Conference PaperPDF Available

Unfriending on Facebook: Context Collapse and Unfriending Behaviors

Authors:

Abstract and Figures

Social network sites (SNS) like Facebook allow users to add friends from a variety of contexts to a single general-purpose social network. The variety of friend types that gather on the site can lead to context collapse where connections from a variety of context are grouped in a single collection. This research examines the friend types who are commonly unfriended and examines two particular friend types in detail to determine differences between these types of friends and the general population. The most common type of friend who is unfriended is the high school friend (18.6%), followed by other (uncategorized), friend of a friend, and work friend. These four friend types account for the majority (53.7%) of unfriending decisions. High school friends are unfriended for making online posts that are polarizing and for posting too frequently about unimportant topics. Work-related friends are commonly unfriended for engaging in disliked offline behavior and are not typically unfriended for their posting behavior.
Content may be subject to copyright.
Unfriending on Facebook: Context Collapse and Unfriending Behaviors
Christopher Sibona
University of Colorado Denver, The Business School
christopher.sibona@ucdenver.edu
Abstract
Social network sites (SNS) like Facebook allow users
to add friends from a variety of contexts to a single
general-purpose social network. The variety of friend
types that gather on the site can lead to context collapse
where connections from a variety of context are grouped
in a single collection. This research examines the friend
types who are commonly unfriended and examines two
particular friend types in detail to determine differ-
ences between these types of friends and the general
population. The most common type of friend who is
unfriended is the high school friend (18.6%), followed
by other (uncategorized), friend of a friend, and work
friend. These four friend types account for the majority
(53.7%) of unfriending decisions. High school friends
are unfriended for making online posts that are polar-
izing and for posting too frequently about unimportant
topics. Work-related friends are commonly unfriended
for engaging in disliked offline behavior and are not
typically unfriended for their posting behavior.
1. Introduction
Facebook is the single most popular website in the
United States; globally there are over one billion active
accounts and billions of dyadic connections that span
the site’s online network [25, 24].1Social network sites
(SNS) are where Americans spend the largest share of
their time online; Americans spend approximately 17%
of their time online via personal computers on Facebook
[24]. Social network sites like Facebook allow users to
accumulate social capital; however, the site appears to
benefit weak-tie relationships more than strong-tie rela-
tionships [8, 31]. Relationship strength may vary from
weak- to strong-ties, although there is some consensus
that the majority of ties on Facebook are weak [31, 19].
Facebook users can become friends with members
from a variety of contexts and all of these friends are
grouped together on a single general purpose site. boyd
[3] defines context collapse as, “the lack of spatial,
social, and temporal boundaries [that] makes it difficult
1http://newsroom.fb.com/Key-Facts
to maintain distinct social contexts.” The lack of bound-
aries tends to group individuals from different contexts
(family, friends, classmates, coworkers, neighbors, etc.)
into the large group of “Facebook Friends” on a SNS like
Facebook [32]. Vitak et al. [32] notes that there may be
large differences between groups for some categories of
users like users from work settings versus social settings.
Online friendships are fluid; friendships are created
and dissolved on social network sites where a con-
nection can be dissolved with the click of a button.
Connections on social network sites are formed under
a variety of contexts, ranging from maintaining existing
relationships, forming new romantic connections, and
creating new online friendships [33]. Unfriending has
become a widely-used feature of social networking sites;
Pew Internet found that 63% of users unfriended at least
one member of their online social network in 2011 up
from 56% in 2010 [20]. The word unfriend was named
the word of the year by the New Oxford American
Dictionary for 2009 [9]. The dictionary defined unfriend
as follows: “unfriend – verb – To remove someone as a
‘friend’ on a social networking site such as Facebook.
There were three motivations for undertaking this
study. First, there is a noted gap in the literature
regarding context collapse and unfriending behaviors
[19, 2]. Second, friendship dissolution in computer-
mediated environments and non-computer-mediated en-
vironments (face-to-face), in general, is not well un-
derstood [22, 19, 2]. Because the friendship dissolution
research is largely based on close relationships includ-
ing close friends, romantic partners and divorce [22],
unfriending on Facebook may differ simply due to the
greater diversity of contexts in which the network oper-
ates through context collapse. Relationship dissolution,
as it is understood by the social sciences, may or may
not resemble unfriending. Indeed, research is needed
to clarify the social causes of friendship dissolution
[19, 27]. Third, and perhaps most importantly, greater
understanding of the dissolution of online relationships
will aid in the development of models for a life-cycle
of online relationships. Certain aspects of online re-
lationship dissolution make it easier to study because
the friend requests and dissolution are visible. Facebook
has technical affordances that explicitly mark events
2014 47th Hawaii International Conference on System Science
978-1-4799-2504-9/14 $31.00 © 2014 IEEE
DOI 10.1109/HICSS.2014.214
1676
like the initiation of the friend request and dissolution
of the tie through the feature-functions of the site. In
offline settings it can be unclear who asked whom to
be friends and it is often unclear who initiated the
dissolution process. Unfriending someone on Facebook
is a conscious act by one person to end the dyadic
relationship and manifests itself through the removal of
a link between the dyad.
There are two major research questions this study
addresses:
1) What are the common friend types who are un-
friended on Facebook.
2) What are the factors related to unfriending of two
common types of friends (high school friends and
work-related friends) and how do they differ.
