THE IMPACT OF SOCIAL MEDIA ON ADOLESCENT ATTACHMENT STYLE FOR

GENERATION Z

Dissertation presented to the Faculty of the

California School of Professional Psychology

Alliant International University

San Francisco

In partial fulfillment of the requirements for the degree of

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Doctor of Psychology
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Éva Maria Nicolas, M.A.

Approved by:

Pauline “Polly” Lytle, Ph.D., Chairperson

Christy Hobza, Psy.D., Reader

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©Éva Maria Nicolas, 2019

Dedication

Je dédie ce mémoire à mon Papi “Wifi,” qui n’ai jamais cessé de s’instruire sur les

tendances modernes, afin de garder l’esprit jeune, et de rester en contact avec ses petites filles.

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Abstract

Today’s adolescent population, Generation Z, has the unique circumstance of growing up in the

digital age, without having known a time when the Internet and smart devices did not exist. The

interplay of online versus offline dynamics adolescents experience in their developmental

exploration of self and peer attachment relationships was examined in the present study. Study

findings showed that social media serves as an extension of offline relationships for adolescents

who have friends in the real world and provide endless possibilities for peer connection for

adolescents who have difficulties making friends face to face. Key characteristics of friendships,

including validation, self-disclosure, companionship, and instrumental support, can occur in

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equally effective and satisfying ways offline and online; however, there is a gap in the research
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on the implications of conflict and conflict resolution online. Another key finding was that

parental use of digital devices in the presence of their adolescent children can have detrimental
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affective outcomes for adolescents’ well-being and their attachment with their parents.
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SOCIAL MEDIA AND ADOLESCENT ATTACHMENT STYLE v

Table of Contents

Dedication iii

Abstract iv

CHAPTER I. Introduction 1

Problem Statement 3

Purpose Statement 5

Significance Statement 5

CHAPTER II. Literature Review 7

Key Concepts and Their Histories 7

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App 7

Consumption versus participation

Viral 11
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Emoji 12

Meme 13
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Selfie 13

Hashtag 16

FOMO 17

Influencers 18

Cyberbullying 19

Adolescent Social Media Use and Online Behaviors 21

Snapchat 22

YouTube 24

Instagram 26
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Facebook 31

TikTok 32

Discord 34

Twitter 35

Recruitment Via Social Media 36

A Biopsychosocial Examination of Gen Z 37

A Cultural Consideration of Gen Z 39

Adolescent Attachment in the Social Media Age 42

Attachment theory 42

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Attachment in adolescence 45
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Adolescent attachment on social media 50

Self-disclosure 51
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Validation 52

Companionship 53
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Instrumental support 53

Conflict 54

Conflict resolution 54

Social media and loneliness 57

Parental use of social media 60

Adolescent attachment and cyberbullying 63

Attachment implications of terrorist recruitment via social media 65

CHAPTER III. Method 66

Objectives 66
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Methods 68

Search terms 68

Results 69

Limitations 70

Delimitations 71

CHAPTER IV. Results 72

Research Question 1 72

Research Question 2 77

Research Question 3 83

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CHAPTER V. Discussion and Conclusion 87

Social Implications
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Clinical Implications 89
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Research Implications 91

Conclusion 93
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References 95
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CHAPTER I

Introduction

Adolescents and preadolescents born after 1995 represent 25% of the U.S. population,

and are referred to as Generation Z, Gen Z, Gen Zers, or the postmillennial generation (Homan,

2015; Kingston, 2014). Other expressions associated with Generation Z include iGeneration, Gen

Tech, Net Gen, and digital natives (Junco & Mastrodicasa, 2007). Gen Z is the term used in the

present study. Gen Z is inherently technologically savvy as they do not know a time before the

Internet (Twenge, 2017), and today, 95% of U.S. adolescents have access to a smartphone (M.

Anderson & Jiang, 2018). The result is a generational divide between Gen Zers and their digital

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immigrant parents (Homan, 2014). Digital immigrants are individuals born before 1985, who
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therefore experienced an adjustment to the ubiquitous use of technology in their every-day lives

(Hayes, 2019). Additionally, individuals who did not grow up using Internet technologies, for
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instance from rural areas, or underdeveloped countries, can also be considered digital immigrants

when the technologies become available to them (Hayes, 2019). For the first time in history,
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adolescents know more about the Internet and technology than their caregivers (Tapscott, 1998).

