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Format: 2-3 pages, Times New Roman, 12-pt font, 1-inch margins on all sides,

Citations should be in a consistent, in-text parenthetical format (MLA and ASA both work).

If you cite course content, then in-text parenthetical citations are good enough (no full bibliography or works cited needed for this assignment), but if you cite anything that is not part of course content, you WILL need a full citation so that we know what this source is.

IMPORTANT: Please check your submission after uploading to make sure 1) it was the correct file and 2) the format of your file was readable. You are responsible for submitting the correct and readable file before the due date.

Preparation to Write the Paper: Throughout this semester, spend approximately 5 hours a week engaging and initiating with a virtual community. Your goal is to immerse yourself as much as possible in a virtual community (either one that you already have some experience with or a new one) to investigate what being a part of such a community is like. This is like doing ethnography and participant observation in a virtual space. Take notes about people’s reactions to you and the social interactions that occur in such a community. Reflect on your own experiences, feelings, and interactions.

You may create social experiments (without harming anyone) or observe other people’s interaction in the virtual community. You may even conduct interviews (virtually) with people that you meet. And look for connections from your experience to the readings, lectures, and themes from the course.

NOTE: Please follow basic ethical guidelines when conducting research, especially if you decide to do some social experiments or conduct interviews. If you have any questions, please ask me.

The final product (due April 12) will be an argumentative paper that connects what you observed/experienced in the virtual community to at least 2 readings from course content.


As a way to guide you towards that final product, the first assignment is a report that will help you gather interesting observations and help you connect them to course content.

Write a double-spaced 2-3-page report that starts to analyze the data you have collected and starts to look at possible themes and readings to engage with. In your report,
you will have two key subsection headings:*

1. People and Interactions

2. Possible Course Content

People and Interactions

In this section, you will do the following:

Describe 2 patterns
that you have observed in your virtual community. Patterns are relatively consistent and repeated incidents, interactions, ways of using the virtual community, etc. that you have observed in the virtual community.

? For each described pattern,
provide at least 1 specific example
that illustrates the pattern. This could include screenshots, but could also just be your description of what occurred.

? For each described pattern,
brainstorm a short list of relevant course concepts
that relate or connect with the described pattern. For example, “This pattern connects to several course concepts including social capital, virtual communities and Rheingold, gaming and Twitch streaming, social movements…” Look at the syllabus to help you brainstorm some possible ideas, including looking ahead at readings that we may have yet to cover. You do not need to elaborate on this list.

Possible Course Content

In this section, you will do the following:

Choose 2 course concepts
from the lists you made in the first section.

? For each chosen course concept,
start by listing the most relevant lectures and readings
that connect to the concept (e.g. “Social capital is a key concept in the readings from… <insert author names>. It is also discussed in the lectures on… <insert lecture titles>.” Be sure to look AHEAD in the syllabus too!

? For each chosen course concept, using readings and/or lecture,
explain the concept
paying special attention to the parts of the idea that relate most to your virtual community.

? Then,
connect the concept to the examples you gave earlier
. Either show how your experiences or observations agree or disagree with the course content; or show how the course content pushes you to understand the data differently.

Grading Rubric

Each section is worth 50% of the total grade. In the first section, your descriptions should be detailed and clear–easy to picture and understand. In the second section, your listing of course content should be relatively complete and your explanations of the course content should be accurate.

The reader should be able to see not only how much time you have spent interacting with the virtual community, but also how well you are able to start seeing connections to course material.