2. Literature Review
boyd and Ellison [4] defined social network sites based
on three system capabilities. The systems: “allow indi-
viduals to (1) construct a public or semi-public profile
within a bounded system, (2) articulate a list of other
users with whom they share a connection, and (3) view
and traverse their list of connections and those made by
others within the system” [4, p. 211]. After users join
a site they are asked to identify others in the network
with whom they have an existing relationship. The links
that are generated between individuals become visible to
others in the local subspace.
Context collapse occurs in online social networks
because a variety of friends from different contexts are
grouped together in a single location [3]. boyd [3] largely
studied teenagers navigation of online spaces through
three dynamic properties: invisible audiences, collapsed
context and the blurring of public and private spaces.
Vitak et al. [32] examined context collapse regarding
work and personal life boundaries. Vitak et al. found
three strategies for managing context collapse: the first
strategy was to not accept friend requests from work-
related friends on their personal account, the second
strategy was to create multiple Facebook accounts for
professional activities and one for personal contacts and
the third strategy was to to avoid controversial topics
altogether - the “lowest common denominator approach”
[12, 21, 32].
Marwick and boyd [21] examined context collapse
on the social networking site Twitter to determine the
techniques used to navigate the imagined audiences
online. The imagined audience is often constructed by
the user in order to present themselves in an appropri-
ate manner. Twitter’s audience is difficult to determine
for users because, under the default privacy options,
tweets are publicly accessible, followers may not read
the tweets of those who they follow, and tweets may
be retweeted by a receiver of the message [21]. Many
Twitter users noted that they are tweeting to an audience
that includes themselves where the content is a kind of
running publicly available diary. The researchers found
that the imagined audiences often included real-life
friends, family and coworkers. One common approach
for managing context collapse on Twitter was to adopt a
lowest common denominator approach and simply avoid
controversial topics.
Researchers have categorized Twitter users using a
variety of methods and developed labels for their clas-
sification types. Java et al. [13] identified categories of
tweets such as daily chatter (personal thoughts and infor-
mation), sharing information & links and reporting news.
Naaman et al. [23] classified Twitter users into two large
categories - those who talk about themselves (meformers
- 80% of Twitter users) and those who inform others
(informers - 20% of Twitter users). Meformers talked
about themselves in 48% of their tweets and informers
provided some level of information in 53% of their
tweets.
Friendships are formed and maintained because they
are rewarding to individuals [34]. Friendships tend to be
formed by people who share certain similarities (such
as values) [16, 22]. People tend to create friendships
with those who share a similar race and ethnicity fol-
lowed by age, religion, education, occupation and gender
and roughly in that order [22]. The largest portion of
friendships that are formed with those who are not
family members are through organizational structures
[22]. Schools, work, and geographic location are major
factors in how relationships are formed and may be a
factor in how dyads are formed on online SNSs.
Friendships are formed for a variety of reasons on
social network sites. boyd [4] found thirteen common
reasons to become friends on SNS; being actual friends,
acquaintances, friend collection, and “it’s easier to say
yes than no,” were all reasons to extend and accept
friend requests on SNSs. But friendships online can be
fragile, unfriending can also occur and 63% of Facebook
users have unfriended someone in their network [20].
Friendship dissolution is not the same process of friend-
ship formation in reverse and is distinctly different [7].
Some friendships end in conflict but most simply fade
away [30]. Friendships do not require the other person’s
permission to end the relationship in either the online or
offline world [1]. You need permission to be someone’s
friend on Facebook; however, no permission is needed
to end the relationship. One person can simply choose
to “unfriend” the other person. In most cases the person
who was unfriended does not receive notification that
they have been unfriended.
1677
Sibona and Walczak [28] found four common on-
line reasons and two common offline reasons for un-
friending on Facebook. The four online reasons were
frequent/unimportant posts, polarizing posts (politics and
religion), inappropriate posts (sexist, racist remarks, etc.)
and everyday life posts (child, spouse, eating habits, etc.)
and in that order of frequency. The two offline reasons
were disliked behavior and changes in the relationship.
The research also showed that 55% of people unfriended
someone for their online posting behavior, 28% for their
offline behavior and 17% unsure.
Quercia et al. [27] examined how online unfriend-
ing between Facebook dyads may differ from offline
unfriending and found few differences. The research
found that important factors that predicted friendship
dissolution were whether the dyad was embedded in
the same social circle, the age difference between the
dyad, and whether one of the two members were neurotic
or introverted. Relationships that had a common female
friend were more stable than those with common male
friends. Kwak, et al. [11] found factors that related to
unfollowing on Twitter (another form of breaking the
tie on a social network); these factors were relationship
reciprocity, relationship duration, ones informativeness
and shared relationships.
Social networking site research often view the con-
nections between members as undifferentiated and un-
derstanding the different contexts in which these inter-
actions occur may aid in understanding how members
interact with each other in different manners (e.g. high
school, work). Social networking site users may employ
various strategies to manage context collapse including
imagining their audience [21] or following a lowest com-
mon denominator approach [12, 21, 32]. Friendships are
formed and dissolved online and the differing contexts
in which friendships occur may affect how the members
interact and how the connections may be dissolved.
3. Study Design
This research was conducted using a survey to determine
the survey respondents’ opinions and behaviors about
unfriending on Facebook. The survey was conducted
solely on the Internet using a commercially available
survey application.