The prevalence of social media in adolescents’ activities of daily living is undeniable. In

findings from the 2018 Pew Research Center study on adolescents’ social media habits and

experiences (ages 13 to 18 years), 81% of adolescents indicated that social media made them feel

more connected to their friends and to what is going on in their lives, and 68% felt supported by

their friends during tough times. Additionally, adolescents tend to have positive emotional

associations with their social media use, with 71% describing feeling included and 69% reporting

feeling secure in their online experiences (M. Anderson & Jiang, 2018). Other findings suggest

that adolescents’ feelings of loneliness have steadily increased since 2013 as they spend more
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time on their smartphones and less time having in-person interactions (Twenge, 2017). A

significant socioemotional step in adolescence involves the maturation of friendships and the

formation of peer attachments (Moretti & Peled, 2004). Today, this developmental stage appears

to have a significant digital component. The implications of social media on the solidification of

adolescent friendships and peer attachment were the focus of the present study.

According to a Kaiser Family Foundation study, the amount of time spent consuming

media steadily increased by 1 hr 17 min between 2004 and 2010 for youth ages 8 to 18 years

(Lamontagne & Singh, 2010). Today, adolescents spent an average of 10 hr per day online, and

76% keep their phones within reach while they sleep (Asurion, 2019; Mediakix, 2019a). Some

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adolescents have noticed and acknowledged a hyperconnection to their devices, with 54% stating
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that they feel they spend too much time on their mobile devices and 45% admitting to being

online almost constantly (M. Anderson & Jiang, 2018). The Pew Research Center’s 2018 study
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on teens, social media, and technology showed that 72% of adolescents checked their phones for

notifications as soon as they woke up, and 57% felt that they must respond to messages
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immediately. Similarly, 56% of participating adolescents reported feeling anxious, upset, or

lonely when they do not have their phones on them. Findings also showed that 52% of U.S.

adolescents have taken measures to cut down their mobile phone use while 57% have attempted

to curb their social media use (M. Anderson & Jiang, 2018).

Parents across gender, race, ethnicity, and income levels have expressed their concerns

about their adolescents’ screen time, and 57% have reported setting time restrictions.

Additionally, parents tend to perceive their own use of digital technologies as insignificant in

comparison to their adolescent child’s and typically believe they model appropriate use of

mobile devices in the home (McDaniel, 2019). However, 51% of adolescents reported their
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parents being distracted by their own phones at least sometimes during conversations, and 14%

of adolescents felt their parents were often distracted by their phones during verbal exchanges

(Jiang, 2018). This novel form of parental distraction caused by digital technologies has been

identified as technoference (McDaniel & Coyne, 2016). Researchers have discerned various

implications related to parental use of technology in the home, namely its negative effects on the

quality of parenting and parental attachment (McDaniel, 2019) and the quality of parent–child

interactions (Straus, 2019). In the present study, I explored the emerging role of digital

technologies in the family system and whether it interferes with adolescents’ abilities to use their

primary attachment as a base from which they can explore peer relationships and form new

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attachments.

Problem Statement
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A 2018 Asurion consumer survey showed that Americans check their phones 80 times
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per day on average, or once every 12 min (Asurion, 2019). Additionally, 1 in 10 people look at

their phones every 4 min. What motivates individuals to use social media? The uses and
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gratification theory (Whiting & Williams, 2013) identifies 10 categories of purposes and

gratifications experienced by social media users: social interaction, information seeking, passing

time, entertainment, relaxation, communication, convenience, expression of opinion, information

sharing, and surveillance or knowledge about others. In other words, mobile Internet and social

media fulfill many needs in a near-constantly accessible manner.

Terms such as social media addiction (Griffiths, 2000), FOMO (fear of missing out;

Przybylski, Murayama, DeHaan, & Gladwell, 2013), and social media anxiety disorder have

joined the dialogue surrounding social media use, introducing the harmful consequences of

digital connections (Spira, 2013). An increasingly pathologizing vocabulary has been employed
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in the depiction of social media-related anxieties such as post-posting traumatic stress disorder,

obsessive-compulsive reloading disorder, and Twitter rage (Spira, 2013). However, the majority

of these concepts have yet to be empirically studied, and their impact on adolescent mental

health and psychosocial development remains largely unknown.