1. What kind of virtual community works for this paper?
A virtual community that has a visible, discernible boundary where you can identify members clearly is generally the kind of virtual community that will work for this. So that means saying “Facebook” might be simply too large, but identifying a subgroup on Facebook (like a Facebook Group) would likely work better. For Twitter or Instagram, this could be a hashtag or communities that revolve around a specific person, theme, etc. Look for subgroups rather than overly large communities with unidentifiable boundaries.
Blended communities (communities that are partially virtual and partially offline/face-to-face) work as well, as long as a relatively large portion of interaction takes place online. This would include things like dating apps, Meet Ups, and other communities that have a predominately online interaction space but has a significant physical component as well.
You are welcome to do a virtual community that you have been a part of for awhile–my only concern is that if you are too close to the community, it could blind you to interesting things to notice, simply because you are too close to the culture of that community. You should pick something that interests you, but something new could also be beneficial for this assignment.
One suggestion is to look for niche virtual communities. These are sometimes on random websites, fan pages, forum spaces, reddit subgroups, etc. and are not always found on massively popular and mainstream social media websites. Some of the most interesting virtual communities are more specific and more hidden. These communities can be relatively small, as long as there is daily engagement so that you can plug yourself in and really get to know people.
The virtual community should also have a social media space that allows you relatively meaningful engagements. In other words, if you did some kind of gaming community, look for specific spaces to engage with a set group of people. This could be a guild, discord site, fan page, resource guide/community, etc. Just playing the game will not work as you probably have fairly limited access to engagements and gathering data.

2. How do I write this report? Should I literally write out the question and then answer it? Should we answer the questions in order?
be sure to use subsection headings as instructed above
. This will help your clarity and make sure your reader can follow your thoughts. My suggestion is to use paragraphs that clearly answer one (maybe two) of the questions that are listed in each subsection. Use transitions and clear topic sentences (the first sentence in each paragraph) to show which question you are answering.
I would generally answer the questions in the order that they are presented above–they follow a fairly logical progression. But technically you do not have to answer them in order if it makes more sense not to.

3. Do we need citations in this report?
If you are only citing readings from course material, you just need the parenthetical, in-text citations. If you are citing anything outside of course material, you need to provide the full citation in a works cited page at the end of the report. You do not need citations outside of course material to do well on this report. I assume you will likely have some citations from readings or lectures to answer part 2 of the report.

4. Can we use screenshots for this report? Can we gather data via surveys on our virtual community for this report?
Yes, I think screenshots can be used for this report if they are helpful in describing the virtual community–however they are NOT necessary to get a perfect grade on this assignment. They can be helpful if you find it difficult to describe something about your virtual community or about the social media platform.

This would not count towards your 3-page limit and you can attach them either embedded in the report or at the end of the paper as an appendix. Please label your screenshots with a simple caption so that your reader knows what they are looking at. In general, keep all identifiers anonymous, which might mean blacking out some names of people–this is to respect anonymity and concerns of privacy.

You may also gather some data informally through a survey, but at this point, I do not think this is necessary for this assignment. You might consider doing it for the final paper, especially if you find it essential or incredibly relevant for your analysis and the argument you will eventually make. For this assignment though, you can certainly do it, but I do not really think it is necessary and your personal observations should be enough for you to answer every question with relative confidence.

If you do gather data through an informal survey of the virtual community members, you can display this data as a chart or graph at the end of the report or embedded in the text of the report–whatever makes more sense from the perspective of someone reading your report. Again, this would not count towards your 3-page limit.

5. I don’t see a reading that really fits with what I want to talk about in my paper/this report. Can I draw on readings I find on my own?
The short answer is no. This is NOT a real research paper. Unfortunately, I don’t have the resources or guidance to feel comfortable unleashing several hundred students online to go do independent research. Instead, I think of this project more as an introduction to virtual community research that uses simple, flexible research methods as a way to introduce you to the field–perhaps in the future, you can build off of what you do in this class.
As a result, you are only graded on readings that are found on the syllabus. This MAY limit the scope of what you can talk about (see above suggestions on how to approach gathering data for this paper). If there is a course concept that appeared in lecture but I did not assign on the syllabus, you ABSOLUTELY can use this reading if you get approval. Please come talk to me as soon as possible to get permission and a copy of the reading that pertains to the course concept and you can use that in your paper and it will count towards your usage of two readings.
Note: Under the Files section of our bCourses site, in the folder title “Readings” there is a folder of “Extra readings” that are okay to use for the virtual community paper. You might want to check there first to see a reading has already been approved and added to that folder.