Part one of the survey asked questions about the type
of person unfriended, whether it was for online or offline
behavior, questions about the friendship and questions
about online and offline behavior. Part two mirrors part
one of the survey and asks questions about the type of
person who unfriended the survey respondent, their per-
ception of whether it was for online or offline behavior,
questions about the friendship and questions about their
offline behavior. Part two adds additional questions to
part one to determine how the survey respondent was
affected by the unfriending. Part three asks questions
about how many friends the survey respondent has, how
many people they have unfriended, how many people
they regularly interact with, and questions about their
online posting behavior. Part three also asks questions
about satisfaction, perceived usefulness and perceived
ease of use of Facebook. Part four asks demographic
questions: age, gender, education, the number of years
of social network use and whether the person lives in
the United States of America. The analysis of this study
concentrates on part one of the survey.
3.1. Data Collection
Survey recruitment was conducted by sending Twitter
users who posted about unfriending a reply asking them
to take a survey about the topic - see Sibona and Walczak
[29] for an in depth description. Twitter was used to
recruit survey participants for several reasons: Twitter
has a large user population where the majority of users
have publicly accessible messages; Twitter users had
a good fit with research (social network sites); it is a
simple process to contact a person on Twitter through the
@reply mechanism; and the tweets can be screened for
recruitment purposes. It is also helpful to recruit people
to the survey who had a recent experience with the matter
for two important factors: (1) Those who experienced
an event more recently may be able to provide more
accurate answers because the event occurred recently. (2)
Those had recently experienced an event may be more
willing to take a survey about the topic because they
may still be thinking about the topic. Experiences need
to be reported immediately after they have happened
in order to be remembered [6]. There is not a random
sample in this research; a purposive sampling method
was used to recruit participants. The recruitment tweet
was sent in a single tweet of 140 characters and provided
enough information to the Twitter user to take the
survey. The recruitment tweet was designed to follow the
methodology of Dillman et al. [6] as much as possible
within the constraints of Twitter.
Surveys were collected between April 17th and
September 15, 2010 for 151 total days. 7,327 recruitment
tweets were sent during the time period. A total of 2,865
surveys were started and 1,552 were completed; 54%
of those who started the survey completed the survey.
The number of surveys in the analysis vary depending
on the path the user took during the survey as not
every survey respondent answered all four parts of the
survey. The analysis of friend types and common reasons
for unfriending analyzed 1,077 survey responses. The
1678
surveys were started by 39.6% of those who were sent
tweets and completed by 21.3%. Twitter respondents
were gathered by screening tweets that had the term
“unfriend,” “defriend,” or “unfriending.” Tweets that met
a screening criterion were sent replies inviting the person
to take the survey about unfriending. The tweet reply sent
was retweeted by many people who received the initial
tweet.
3.2. Method
The raw data was collected from a commercially avail-
able survey application and analyzed with a commercial
statistical package. The survey used methods such as
Cronbach’s alpha to measure reliability and multivariate
analysis of covariance (MANCOVA). Constructs were
generated based on the factor analysis and interpreta-
tion of the results. Cronbach’s alpha measure of re-
liability was calculated for each construct. Constructs
were generated by averaging the individual Likert-type
questions into a single composite variable. MANCOVA
was used to determine how the independent factors
predicted the five dependent variables, with covariates.
The five dependent variables are polarizing topics, fre-
quent/unimportant topics, everyday life topics, inappro-
priate topics and disliked behavior - see Ta b l e 3 and 4.
Statistical tool selection is based on the appropri-
ateness to the model and unit of analysis. MANOVA
is used to analyze multiple dependent variables that
are correlated with each other in a low to moderate
level [18]. MANCOVA is used to adjust for difference
between the groups based on another typically interval-
level variable called the covariate [18]. The analysis used
friend type as an independent variable and compared the
levels of five dependent variables with covariates.
There are several control variables used to adjust the
primary constructs in the study; the control variables are:
age, gender, location (reside in U.S. or outside U.S.),
number of interactions with Facebook users, number
of friends on the site and years of social network site
use. Madden noted significant gender differences in the
way men and women manage their profiles; women
were more restrictive in how they managed their privacy
settings [20]. Age has been shown to be correlated
with unfriending behavior as well; Madden noted that
younger Facebook users unfriended members of their
social networks more often than older users [20]. Several
studies have found cultural differences (based on loca-
tion) in how information systems are perceived by the
user [17, 15, 26]; this study uses location as a proxy
to culture to determine whether U.S. Facebook users
have different behaviors regarding unfriending compared
to those who reside outside the U.S. The number of
interactions measures the number of friends with whom
the user typically interacts and may be related to the
bridging social capital that users obtains from the site
[35]. Joinson [14] found several differences in frequency
of use and time spent on the network site that varied
based on the number of friends on the site and may
have an their unfriending behavior. The variable years of
social network site use is used as a proxy for SNS self-
efficacy. Users who have used SNS for longer periods
of time (which includes sites other than Facebook, such
as Twitter) may be related to that user’s SNS self-
efficacy and may have an effect on the dependent factors.
The control variables are not the primary predictive
variables in this research but are used to control for user
differences.
