IEEE Technology and Society Magazine - March 2020 - 63

after playing an online game continuously for 50 hours.
A study of Massively Multiplayer Online Role Playing
Games players in [7] reported that the average player
spent 35 hours per week in the game, clearly at the detriment of other activities in real life.
China is another country strongly affected by Internet
overuse. A Chinese 17-years-old who played an online
game for 40 hours straight suffered a stroke [9]. Another
Chinese teenager committed suicide because he found it
unacceptable to spend so much time playing online
games, yet could not stop. The Guardian estimates that
24 million young Chinese are addicted to Internet games
[9], out of a population of 750 million users, 23.4% of
which are under 19 years old [10]. Another heart-wrenching story is that of a Chinese girl who was committed to a
center for treating IA, escaped, and brutally murdered her
mother in retaliation for the electroshock therapy she suffered at the treatment center [11]. The range of virtual
worlds and sites available online is compelling, and many
of them target young users: Goltz [7] reported more than
150 virtual worlds for teens and preteens, including 88
worlds for 8-12 year olds and 72 for children younger
than 7. While these statistics are for online games, not for
SM use, Internet games have a strong social component
and solutions proposed for Internet gaming might have
applicability to SM addiction as well.
Like other types of addiction, SM addiction tends to
disproportionately affect certain groups, some that are
already more vulnerable. A survey of 23 500+ Norwegians [12] found that SM addiction is most highly correlated with low self-esteem, with being a woman, with
narcissism, and with being younger. Other authors have
pointed out that the gender correlation might not be a
true indicator, but only a false alarm, given the predominantly female respondent population in SM surveys,
motivated in part by the higher willingness of women to
participate in such studies [13]. For teens with IA, SM
addiction is the main concern among girls, while boys
are also likely to be addicted to online pornography [13].
Still other authors did not find a correlation between
Facebook addiction and age or gender [14].
Compared to Internet gaming, there are not as many
statistics on SM addiction, and no stories as gruesome
as those above. It is estimated that 24% of teens are
online continuously, thanks to mobile devices that are
always on and always in the owner's possession [13].
Among teens, 71% use more than one social media platform. Social media addiction prevalence ranges widely,
depending on the study, from as low as 2.8% to as high
as 46% even when measured only among college students [13]. Other authors cite narrower ranges, 2.6-
10.9% [15]. A national study of 6664 youth SM users in
Hungary found that 6.83% did not use the Internet or
SM. Of the remaining users, another 3.72% submitted
MARCH 2020

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surveys that were incomplete or inconsistent. Finally, of
the 5961 users of SM with usable responses 78.3% were
classified as "no risk," 17.2% as "low risk" and only 4.5%
as "at-risk." Despite of the almost perfect gender balance
in the survey group, the at-risk group was strongly biased
to females, at 58.8% [13].

Is excessive time spent online
and on social media truly an
addictive behavior?
Even within SM addiction there is yet to be agreement
on terminology [13], scope, or ways to measure or diagnose it [4]. The Bergen Social Media Addiction Scale
(BSMAS) [12] is one of the most well-established ways to
measure addiction to SM. BSMAS was derived from an
earlier Bergen Facebook Addiction Scale, which in turn is
only one of several measures reported for measuring
Facebook addiction [16]. The complications arise
because Facebook use and SM use have some commonalities, but some areas where they do not overlap.
Because Facebook users can play games, can gamble,
watch videos or can connect socially, Facebook addiction
includes SM addiction as a subset. At the same time, SM
addiction includes excessive use of other non-Facebook
SM sites, including Twitter, Instagram, and Snapchat [16].
Other researchers have pointed out that SM addiction is
complemented by or is a facet of nomophobia (the fear of
not having one's mobile home handy) [17].

How We Got Here: Designing for Addiction
Part of the reason for these sad statistics of Internet
overuse and abuse is the fact that online media are
designed to be addictive. The revenue model online is to
offer free or reduced-price content in exchange for page
views that lead to advertising revenue. As such, websites
and mobile apps are optimized for increasing "stickiness" - keeping the viewers online for longer and moving them through more pages. In 2018, YouTube had
more than 1.5 million users who watched more than a
billion hours each day, ten times more than they
watched in 2012 [18]. A critical factor in this increased
viewing time is a personalization algorithm that recommends and cues up the next video, shortly before the
user is done watching the current one. The company
estimates that more than 70% of viewing time is driven
by the recommendation algorithm. In some cases,
researchers have found that the recommendations lead
users to extreme content, even for users with moderate

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IEEE Technology and Society Magazine - March 2020

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