There is a growing interest in the field of psychology regarding the behavioral and

emotional implications of prevalent social media use in adolescence. Some implications

identified to date include diminished sleep, body image issues, social isolation, self-harming,

attention seeking, eating disorders, anxiety, and depression (Kelley, Schrochet, & Landry, 2004;

Twenge, 2017). Neuroscientist Adam Gazzaley and psychologist Larry D. Rosen (2016)

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explained that the increase in access to mobile devices and the expectation for immediate
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responses can deteriorate attention span and impact productivity, mental health, and stress levels.

A 2015 Microsoft study in which electroencephalography was used to monitor brain activity
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showed that individuals’ average attention span decreased from 12 s in 2002 to 8 s in 2013

(Gausby, 2016). Researcher Bruce Morton refuted these results, suggesting that human attention
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has adapted and is allocated differently as a result of evolving technology and increased exposure

to information. He stated, “Digital technologies dovetail seamlessly into the information

processing abilities of our brain” (Morton, as cited in Hooton, 2015, p. 2). A 2015 Microsoft

study also showed that individuals are now better at multitasking (Hooton, 2015). Harvard

pediatrician Michael Rich explained that youth brains are rewarded for not staying on task and

for jumping to the next thing. In other words, multitasking is a misleading description for

neurological adaptation toward faster working memory and improvements of fine motor skills

(Kingston, 2014). In 2013, a tentative diagnosis, Internet gaming disorder, was added to the fifth
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edition Diagnostic and Statistical Manual of Mental Disorders appendix pending further

research (Kuss & Griffiths, 2011).

As adolescents spend a large majority of their day on their smartphones, researchers have

begun to examine whether friendship quality and perceived relationship satisfaction are

comparable between the online and offline realms of interactions and whether attachment style

mediates preferences for one or the other (Buote, Wood, & Pratt, 2009). Such research is

particularly relevant for Gen Z adolescents whose peer relationships develop both online and in

person and whose attachment transfers from their parents to their friends (Doherty & Feeney,

2004).

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Purpose Statement
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The purpose of this literature review was to investigate the impact of adolescents’ social

media use on their formative development of self and peer relationships. A review of the current
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literature served to determine the current standing in the field of psychology regarding the

development of adolescent attachment styles and peer relationships in the digital era. I sought to
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bridge the gap in the research between these two concurrent concepts by examining the

following questions:

1. Can adolescents form meaningful and long-lasting attachment relationships in an age

where digital interactions are ubiquitous?

2. Can adolescents develop authentic self-concepts in an environment of judgment?

3. Do social media foster adolescent detachment from their parents?

Significance Statement

Adolescence is the transitional stage of development between childhood and adulthood. It

is deemed a unique and formative phase in social, emotional, and personal development (World
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Health Organization [WHO], 2019). During this period, habits for emotional well-being are

formed, including sleep hygiene and exercise, along with developing skills for problem solving,

coping, emotion management, and interpersonal relationships. According to the WHO (2019), 1

in 5 adolescents is impacted by mental health issues, which oftentimes go undiagnosed. As a

result of parental allowances, adolescence also involves increased independence (Nauert, 2018),

which gives youth opportunities to develop new friendships and foster existing ones. The

solidification of peer relationships outside of the family structure helps adolescents explore the

balance between autonomy and relationships (Nauert, 2018). Attachment style is a concept

delineated by social psychologists that describes the various paths individuals can take to

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understand their sense of self and others while informing their development of social skills and
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friendship building (Bartholomew & Horowitz 1991; Moretti & Peled, 2004) as well as

emotional closeness (Zimmerman, 2004), social competence, cooperativeness, and conflict

As personal issues arise with the increased digitalization of social interactions, it is

important for mental health professionals to be at the forefront of these trends in order to better

support their clients. This literature review provided background information that can serve as

psychoeducational tools for psychologists to use with their adolescent clients and with parents,

teachers, and other individuals who work closely with the adolescent population during this

period of interpersonal growth and transitions. As Gen Z adolescents extend their peer

attachment relationships online, their caregivers, who remain important guiding figures, must

have an understanding of social media’s interpersonal dynamics.