4. Results
4.1. Friend Type Analysis for Unfriending
The survey asked the survey respondent to identify the
last individual who they unfriended; a total of 1330
survey respondents answered this question. The survey
respondent was offered 15 choices of friend types and
the ability to specify “other” and specify the relation-
ship in an open text field. The majority of unfriending
happens in the first four types (53.7%): High School,
Other, Friend of a Friend, and Work - see Ta b l e 1 . The
Other category consists of answers from the specified
categories with more specificity and new classifications
of friend types. Examples of types of friends that could
be classified in the existing categories are: “elemen-
tary” (grade school), “MBA School” (graduate school),
“college classmate” (college), “former romantic partner”
(romantic partner), etc. The previous examples show the
respondent’s text field in quotes and could be classified
into the categories in italics as provided by the survey.
Other friend types that were not included in the survey
choices include: “didn’t know her,” “enemy,” “former
student.” The 15 categories of friend types could classify
87.5% of the friend relationship where the remaining
12.5% were specified as other.
The survey asked the survey respondent, in a sub-
sequent section, to identify the last individual who
unfriended the survey respondent; a total of 614 survey
respondents answered this question. They survey respon-
dent was offered 14 choices of friend types and also the
ability to specify “other.” The majority of unfriending
happens in the first four types (52.8%): High School,
Common Interest Friend, College, and Coworker - see
Ta b l e 2. The Other category consists of answers from the
specified categories with more specificity and new clas-
sifications of friend types. Examples of types of friends
that could be classified in the existing categories are:
1679
Tab le 1
TYPE OF PERSON UNFRIENDED BY THE SURVEY RESPONDENT
Friend Type Number % Cumulative %
High School 247 18.6 18.6
Other 166 12.5 31.1
Friend of a Friend 156 11.7 42.8
Work 145 10.9 53.7
Common Interest Friend 139 10.5 64.1
College 117 8.8 72.9
Romantic Partner 103 7.7 80.7
Internet 84 6.3 87.0
Family Member 63 4.7 91.7
Church 26 1.7 93.7
Grade School 22 1.7 95.3
Friend through Spouse 22 1.7 97.0
Graduate School 19 1.2 98.4
Friend through Child 9 0.7 99.1
Neighbor 8 0.6 99.7
Friend through Parent 4 0.3 100.0
TOTAL 1330 100.0 100.0
“sibling,” “daughter” (family member), “college room-
mate” (college), “business contact” (work), “potential
romantic partner” (romantic partner), etc. The previous
examples could be classified into the categories in italics.
Example types that were not included as a survey choice
are: “spouse of a close friend,” “he liked me and I didn’t
like him,” “celebrity.” The 14 categories of friend types
could classify 89.1% of the friend relationship where the
remaining 10.9% were specified as other.
The results of the top five friend types are shown
in Figure 1 where differences in ordering may be seen
depending on the perspective of the survey respondent.
Three of the top five friend types are in both the un-
friended by the survey respondent column and the friend
type who unfriended the survey respondent. The rank for
the most common type of friend unfriended by the survey
respondent or who unfriended the survey respondent is
the high school friend. Survey respondents may have
differed in how they categorized the friend types by
context. Survey respondents who did the unfriending
seemed to have a more difficult time categorizing the
user and placed more friends in the other category.
Friend of a friend only shows up in the unfriended by
list and common interest friend is ranked higher on the
friend type who unfriended the survey respondent. Work
friends maintains the same ranking on both lists (4) and
may indicate how common it is to unfriend someone
Tab le 2
TYPE OF PERSON WHO UNFRIENDED THE SURVEY RESPONDENT
Friend Type Number % Cumulative %
High School 100 16.3 16.3
Common Interest Friend 83 13.5 29.8
College 72 11.7 41.5
Work 69 11.2 52.8
Romantic Partner 68 11.1 63.8
Other 67 10.9 74.8
Friend of a Friend 53 8.6 83.4
Family Member 39 6.4 89.7
Grade School 15 2.4 92.2
Friend through Spouse 12 2.0 94.1
Church 11 1.8 95.9
Graduate School 10 1.6 97.6
Friend through Child 7 1.1 98.7
Neighbor 6 1.0 97.7
Friend through Parent 2 0.3 100.0
TOTAL 614 100.0 100.0
Figure 1. Top 5 Commonly Unfriended Friend Types
from work-related contexts. The rankings may indicate
that the perspective of the person varies depending on
who does the unfriending on the social network. More
defined organizational contexts such as high school and
work may be more clear in how friends are categorized
where other friend types such as common interest friend
or friend of a friend may vary more widely based on the
perspective of the survey respondent. That is, it may be
more clear for a survey respondent to say that they went
to high school with this friend and assign that category to
a person, whereas deciding whether a person is a friend
of a friend or common interest friend may be somewhat
more challenging and open to interpretation.
1680
4.2. Analysis of Friend Type by Common
Reasons for Unfriending
Two common friend types were chosen for further in-
vestigation to determine whether certain online topics or
offline behavior may be related to unfriending a particu-
lar friend type at higher rates than others. The two types
of friends for further analysis are high school friends
(ranked number one in both the unfriending done by the
survey respondent and unfriending done to the survey re-
spondent) and work friends (ranked fourth in both friend
type surveys). These two types were chosen because
high school friend is the most common type of friend
and prior research on context collapse indicates that
work-related dyads require some management [21, 32].