Computers in Human Behavior 29 (2013) 1841?1848

Contents lists available at SciVerse ScienceDi rect

Com puters in Human Behavior

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h

Motivational, emotional, and behavioral correlates of fear of missing out

0747-5632/$ – see front matter ? 2013 Elsevier Ltd. All rights reserved.

? Corresponding author. Tel.: +44 (0) 1206 873786.
E-mail addresses: [email?protected] (A.K. Przybylski), [email?protected] (K. Murayama), [email?protected] (C.R. DeHaan), [email?protected]
(V. Gladwell).

Andrew K. Przybylski a,?, Kou Murayama b, Cody R. DeHaan c, Valerie Gladwell d
a Department of Psychology, University of Essex, Wivenhoe Park, Colchester, Essex CO5 3SQ, UK
b Department of Psychology, University of California, Los Angeles, CA 90095-1563, USA
c Department of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, NY 14627-0266, USA
d Department of Biological Sciences, University of Essex, Wivenhoe Park, Colchester, Essex CO5 3SQ, UK

a r t i c l e i n f o

Article history:
Available online 9 April 2013

Fear of missing out
Human motivation
Individual differences
Social networking
Scale development

a b s t r a c t

Social media utilities have made it easier than ever to know about the range of online or offline social
activities one could be engaging. On the upside, these social resources provide a multitude of opportuni-
ties for interactio n; on the downside, they often broadcast more options than can be pursued , given prac-
tical restrictions and limited time. This dual nature of social media has driven popular interest in the
concept of Fear of Missing Out ? popularly referred to as FoMO. Defined as a pervasive apprehension that
others might be having rewarding experiences from which one is absent, FoMO is characterized by the
desire to stay continually connected with what others are doing. The present research presents three
studies conducted to advance an empirically based understanding of the fear of missing out phenome-
non. The first study collected a diverse international sample of participants in order to create a robust
individual differences measure of FoMO, the Fear of Missing Out scale (FoMOs); this study is the first to
operationalize the construct. Study 2 recruited a nationally represe ntative cohort to investigate how
demographic, motivational and well-being factors relate to FoMO. Study 3 examined the behavioral
and emotional correlate s of fear of missing out in a sample of young adults. Implications of the FoMOs
measure and for the future study of FoMO are discussed.

? 2013 Elsevier Ltd. All rights reserved.

1. Introductio n

Social media utilities provide increasingl y abundan t forms of
social informat ion. These mediums afford easy access to real-time
information about the activities, events, and conversations hap-
pening across diverse social networks. This digitally fueled deluge
of updates has kindled interest in and writing about a relatively
new phenomeno n termed Fear of Missing Out , popularly referred
to as FoMO. Defined as a pervasive apprehension that others might
be having rewarding experiences from which one is absent, FoMO
is characterized by the desire to stay continually connected with
what others are doing.

For those who fear missing out, participation in social media
may be especially attractive. Services like Facebook, Twitter, and
Foursquare are technological tools for seeking social connection
and provide the promise of greater levels of social involvem ent
(Ellison, Steinfield, & Lampe, 2007 ). In many ways, social media
utilities such as these can be thought of as reducing the ??cost of
admission?? for being socially engaged. While these social tools pro-

vide advantages for the general population, it is likely they are a
particular boon for those who grapple with fear of missing out.

Indeed, social media engagement presents a high efficiency low
friction path for those who are oriented towards a continua l con-
nection with what is going on. There is good reason then to expect
that those who are high in fear of missing out gravitate towards so-
cial media. Despite increased interest in and writing about FoMO, it
is noteworthy that very little is empirically known about the phe-
nomenon . To address this deficit, the present research applies a
motivatio n-based perspective to delve deeper into fear of missing
out and explore its motivational , behavioral , and well-being
correlate s.