CHAPTER II

Literature Review

The following chapter includes key terms commonly employed in the context of

adolescent social media use, along with their historical background. Additionally, I describe the

seven predominant social media platforms adolescents use and explore the online behaviors

specific to Gen Z for each of them. Next, I discuss adolescent attachment style, first from a

theoretical framework, then specific to the adolescent developmental stage. Finally, I examine

the implications of adolescent attachment styles in the social media age. Three noteworthy

themes emerged from the research regarding the adolescent experience of growing up in the

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digital age: loneliness, parental use of social media, and cyberbullying. I also review each in this

chapter.
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Key Concepts and Their Histories
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App. This term is an abbreviation for the word application, and it refers to software

programs that run on computers, smart televisions, or mobile devices such as phones, tablets, and
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smart watches (Karch, 2019). The three types of apps are desktop, mobile, and web. While some

apps are only coded for one platform, others such as Google’s Gmail app exist across all three

types. Those that already exist on a device are called native apps and include messaging, music

libraries, etc. Third-party apps are those not built by device manufacturers or their software

creators. They can be downloaded from an app store associated with the device’s brand

(Midrack, 2019). The purpose and functions of apps are as endless as the human creative

potential and include shopping, photo editing, gaming, social media, mental health support, and

education.
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When using an app for the first time, users are typically asked to enter personal

information such as their name, date of birth, and gender prior to gaining access to its features.

Additionally, apps track and gather digital footprints or “digital shadows,” which inform users’

interests, digital interactions, locations visited, and even health information (Gutermuth, 2017).

The prevalent “freemium” business model for the mobile ecosystem, where revenue is achieved

through in-app advertising, involves third-party trackers that embed their technology into native

apps, in turn selling user data to digital advertisers (Ram, Wisniewska, Kao, Rininsland, &

Nevitt, 2018). According to a 2017 study of 1,000,000 apps from Google’s Android store, 90%

were designed to share user data back to Google, while the median app could share data to 10

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different third parties, and 1 in 5 apps could do so with more than 20 third parties (Binns et al.,
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2018). This model has raised concerns about users’ rights to privacy and the lack of transparency

regarding what users are giving consent to by agreeing to a terms of service agreement.
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In a 2018 study of 543 undergraduate students, Obar and Oeldorf-Hirsch sought to

determine how often users ignore terms of service and privacy policy when agreeing to them.
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Participants’ average age was 19 years. They were given industry standard-length agreements to

read through (the privacy policy should have taken the average adult 29 to 32 min, and the terms

of agreement 15 to 17 min) prior to joining a decoy social media app. To gauge participants’

views and attitudes toward terms of services on commonly used apps such as Facebook and

Gmail, among others, they were asked to identify how many minutes they typically spend

reading by selecting from several time brackets. Four Likert-type scale items were used to

measure behaviors, and 16 paired items assessed their views on privacy policies. Results

indicated that 74% of the participants opted for a “quick join” function in lieu of reading the

privacy policy, and those who did not had an average read time of 73 s with 97% agreement
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rates. Concurrently, the average reading time for the terms of service was 51 s with 93% consent.

A full 98% of participants did not see the “gotcha” clause in which users agree to share data with

the National Security Agency (NSA) and provide their “first-born child” (Obar & Oeldorf-

Hirsch, p. 12) as payment to access the social media site. Results from the self-report measure in

the study revealed that a large majority of users value privacy. However, they view policy

agreements as a time-consuming nuisance, and their behaviors suggest they do not read through

terms of service. By agreeing without reading these terms, adult users are unable to provide

informed consent. This raises additional concerns for younger populations, who are more eager

to gain access to apps. Future research focused on the risks associated with adolescent behaviors

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regarding privacy security is needed.
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Consumption versus participation. Social media allow users to interact with online

content in various ways according to their individual needs, preferences, purposes, and
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gratifications (Whiting & Williams, 2013). Passive users are those who view content without

“liking” or commenting on it themselves; they are considered consumers of media (G. Khan &
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Vong, 2014). On the other hand, active users are those who engage with content with a like, a

comment, or by sharing a post, henceforth participating in media dissemination. Engagement

through participation is defined as a user-initiated action (Gluck, 2012, p. 8), which in turn

increases the post’s value through collaborative creation (Brodie, Ilic, Juric, & Hollebeek, 2013).