The analysis compares common reasons for unfriending
for the two friend types (high school and work)to
determine the dynamics of unfriending behavior through
multivariate analysis of covariance (MANCOVA). The
analysis used friend type as the independent variable and
polarizing topics, frequent/unimportant topics, everyday
life topics, inappropriate topics and disliked behavior
as the dependent variable - see Ta bl e 5 for reliability
measures and sample items for the constructs. The
construct change was removed from the analysis as its
alpha level was less than a .60 threshold. The analysis
used age, gender, education, years of social networking
use, number of friends, number of interactions number
of unfriends and whether the person lives in the U.S.
as control variables. A total of 1,077 survey respondents
were analyzed in this analysis. The analysis compared
206 high school friend types to 871 non-high school
friend types in Ta b l e 3. A second analysis of the same
survey respondents was conducted to compare 119 work
friends to 958 non-work friends in Ta b l e 4 .
The results show that survey respondents who
unfriended high school friend types indicated that
the person they unfriended posted statistically signif-
icantly more often about polarizing topics and fre-
quent/unimportant topics than friends who were not from
high school. The analysis found no differences in how
the survey respondent perceived the posts of the person
who they unfriended regarding everyday life posts and
inappropriate posts. Facebook users were less likely to
unfriend their high school friends for offline behavior
compared to other friend types.
There were covariates that show statistically sig-
nificant differences for three of the four topics areas
and the offline category. Higher educated survey re-
spondents perceived that Facebook friends posted too
often about polarizing topics compared to those who
had lower levels of education. Survey respondents in the
U.S. perceived that their friends posted too often about
polarizing topics than those who lived outside the U.S.
Younger survey respondents were less tolerant of their
Facebook friends posting too often about unimportant
topics than older survey respondents. Female survey re-
spondents were more tolerant regarding their friends fre-
quent/unimportant posts compared to male respondents.
Survey respondents who did more unfriending were less
tolerant of their friends posts about everyday life events
than those who did unfriended fewer members of their
social network. Older Facebook users were less likely to
say that the unfriending of their high school friends was
related to disliked behavior. Female respondents were
more likely to say that the unfriending of their high
school friends was related to disliked behavior compared
to male survey respondents. Higher educated users were
less likely to say that the unfriending was related disliked
behavior.
The results in Ta b l e 4 show that survey respondents
who unfriended work friends indicated that the person
person they unfriended did not post too frequently about
unimportant topics compared to other friend types. The
analysis found no differences in how the survey re-
spondent perceived the posts of the person who they
unfriended regarding inappropriate posts, everyday life
posts and polarizing posts. Work friends were more
likely to be unfriended for engaging in disliked behavior
than non-work friends; i.e. work friends were unfriended
more often for their non-computer-mediated behavior.
There were covariates that show statistically signifi-
cant differences for three of the four online topics areas
and the offline category. As in the analysis regarding high
school friends, female survey respondents were more tol-
erant regarding their friends frequent/unimportant posts
compared to male respondents. Survey respondents who
did more unfriending were less tolerant friends posts
about everyday life events than those who did unfriended
fewer members of their social network. The last two
topics have similar findings to the high school friend
results. Higher educated survey respondents perceived
that Facebook friends posted too often about polarizing
topics compared to those who had lower levels of ed-
ucation. Survey respondents in the U.S. perceived that
their friends posted too often about polarizing topics
than those who lived outside the U.S. Older Facebook
users were less likely to say that the unfriending of their
work friends was related to disliked behavior. Female
respondents were more likely to say that the unfriending
of their work friends was related to disliked behavior
compared to male survey respondents.
5. Discussion
The results of this research are helpful in that they
contextualize friendships and unfriending beyond broad
1681
Tab le 3
HIGH SCHOOL FRIENDS AND COMMON REASONS FOR
UNFRIENDING
Topic H.S. Mean Non-H.S.
Mean
Diff Sig
Polarizing 3.133 2.703 .430 .003 **
Frequent/-
Unimportant
4.000 3.674 .326 .031 *
Everyday
Life
2.117 2.557 -.140 .145
Inappropriate 2.493 2.644 .150 .168
Disliked
Behavior
3.864 4.268 -.584 .001 ***
Covariate Results
Topic Covariate p< .05
Polarizing ed B=.129 p=.019 *
US B=-.402 p=.002 **
Frequent/Unimportant gender B=-.330 p=.011 *
Everyday Life num-unfriend B=.071 p=.020 *
Inappropriate NONE
Disliked Behavior
age B=-.107 p=.003 **
gender B=.460 p=.001 ***
ed B=-.112 p=.043 *
*p< .05; ** p< .01; *** p< .001
Bis the Bcoefficient for the MANCOVA
Means based on Likert-type questions 1-7
H.S. Mean - High School Mean for the topic
Non-H.S. Mean - The mean for all other friend types for the topic
Diff - Mean difference H.S. to non-H.S.