1.1. Psychologica l needs perspective

Self-determinati on theory (SDT; Deci & Ryan, 1985 ) a macro-
theory of human motivation provides a useful perspective for
framing an empirica lly based understanding of FoMO. According
to SDT effective self-regulati on and psychological health are based
on the satisfaction of three basic psychological needs: competence
? the capacity to effectively act on the world, autonom y ? self-
authorshi p or personal initiative, and relatedness ? closeness or
connected ness with others. Research conducte d in the sports
(Hagger & Chatzisarantis, 2007 ), education (Ryan & Deci, 2000 ),
and video-ga ming domains (Przybylski, Weinstein, Ryan, & Rigby,

1842 A.K. Przybylski et al. / Computers in Human Behavior 29 (2013) 1841?1848

2009), indicate that basic need satisfaction is robustly associated
with proactive behavioral regulation. Through this theoretical lens,
the FoMO phenomenon can be understood as self-regulator y limbo
arising from situational or chronic deficits in psychological need
satisfaction s.

Following this line of thought, low levels of basic need satisfac-
tion may relate to FoMO and social media engagement in two
ways. The link could be direct, individuals who are low in basic
need satisfaction may gravitate towards social media use because
it is perceived as a resource to get in touch with others, a tool to
develop social competence , and an opportunity to deepen social
ties. The relation between basic needs and social media engage-
ment could also be indirect, that is, linked by way of FoMO. Provid-
ing that need deficits could lead some towards a general sensitivity
to fear of missing out, it is possible that need satisfaction is linked
to social media use only insofar as it is linked to FoMO. Said differ-
ently, fear of missing out could serve as a mediator linking deficits
in psychological needs to social media engagem ent.

1.2. FoMO and functioning

Another important dimension of FoMO are its potential links
with psychologi cal health and well-being. In a recent book, Turkle
(2011) advances the position that technology-med iated communi-
cation carries positive as well as negative influences. Turkle ex-
plores a number of case studies and outlines general conditions
under which digital communicati on mediums can undermine
self-reflection and ultimately degrade well-being. She argues the
??tethered self?? provided by always-on communication technolo-
gies can distract us from important social experiences in the
here-and-no w. Turkle advances the position a strong desire to stay
continuously connected is potential ly dangerous as it encourages
people to check in with their digital technology even when they
are operating motor vehicles. In line with this, accounts of FoMO
presented by journalists writing for The New York Times
(Wortham, 2011) and San Francisco Chronicle (Morford, 2010) high-
light how a mix of social media and fear of missing out may be linked
to general unhappiness. Wortham (2011) proposes that FoMO may be
a source of negative mood or depressed feelings in part because it
undermines the sense that one has made the best decisions in life.

Research focused on the motives underlying social media give
additional reasons to expect FoMO linked to deficits in mood and
satisfaction with life drive social media engagement. Research on
internal motives for social media engagement indicates that avoid-
ing negative emotional states such as loneliness (Burke, Marlow, &
Lento, 2010 ) and boredom (Lampe , Ellison, & Steinfield, 2007 )
compel Facebook use. In a similar vein, dissatisfacti on with the
present state of one?s relationshi ps has been identified as a motive
undergirdin g social media use (Ellison, Steinfield, & Lampe, 2007 ).
These perspectives suggest social media affords an outlet for social
and emotional frustrations. Taken together with the wider motiva-
tion literature, it appears that fear of missing out could serve an
important role in linking individual variability in factors such as
psychological need satisfaction, overall mood, and general life sat-
isfaction to social media engagement.

1.3. Previous research

Some preliminar y research has explored the prevalence of
FoMO and its relation to social media (JWT, 2011, 2012 ). This sur-
vey work defined FoMO as ??the uneasy and sometimes all-consum-
ing feeling that you?re missing out ? that your peers are doing, in
the know about, or in possession of more or something better than
you??. Under this framing of FoMO, nearly three quarters of young
adults reported they experienced the phenomeno n. This polling
also indicated that younger people tended to experienced intense

unease when they felt at risk for missing out on positive experi-
ence, and that males were more likely than females to turn to so-
cial media when struggling with a sense of FoMO. Taken together,
findings from this initial examination of fear of missing out suggest
it may be quite common among some groups. That said, these pre-
liminary industry reports leave open wider questions about the
operation alization, correlates, and overall relevance of FoMO.