Hollebeek (2011) viewed online engagement as multidimensional by acknowledging the

behavioral, cognitive, and emotional forces at play.

User-generated content in the form of likes, comments, and “shares” further encourages

user interaction with the content, which may give the impression of veracity and credibility

(Kraut & Resnick, 2011). This can influence how users perceive reality and can also alter users’
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points of view on topics discussed (E. M. Kim & Sun, 2006; E. J. Lee & Jang, 2010). Studies

have shown a positive relationship between user anonymity and the proclivity to engage through

comments. Furthermore, inflammatory comments are more often linked to anonymity (Kilner &

Hoadley, 2005).

Several studies have shown that passive participation in social media can reduce a sense

of belonging, predict loneliness, and increase symptoms of depression (Fried & Nesse, 2015;

Mellor, Stokes, Firth, Hayashi, & Cummins, 2008; Tobin, Vanman, Verreynne, & Saeri, 2015;

Verduyn et al., 2015). In 2018, Aalbers, McNally, Heeren, de Wit, and Fried surveyed 125

undergraduate students by sending them a 12-item questionnaire (which measured for passive

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social media use, depression symptoms, loneliness, and stress) seven times daily in 2-hr intervals
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for 14 days via a smartphone app. The particularity of this study is in the network structures used

to analyze variables across three different models of time: Aalbers et al. used contemporaneous
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associations to examine the relationship between the variables measured within a single

timeframe of 2 hr and used temporal associations to analyze l variables between consecutive 2-hr
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timeframes in the hopes of establishing causality. Between-subjects associations were applied to

see how the variables fluctuated for each participant throughout the 14 days. Results showed that

passive social media use did not predict depression, loneliness, or stress. Instead, Aalbers et al.

found that previous fatigue and loneliness predicted passive social media use and that passive

social media use co-occurred with symptoms of depression including loss of interest,

concentration problems, and loneliness. They also found that participants who spent more time

passively engaging with social media reported higher mean levels of depressed mood, loneliness,

hopelessness, and feelings of inferiority over a short period of time. These findings indicate that

while there is no direct causality between passive social media use and depression in the long
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run, social media use can have an affective impact on young individuals.

Viral. This idiom refers to online content that quickly becomes very popular or well

known by virtue of having been published on the Internet, copied, and shared across various

social media platforms. According to the Oxford English Dictionary (as cited in O’Neill, 2011),

the term viral in the sense of rapid sharing of information dates to 1989 and was used in the

context of traditional media (print and film). When this expression reached the Internet culture,

an online post was initially considered viral when it had accrued 1,000,000 views (O’Neill,

2011). YouTube celebrity Kevin Nalty purported, “A video is ‘viral’ when it gets more than 5

million views in a 3 to 7 day period” (as cited in O’Neill, 2011, p. 3). In other words, viral is

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associated with how fast a post spreads across the web through user engagement (views and
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shares) and is a measure of online success (Alhabash & McAlister, 2014).

Another key characteristic of a viral post is its impact on social discourse both online,
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through likes and comments, and offline; this is typically achieved when a post reaches popular

blogs or the evening news (G. Khan & Vong, 2014). A viral post’s longevity (meaning how long
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it is remembered for) is also an indicator of its impact on popular culture. A viral post’s success

can also be measured by its degree of imitation through replication, typically in the form of

parody (O’Neill, 2011).

Viral posts exist in various formats, including photos, memes, videos, and challenges.

Internet challenges are social and cultural phenomena specific to the Internet. They consist of

videos created by individuals recording themselves completing or replicating a task. They then

distribute the footage on social media. A noteworthy Internet challenge was the 2014 Ice Bucket

Challenge, a charity-driven endeavor in which an individual nominated three people to either

donate $100 to the ALS Association or to douse themselves with a bucket of ice-cold water after
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nominating three other people to partake in the event (Lawrey, 2014). This challenge yielded

over $115,000,000 for the ALS Association (McNamara, 2016). The popularity of this challenge

was further enhanced by the participation of celebrities and politicians (Tanaka, 2014), therefore

encouraging adolescent engagement. However, a majority of Internet challenges do not have a

charitable etiology and hold rather harmful rules. For instance, the “fire challenge,” targeted to

adolescents, invited challengers to apply flammable liquids on their skin and light themselves on

fire. Several were hospitalized for third- and fourth-degree burns, loss of sensation, loss of hair,

and permanent disfigurement (Marshall, 2018). Adolescents do not always recognize the

potential risks associated with Internet challenges, as they are concerned with gaining popularity,