ed - Education where education is increasing levels of education
US - 0 denotes U.S. survey respondent and 1 denotes non-U.S. survey
respondents
age - age where age is increasing age
gender - 0 denotes male survey respondents and 1 denotes female
survey respondents
num-unfriends - number of unfriends the survey respondent has enacted
categories of friend on Facebook in the face of context
collapse. Many different kinds of friends may be co-
located on Facebook because the site serves as a gen-
eral purpose social network site as opposed to more
specialized sites (e.g. LinkedIn which is designed for
professional contacts). The analysis shows some of the
most common types of friends who are unfriended and
friend types who commonly do unfriending. The general
term of friend on social networking sites can be mis-
leading because a given dyad does not always represent
friendship in the common sense as the tie strength may
vary from weak to strong [4, 2]. Some friend types
have strongly defined organizational boundaries like high
school friend, work friend, college, and family member
where other friend types are more amorphous like friend
of a friend, common interest friend, and friend through
Tab le 4
WORK FRIENDS AND COMMON REASONS FOR UNFRIENDING
Topic Work Mean Non-Work
Mean
Diff Sig
Frequent/-
Unimportant
3.391 3.780 -.389 .041 *
Inappropriate 2.305 2.549 -.244 .075
Everyday
Life
2.216 2.350 .134 .267
Polarizing 2.755 2.789 -.034 .853
Disliked
Behavior
4.499 4.113 .386 .035 *
Covariate Results
Topic Covariate p< .05
Frequent/Unimportant gender B=-.322 p=.013 *
Inappropriate NONE
Everyday Life num-unfriend B=.067 p=.027 *
Polarizing ed B=.125 p=.024 *
US B=-.415 p=.001 ***
Disliked Behavior age B=-.112 p=.003 **
gender B=.454 p=.001 ***
*p< .05; ** p< .01; *** p< .001
Bis the Bcoefficient for the MANCOVA
Means based on Likert-type questions 1-7
Work Mean - Work Mean for the topic
Non-Work Mean - The mean for all other friend types for the topic
Diff - Mean difference work to non-work
gender - 0 denotes male survey respondents and 1 denotes female
survey respondents
num-unfriends - number of unfriends the survey respondent has enacted
ed - Education where education is increasing levels of education
US - 0 denotes U.S. survey respondent and 1 denotes non-U.S. survey
respondents
spouse.
The goal of capturing the friend types is to gain
better insight into the commonly found contexts for
online friends. Broadly four types of friends are most
commonly unfriended on the network (53.7%) are: High
School, Other, Friend of a Friend, and Work. The goal
was not to collect the entire set of every kind of rela-
tionship but contextualize unfriending into a relatively
small number of categories. 87.5% of people chose
one of the fifteen categories provided (12.5% choose
other) and three categories captured less than 1% of
unfriending (friend through child, neighbor and friend
through parent). The results help understand patterns of
friendship and dissolution.
The most common type of friend who is unfriended
is from a relatively well-defined organizational structure;
most users could clearly categorize a person as someone
with whom they went to high school or not. It may
be that high school friends on Facebook were never
1682
Tab le 5
RELIABILITY MEASURES FOR CONSTRUCTS
Construct Cronbach’s
alpha
Num
of
Items
Sample items
“the person I
unfriended posted
too often about
item
N.
Polarizing .754 2 politics, religion 1096
Frequent/-
Unimportant
.693 2 unimportant, too
frequently
1140
Everyday
Life
.908 11 spouse, pets,
celebrities, eating
habits
973
Inappropriate .808 6 cursing, sex, sexist,
racist
1018
Disliked
Behavior
.919 7 dislike, distrust,
betray, did misdeed
999
Change .573 5 incompatible friends,
romantic end,
learned new
information, moved
away (geographical)
1096
close and became friends more for social surveillance
purposes rather than to keep in touch with the person on
a more personal level. Joinson’s [14] research regarding
Facebook users’ motivations and uses of SNSs found that
keeping in touch [with friends and acquaintances] was
the main motivation of most users (47.3%), and social
surveillance was the second largest motivation (17.3%).
High school friends may have accepted the friend request
for one of boyd’s [2] 12 categories of friends that is not
an actual friend but one that represents a weaker tie such
as “[someone] who it would be socially inappropriate to
say no to because you know them,” or it was easier to
accept the friend request than to reject it [2]. The dyad
from high school may have been friends on the social
network largely because of the organizational context
and the number of friends in common but eventually
the friendship dissolved.
High school friends appear to be unfriended for dis-
cussing polarizing topics too often (politics and religion)
and for posting too frequently about unimportant topics
compared to other friend types. High school friends did
not post too often about every day life topics or post too
often about inappropriate topics (sex, racist comments,
etc.) compared to other friend types. Additionally, high
school friends were far less likely to be unfriended
for disliked offline behavior compared to other friend
types. It may be that people who are friends from high
school did not know the political or religious views of
their high school classmate when they became friends
on Facebook. It is also possible that the political or
religious views once held in high school have changed
by one or both members of the dyad. McPherson et al.
[22] notes that friendships tend to be formed by those
who share similar race and ethnicity, followed by age,
religion, education, occupation and gender. Strongly held
views on polarizing topics such as politics and religion
may be difficult to reach agreement on between friends
who hold strong opposing views. One way of managing
context collapse is to avoid discussing these potentially
hazardous topics but not everyone follows the lowest
common denominator approach and some may feel quite
free to discuss deeply personal matters with their social
network. High school friends may not be seen as often as
other friend types for geographical reasons so these high
school friends may be unfriended less often for disliked
offline behavior.