1.4. Present research

The aim of the present research was to advance an empirically-
based and theoretically-m eaningful framing of the fear of missing
out phenomenon. To this end, we designed and conducted three
studies. In the first, we developed a self-report assessment that
measure d the FoMO construct as an individual difference. In the
second, we explored how fear of missing out constellates with a
range of demogra phic and individua l differenc e factors linked to
social media engagement. In the third, we examine d its emotional
and behavioral correlate s.

In Study 1, we collected data from a large and diverse interna-
tional sample of participa nts in order to create a robust individual
differenc es measure of FoMO. Guided by extant writing about fear
of missing out we drafted a pool of statements reflecting FoMO and
used a data driven approach to select representative items with the
best psychometri c properties. Our aim in this first study was to
create a sensitive self-repo rt instrument, one that is informative
for individuals with low, medium, and high latent levels of fear
of missing out, and one that is useful for measuring FoMO in a wide
range of research contexts.

In Study 2, we recruited a nationally representat ive sample to
empirica lly evaluate fear of missing out from a broad perspecti ve.
This study was conducted with two aims in mind. First, we aimed
to investiga te demographic variability in FoMO, to explore who in
the general population tended towards fear of missing out. Our
second goal was to evaluate FoMO as a mediating factor linking
individua l differenc es identified in past motivation and social med-
ia research to behavioral engagement with social media.

In Study 3, we shifted focus from large-scal e samples to a uni-
versity cohort to fine-grained understand ing of how FoMO related
to emotion and behavior. In particular , our goal for this study was
to understand how those high in fear of missing out felt about their
social media usage, how frequent ly they used social media, and the
extent to which FoMO enables social media as a distractor from
other important responsibilities in everyday life.

2. Study 1: measuring FoMO

Our objective in the first study was to create a robust individual
differenc es measure of fear of missing out. More specifically, we
wanted to create a brief, self-repo rt assessment that minimize d
participa nt burden and provided maximal informat ion about an
individua l?s level of FoMO. To achieve this goal we paired a the-
ory-guid ed method with latent trait theory analysis to craft a ro-
bust assessment of fear of missing out.

To take full advantag e of this approach we needed to start with
a large pool of potential FoMO items. Based on a review of popular
and industry writing on FoMO (e.g., JWT, 2011; Morford, 2010;
Wortham, 2011 ) we drafted 32 items meant to reflect the fears,
worries, and anxieties people may have in relation to being in (or
out of) touch with the events, experiences, and conversations hap-
pening across their extended social circles. We framed partici-
pants? reading of and responses to scale items in terms of what
really reflected their general experiences instead of what they
thought their experiences should be.

A.K. Przybylski et al. / Computers in Human Behavior 29 (2013) 1841?1848 1843

We then recruited a diverse international sample of adults to
provide self-repo rt ratings for this broad pool of candidate items,
which focused on the extent to which people feared missing out
on rewarding experiences, activities, and methods of discourse
(e.g. in jokes). The large sample was intended to be representat ive
of a wide range of potential respondents and provided the volume
of responses needed to empirically identify a subset of optimally
representat ive items using latent trait theory analysis.

2.1. Method

Participants were 672 men and 341 women (n = 1013), ranging
in age from 18 to 62 years (M = 28.5, SD = 8.55). All participants
were fluent in English; 41.1% lived in the United States, 35.9% India,
5.6% Australia, 3.9% Canada, 3.2% United Kingdom, and 10.3% re-
sided in other nations (each not exceeding 2%). Participants were
recruited online through Amazon?s Mechani cal Turk worker sys-
tem; each participa nt was compensated $0.30 each for completing
the questionnair e.

2.1.1. Fear of Missing Out scale (FoMOs)
Participants completed basic demographic questions followed

by the 32 candidate items drafted for the FoMOs by way of an
HTML questionnair e. Instructio ns stated: ??Below is a collection of
statements about your everyday experience. Using the scale pro-
vided please indicate how true each statement is of your general
experiences. Please answer accordin g to what really reflects your
experiences rather than what you think your experiences should
be. Please treat each item separately from every other item??. The
presentation order of items was randomized for each participant
and items were paired with a five-point Likert-ty pe scale:
1 = ??Not at all true of me??, 2 = ??Slightly true of me??, 3 = ??Moder-
ately true of me??, 4 = ??Very true of me??, and 5 = ??Extreme ly true
of me??.