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likes, and the opportunity to go viral (Marshall, 2018).
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Emoji. Emojis were created by Japanese developer Shigetaka Kurita in 1999 (Pardes,

2018). They are a standardized set of characters ranging from faces, objects, and buildings to
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mythical creatures and are available on iOS, Android, Windows, and MacOS. However, they

appear slightly differently on each platform as there is no one true design for any given character
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(Burge, 2019). The original idea behind emojis was to insert human emotion in a message to

convey tone and reduce confusion associated with text communication in the Japanese language.

As of June 2018, there were 2,823 emojis in the Unicode Standard, and 230 new characters were

approved for the 2019 release (Emojipedia, n.d.). An estimated 5,000,000,000 emojis are sent

daily through Facebook’s messenger app (Burge, 2019). The face with tears of joy is the most

used emoji, representing 17% of U.S. emoji use. Oxford University Press named emoji the Word

of the Year in 2015 (Cocozza, 2015).

Since 2014, each new update of the emoji Unicode Standard has reflected more inclusive

representations of diversity. Skin tone was added to the 2015 code, an increase in female
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representation occurred in 2016, gender inclusivity marked the 2017 version, and hair color was

added in 2018. The 2019 release included differently abled individuals as well as interracial

couples of all genders holding hands (Burge, 2019).

Meme. This term was created by evolutionary biologist Richard Dawkins to describe

content that spreads quickly from brain to brain and, like genes, replicates and mutates as it goes

along (Dawkins, 1989). A meme refers to a picture macro (an image superimposed with a word

or phrase), a video, or a graphic interchange format (GIF) animated image that is shared through

various Internet and social media channels. Meme-generating websites allow users to create their

own memes by using existing templates (Watercutter & Ellis, 2018). Their proliferation by user

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adaptation or mimic in various Internet cultures and subcultures is synonymous to the
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hyperconnection of users thinking in unison (Schubert, 2003). In other words, memes are

snapshots of culture.
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While memes have been used to connect and share common experiences and jokes,

organizations such as ISIS and the Alt Right have used this media form to recruit followers
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(Watercutter & Ellis, 2018). The use of humor can be a nonthreatening tool for any ideology, and

isolated individuals who are yearning for a sense of belonging are most at risk. Users’

engagement with any content is tracked by algorithms that can alter users’ digital landscape by

generating like-minded content, which means Internet users can easily be targeted by underlying

messages of propaganda through memes (Watercutter & Ellis, 2018).

Selfie. Selfie is a colloquial term that refers to self-portrait photography, taken by one’s

self on a mobile device at arm’s length or through a mirror, and shared via social media

(Computer Hope, 2019; “Selfie,” n.d.). Selfies are typically rehearsed extensively, posed, taken

several times, carefully selected, modified, edited, and embellished through filters and other
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alterations (D. Lee, 2010). Adolescents commonly use apps such as Airbrush and Facetune,

among many others, to correct facial imperfections such as blemishes, skin tone, and wrinkles

(Grasso, 2016). Photo editing apps also allow using digital effects such as borders and collages,

embedded text, and art (Marwick, 2015). Accessories such as selfie sticks and selfie shoes have

made their mark on young consumers, fostering an obsession in the practice (Che, 2015;

Diefenbach & Christoforakos, 2017). Additionally, phone manufacturers have adjusted their

products in adherence to the consumer trend by adding a selfie mode to their photo

functionalities, giving access to professional-grade production of self-portraits (Carbon, 2017).

While millennials were deemed “the selfie generation,” Gen Z adolescents are more

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likely to post about their families (44%) and their accomplishments (49%; M. Anderson & Jiang,
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2018). According to the Pew Research Center, 45% of adolescents reported they often or

sometimes post selfies online; 60% of adolescent girls indicated they do so often compared to
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30% of boys. The proportion of White adolescents who post selfies has steadily dropped to 39%,

while 66% of Black adolescents and 51% of Hispanic adolescents reported engaging in these
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online self-presentation practices (M. Anderson & Jiang, 2018). Adolescent girls can spend an

average of 16 min perfecting a selfie (Glum, 2015), and 26% of surveyed adolescents reported

that they felt badly about themselves when their photo was ignored, not liked, or commented on

(Common Sense, 2018). In its 2015 report, Common Sense found that adolescent girls worry

about how they are perceived online, with 35% of young female participants reporting feeling

anxious about being tagged in an unattractive photo and 27% expressing worry about how their

posts will be received by their online audience.