Work-related friends appear to be unfriended for
disliked offline behavior more often compared to other
friend types. Work friends were less likely to be un-
friended for posting too often about unimportant topics
compared to other friend types. There were no statis-
tically significant differences for inappropriate posting,
everyday life posting and polarizing posts compared
to other friend types. Work-related friends was inten-
tionally broad to cover any work-related relationship
which can include working in the same company (co-
workers), buyers & suppliers (outside company), pro-
fessional societies, etc. Work-related friendships may
mean that the dyad sees each other in non-computer-
mediated environments (in real life) more often than
other relationships (e.g. high school friends). It may be
harder to unfriend someone that you see more often for
their posting content because the unfriended person may
confront the person and ask why they were unfriended.
However, when one member of the dyad engages in
disliked behavior the other person may feel that the
online relationship should be terminated. Posting too
frequently about unimportant topics was less likely to be
a factor in work-related unfriending; it may be that dyads
who see each other more frequently are more tolerant of
frequent posting of those they see often. Work-related
dyads may also know the other’s view of polarizing
topics and either disregard opinions that are contrary or
simply not engage in a discussion about these polarizing
topics.
Message content on Facebook may share some sim-
ilarities to that of the social network site Twitter. Java
et al. [13] and Naaman et al. [23] classify many posts
on Twitter to be about the daily life of the user and
Marwick and boyd [21] state that users often use the
site as a running publicly accessible personal diary.
Facebook users may exhibit similar posting behavior
where they are less concerned about how the imagined
audience consumes their posts and may use Facebook
1683
more for self-expression like a personal diary or to
inform others of their daily routines (meformers). In the
high-school related dyads posting about personal topics
like politics and religion may cause difficulty in the dyad
and eventually friendship dissolution whereas in other
contexts it seems to cause less difficulty. Context matters
in the context collapse of Facebook; less than 1% of
survey respondents said they had less than a high school
education which means that people in the survey who
were identified as a certain type of friend were also likely
to be a high-school friend of someone else (e.g. one dyad
may be a high-school friend and another dyad of the
same person may be work-related). The interpretation of
the post or the interpretation of the relationship may have
an large impact on whether a person decides to unfriend
another on the site.
The individual user may acquire social capital
through the use of Facebook [8]. Social capital generally
refers to the skills and knowledge that are accessible
to an individual through their relationships with others
[5]. Coleman [5] notes that an important form of social
capital is the ability to acquire information through
relationships; information itself may be valued highly
and is generally costly to acquire. Access to a large
and weakly-tied tied network may provide more benefits
a smaller strongly-tied network [10]. Ellison et al. [8]
found a strong positive relationship with Facebook use
and bridging social capital. Friendship dissolution may
be related to a loss of social capital as ties are pruned. A
lowest common denominator approach may reduce the
amount of unfriending on a SNS but also may reduce
the usefulness of the site [32]. It is likely that there
is a life-cycle to the relationships that are held online;
some relationships will be maintained or strengthened
while others that will be dissolved through unfriending.
Understanding the specific context of the dyad’s friend
relationship may help bring greater understanding to the
life-cycle of online relationships.
6. Limitations
Participants in the present study were not recruited
randomly. Respondents were recruited via Twitter by
approaching users who had used the terms “unfriend,”
“defriend,” or “unfriending.” The goal this sampling
method was to reach people from whom Facebook’s
unfriending tool was meaningful, relevant, and recent,
but it may also have led to the over-representation
of those who had been strongly affected by a recent
experience.
The survey did not assess the role of privacy in
unfriending behaviors related to context collapse. Privacy
may be a factor in many unfriending decisions and is not
used in the models in this research. Future research may
look at the role of privacy specifically in the face of
context collapse to determine how privacy controls such
as limiting the dissemination of posts to specific users
or categories of users can be used to better the dyadic
relationship. Facebook users have the option to hide
posts from specific users and this technical capability
was not analyzed in this research. Facebook users may
have multiple accounts to manage different contexts
(privacy) and the survey did not assess whether users
had multiple accounts.
7. Conclusions
This research attempts to answer two research questions
- what are the common types of friends who are un-
friended on Facebook and what are the factors related
to unfriending two particular friend types. The research
can successfully categorize 87.5% of friend types into
15 groups (the remaining are in the other category). The
top four categories account for over 50% of unfriending;
these include high school friend, other, friend of a friend
and work friend.
Two friend types were investigated in greater depth,
the high school friend and work-related friend. High
school friends were more commonly unfriended for
posting too often about polarizing topics and posting
too frequently about unimportant topics compared to
other friend types. High school friends were less likely
to be unfriended for disliked offline behavior compared
to other friends. Work friends were more commonly
unfriended for disliked offline behavior compared to
other friend types. Posting frequently about unimportant
topics was less likely to be related to unfriending for
work-related friends compared to other friend types.
Examining unfriending behavior on Facebook pro-
vides a unique opportunity to study friendship dissolu-
tion, because there is a definite marker for the beginning
of the online relationship (the initial friend request)
and a marker for the dissolution of the relationship
through unfriending. This study examined two friend
types in depth, work friends and high school friends;
future analysis can more fully explore the friend types
to determine how friend types are similar and how they
are different.
References
[1] Baxter, L. A. (1979). Self-disclosure as a relationship dis-
engagement strategy: An exploratory investigation. Human
Communication Research, 5:215–222.
