Social media platforms present an abundance of
photoshopped images of the perfect body, which
users are repeatedly exposed to and subconsciously
use as a reference point. At the same time, users often
start comparing themselves to the perfect persona on
the internet, rather than to real people with similar
backgrounds. This upward comparison can easily
lead to low self-esteem and self-denial (Festinger
1957). This series of operations is a vicious circle.
3.3 The Unification of Aesthetics and
the Mechanism of Platforms
Algorithmic recommendation mechanisms are
another central pathway to understanding how social
media exacerbates women's body image anxieties.
Based on the feedback mechanism of likes and social
comparisons, recommendation algorithms act as
amplifiers and filters that determine who, what, and
how much you see. Media platforms will calculate
each user's favorite type of video through the user's
time spent on different types of videos, favorites and
comments. Therefore, the platform will recommend
the video content that the user is likely to be interested
in more accurately.
Platforms may build a single aesthetic platform. If
you click on a few videos or notes related to good
body shape, high face value, and slimming, the
algorithm will start pushing similar content over and
over again. Resulting in the illusion that the only
thing in your stream is the perfect and ideal body and
beauty, mistakenly believing that is the mass
standard.
4 IMPROVEMENT METHOD
With the widespread use of digital social media, more
and more women are caught up in body image
dissatisfaction and anxiety. In order to alleviate this
problem at root, not only do we need to raise
awareness at the user level, but we also need to
actively intervene at the technical and ethical levels
of the platforms.
Improving the mechanism of self-objectification
requires efforts from both self-awareness education
and platform content guidance. At the educational
level, it is necessary to enhance the popularization of
the concepts of body neutrality and body positivity,
guiding women to shift their self-worth from beauty
as perceived by others to function, health and true
feelings of the body. At the platform level, it is
necessary to encourage creators to present real,
natural and imperfect body states, and provide
preferential recommendations for such content. For
example, establish real beauty tag recommendations,
launch anti-filter challenge activities, and gradually
break the cultural narrative of beauty equals value
(Simon, et al. 2022) .
Comments, content dwell time, etc. make users'
self-evaluation increasingly dependent on platform
feedback, which in turn influences emotions and
behavioral choices. To alleviate this external
evaluation dependence, changes can be made in two
directions. First, weaken the display weight of public
data. Platforms can allow users to independently
choose whether to display the number of likes or not,
reducing the influence of the single evaluation
criterion of likes equals value. Second, increase the
multi-dimensional evaluation mechanism of content.
The platform can introduce feedback mechanisms for
dimensions such as interesting content, real life and
independence of viewpoints, so that likes are no
longer limited to appearance and aesthetic judgments,
but focus more on value, thought and personality
expression (Cohen 2018). The feedback mechanism
makes the likes no longer limited to appearance and
aesthetic judgment, but more focused on value,
thought and personality expression.
In the social media environment, women are more
likely to engage in up-comparisons, often comparing
themselves to users on the platform who have better
looks, better bodies, and richer lives, resulting in body
dissatisfaction and negative self-perceptions.
Intervening in this mechanism requires addressing
two issues: the selectivity of information exposure
and the unreality of comparison objects.
Platforms should strengthen the mechanism of
pushing diversified content, and include people of
different body sizes, ages, skin colors, and styles in
the recommendation scope, so as to break the single
aesthetic standard. At the same time, the platform
should establish a mechanism for psychological
adjustment and guidance, for example, when
displaying content that may cause comparative
anxiety, it should prompt pop-up tips such as These
pictures may have been retouched and Everyone's
beauty is unique (Choukas-Bradley 2022).
Everyone's beauty has its uniqueness and other pop-
up tips to help users feel more comfortable and
healthier.
The algorithmic recommendation mechanism is
the most insidious yet critical technical factor
affecting body image on current social platforms.
Improving this mechanism requires platforms to
implement mental health protection algorithms, and
once they recognize that users frequently view
content related to body image, cosmetic surgery, and