In his study on Israeli social networks, sociologist Ori Schwarz (2010) wrote, “We are

witnessing a shift from photographing others for self-consumption to documentation of the self
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for consumption by others” (p. 165). Conversely, Norwegian professor in digital culture Jill

Walker (2005) argued that selfies serve as instruments for identity exploration and for making

statements of individualism as well as for empowerment over public self-representation. While

women and girls have historically been portrayed in sexualized and objectified forms to satisfy

the “male gaze” (D. Lee, 2005), selfies have been said to emancipate women to “becom[e]

autonomous subjects and gain control over the ways in which they are being represented”

(Schwarz, 2010, p. 164). However, selfies allow users to control how others will see them; they

are created for publication on social platforms with rating systems (likes, comments, shares) that

assign them value while their ultimate intention is to generate user traffic and engagement (A.

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Cox, 2007). The production and online publication of selfies has become a game of numbers that
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impacts and motivates a continuous cycle of content production and publication (Cohen, 2005).

As such, selfies often replicate conventional images seen in mass media, including sexualized
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female forms (Hjorth, 2007; D. Lee, 2005). The social impact of this means of self-presentation

is such that selfies have become a cultural phenomenon with their own set of conventions and
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practices (Marwick, 2015). For instance, the “MySpace angle” is a photo that is captured above

the face in order to make one appear thinner and more attractive (Sessions, 2009). “Duck face”

or “duck lips” refer to a facial expression marked by pouted lips with sucked-in cheeks, while

“fish gape” is depicted by a slightly open mouth and faint showing of teeth (Rodulfo, 2015).

As selfies have become a tool for online self-expression, the social media culture

encourages attention-seeking behaviors leading to higher risk factors for users, including death

(Bansal, Garg, Pakhare, & Gupta, 2018). Between October 2011 and November 2017, 259

deaths related to taking a selfie were reported. Common reasons for these deaths included

drowning, vehicular accidents, and falling. Of these deaths, 36% involved young individuals
 SOCIAL MEDIA AND ADOLESCENT ATTACHMENT STYLE 16

between ages 10 and 19 years, and 76% were boys compared to 52% of girls. The United States

was third in selfie-related deaths after India and Russia (Bansal et al., 2018). In response to the

surge in selfie-related accidents, “no-selfie zones” have been demarcated in Mumbai’s tourist

areas, “selfie-safe zones” are in the works in Indonesia, signs dissuading selfies have emerged in

Russia, “phone seats” for taking selfies in tourism spots are being prototyped in Ireland, and the

Saftie app delineates safe spots to take selfies around the world (Bansal et al., 2018; Southern

Star Team, 2019).

Hashtag. Hashtags are metadata tags that users can apply to any post on social media by

placing the pound sign (#) before any word or phrase without spacing between terms. These

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phrases become dynamic tags that other users can click to find similar content (Chang & Iyer,
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2012). Hashtags are user generated, meaning they are not owned or controlled by any entity.

Therefore, they cannot be removed from the Internet sphere, and there is no guaranteed
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uniformity of content associated with hashtags. According to Scott (2015), the hashtag “was

created organically by Twitter users as a way to categorize messages” (p. 9). In 2010, Twitter
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introduced a trending topics category on its home page to curate the most popular hashtags (Rao,

2009). Since their proliferation in the social media sphere, hashtags have become a strategic tool

for increasing traffic to user-generated content (Tiltow, 2012). Common hashtags employed by

users who are actively seeking more followers include #followforfollow, #follow4follow,

#likeforlike, and #followme. The hashtag #nofilter was popularized in resistance to the digital

manipulation of images to indicate that no alterations were made to the original image (Marwick,

2015).

In early 2010, television channels began implementing hashtags on screen, encouraging

viewers to engage in conversation via social media (Schneider, 2011). Hashtags have also been

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