information on the music download choices of others would be available, and another without this information. Both groups were provided with the names and band names of 48 songs and individuals were then asked to select songs to listen to, rate how much they liked the songs and download them if they wished. Songs which appeared to have been favoured by previous listeners (measured by download count) grew in popularity compared to less favoured songs, providing further support for the effect of social consensus influencing decision-making.
So, the next time you’re on Youtube and find yourself itching to click a video you can just tell is clickbait, why not take on the challenge and:
Asch, S. E. (1952). Group forces in the modification and distortion of judgments.
Clickbait (Def. 1] (n.d.) In Oxford Dictionaries Online, Retrieved March 20, 2018 from https://en.oxforddictionaries.com/definition/clickbait
Connell, A. (2017, September 28). James Charles took clickbait too far and freaked fans TF out. Retrieved from http://www.revelist.com/bloggers/james-charles-youtube/9646
Dean, B. (2018, February 20). YouTube SEO: How to Rank YouTube Videos in 2018. Retrieved from https://backlinko.com/how-to-rank-youtube-videos
Festinger, L. (1954). A theory of social comparison processes. Human relations, 7(2), 117-140.
Matsakis, L. (2017, June 22). Inside the Strange World of YouTube Thumbnails. Retrieved from https://motherboard.vice.com/en_us/article/zme97a/inside-the-strange-world-of-youtube-thumbnails
Muchnik, L., Aral, S., & Taylor, S. J. (2013). Social influence bias: A randomized experiment. Science, 341(6146), 647-651.
Pratkanis, A. R. (2007). Social influence analysis: An index of tactics. The science of social influence: Advances and future progress, 17-82.
Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006). Experimental study of inequality and unpredictability in an artificial cultural market. science, 311(5762), 854-856.
Sherman, S. J. (1980). On the self-erasing nature of errors of prediction. Journal of personality and Social Psychology, 39(2), 211.
Team, T. V. T. W. O. (2017). Establishing a Blockchain-Based Open Platform for the Television Ecosystem. Retrieved March 20, 2018 from https://tv-two.com/TV_Whitepaper.pdf
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453-458.
Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of personality and social psychology, 9(22), 1.