2.2. Results

2.2.1. Factor and IRT analyses
The purpose of this study is to select a small set of unidimen-

sional items that reliably assess all levels of fear of missing out.
In line with this, the analytic approach we adopted to achieve this
end was comprised of two steps.

First, we conducte d a principle components analysis using a
maximum likelihood estimation method including all the 32

Fig. 1. Total test information curve observed for 10-item FoMO scale in Study 1. Note: the
as a function of scale scores (i.e. latent trait scores).

candidat e items. Prelimina ry investigation of the data suggested
a strong single factor solution, but there were some items that
had small suboptimal factor loadings, and others that lowered
the overall model fit considerabl y. Following an iterative process
of confirmatory factor analysis we eliminated suboptimal items
and retained 25 of the original 32 items. These items produced a
good fit to the data, v2 (275) = 1778.1, p < .01, RMSEA = .073,
SRMR = .056.

Second, to further reduce the number of items while maximiz-
ing the sensitivity of the scale to all levels of the fear of missing out,
we estimated item paramete rs using an Item Response Theory
(IRT; De Ayala, 2009 ) approach with PARSCAL E (Muraki & Bock,
1998). Specifically, we applied a graded response model to the data
and estimate d individual item information curves, which describes
the amount of information the individual items provides at various
points along the latent trait (i.e., fear of missing out) spectrum
(Samejima, 1969 ). From this we were able to identify 10 items that
jointly showed high amount of information across a broad range of
the FoMO continuum. Fig. 1 provides a graphic depiction of the test
informat ion curve ? the sum of the individual item informat ion
curve ? of this final 10-item scale. The latent trait was scaled with
mean of 0 and SD = 1.0 and the maximum informat ion were ob-
served at a slightly positive level of the latent trait (h = .51). This
indicates that the final scale is most sensitive to assessing partici-
pants with moderate to high fear of missing out. However, overall
the curve was quite well distribut ed, suggesting that this scale can
reliably assess participants with a broad range of FoMO (i.e., low,
medium, and high). We also computed latent trait scores for partic-
ipants using the graded response model and correlated them with
scale scores computed by averaging the row rating scores of the fi-
nal 10-item scale. The resulting correlation (r = .95) indicated that
overall FoMO scores for individuals could be computed simply by
averaging across the raw rating scores (M = 2.56, SD = 0.82). The fi-
nal scale items, presented in Appendix A, showed good consistency
(a = .87), as well as an acceptab le distribution in terms of both
skewnes s (0.27) and kurtosis (?0.48).

2.3. Brief conclusion

In this study we recruited a large and diverse sample of partic-
ipants who rated a pool of items drafted to reflect individual differ-
ences in fear of missing out. We pursued a data-driven approach
guided by existing views of the phenomeno n to create a self-report
instrument of FoMO. As a result, we were able to identify ten items

dotted like represents standard error and the solid line represents item information

1844 A.K. Przybylski et al. / Computers in Human Behavior 29 (2013) 1841?1848

that accurately tapped into between- persons variability in FoMO.
This assessment, labeled the Fear of Missing Out scale (or FoMOs),
is brief and is sensitive to those who evince low, moderate, and
high levels of fear of missing out construct as an individual

3. Study 2: FoMO in society

In our second study we recruited a representat ive adult sample
to explore how fear of missing out related to demogra phics, indi-
vidual differences, and social media engagement across the general
population. Our aims in this study were twofold. First, we wanted
to examine how demograph ic factors, such as age and gender re-
lated to FoMO on the population level. Our second goal was to ap-
ply the motivatio nal framework of SDT to understand how
individual differenc es in need satisfaction and well-being related
social media engagem ent. This took the form of three research

First we hypothesize d that individuals who have had their basic
needs for competence , autonomy, and relatedness satisfied on a
day-to-day basis would be lower in fear of missing out. Second,
we hypothesize d tha

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