[2] boyd, D. M. (2006). Friends, friendsters and top 8:
1684
Writing community into being on social network sites. First
Monday, 11(12):Online.
[3] boyd, D. M. (2008). Taken out of context: American teen
sociality in networked publics. Phd thesis, University of
California, Berkeley, Berkley, CA.
[4] boyd, D. M. and Ellison, N. B. (2007). Social net-
work sites: Definition, history and scholarship. Journal of
Computer-Mediated Communication, 13(1):1.
[5] Coleman, J. S. (1988). Social capital in the creation of
human capital. American Journal of Sociology, 94:s95–
s120.
[6] Dillman, D. A., Smyth, J. D., and Christian, L. M. (2008).
Internet, Mail, and Mixed-Mode Surveys: The Tailored
Design Method. Wiley, 3rd edition.
[7] Duck, S. W. (1982). Personal Relationships and Personal
Constructs: A Study of Friendship Formation. John Wiley.
[8] Ellison, N. B., Steinfield, C., and Lampe, C. (2007). The
benefits of facebook "friends:" social capital and college
students’ use of online social network sites. Journal of
Computer-Mediated Communication, 12:1143–1168.
[9] Goldsmith, B. (2009). "unfriend" named word of 2009.
Reuters.
[10] Granovetter, M. S. (1973). The strength of weak ties.
American Journal of Sociology, 78(6):1360–1380.
[11] Haewoon Kwak, H. C. and Moon, S. (2011). Fragile
online relationship: A first look at unfollow dynamics in
twitter. In In Proceedings of CHI 2011, Vancouver, BC.
[12] Hogan, B. (2010). The presentation of self in the age
of social media: Distinguising performances and exhibi-
tions online. Bulletin of Science, Technology & Society,
30(6):377–386.
[13] Java, A., Finin, T., Song, X., and Tseng, B. (2007).
Why we twitter: Understanding microblogging usage and
communities. In 9th WebKDD and 1st SNA-KDD 2007
workshop on Web mining and social network analysis.
[14] Joinson, A. N. (2008). Looking at, looking up or keeping
up with people?: motives and use of facebook. In twenty-
sixth annual SIGCHI conference on Human factors in
computing systems.
[15] King, W. R. and He, J. (2006). A meta-analysis of the
technology acceptance model. Information & Management,
43(6):740–755.
[16] Lea, M. and Duck, S. (1982). A model for the role
of similarity of values in frienship development. British
Journal of Social Psyschology, 21:301–310.
[17] Lee, Y., Kozar, K. A., and Larsen, K. R. (2003). The
technology acceptance model: Past, present, and future.
Communications of the Association for Information Systems,
12(50):752–780.
[18] Leech, N., Barrett, K., and Morgan, G. (2008). SPSS
for intermediate statistics: Use and interpretation. Erl-
baum/Taylor & Francis Group., 3rd edition.
[19] Lewis, J. and West, A. (2009). ’friending’: London-based
undergraduates’ experience of facebook. new media and
society, 11(7):1209–1229.
[20] Madden, M. and Smith, A. (2012). Privacy management
on social media sites. Technical report, Pew Research
Center’s Internet and American Life Project.
[21] Marwick, A. E. and boyd, d. (2011). I tweet honestly, i
tweet passionately: Twitter users, context collapse, and the
imagined audience. new media and society, 13(1):114–133.
[22] McPherson, M., Smith-Lovin, L., and Cook, J. M. (2001).
Birds of a feather: Homophily in social networks. Annaul
Review of Sociology, 27:415–444.
[23] Naaman, M., Boase, J., and Lai, C.-H. (2010). Is it really
about me? message content in social awareness streams.
CSCW 2010, 2010:189–192.
[24] Nielsen (2012). The social media report 2012: Social
media comes of age. Technical report, Nielsen.
[25] Nuttal, C. and Gelles, D. (2010). Facebook becomes
bigger hit than google. Financial Times.
[26] Petter, S. and McLean, E. R. (2009). A meta-analytic
assessment of the delone and mclean is success model:
An examiiniation of is success at the individual level.
Information & Management, 46(3):159–166.
[27] Quercia, D., Bodaghi, M., and Crowcroft, J. (2012).
Losing "friends" on facebook. In Proceedings of WebSci
’12, Evansons, Illinois.
[28] Sibona, C. and Walczak, S. (2011). Unfriending on
facebook: Friend request and online/offline behavior analy-
sis. In Proceedings of the 2011 44th Hawaii International
Conference on System Sciences, volume 44, pages 1–10.
[29] Sibona, C. and Walczak, S. (2012). Purposive sampling
on twitter: A case study. In Proceedings of the 2012 45th
Hawaii International Conference on System Sciences, pages
3510 –3519.
[30] Sprecher, S. and Fehr, B. (1998). The dissolution of close
relationships. Edwards Brother.
[31] Vitak, J., Ellison, N. B., and Steinfield, C. (2010). The ties
that bond: Re-examining the relationship between facebook
use and bonding social capital. In Proceedings of the 2011
44th Hawaii International Conference on System Sciences,
volume 44, pages 1–10.
[32] Vitak, J., Lampe, C., Gray, R., and Ellison, N. B. (2012).
"why won’t you be my facebook friend?": strategies for
managing context collapse in the workplace. In Proceedings
of the 2012 iConference, iConference ’12, pages 555–557,
New York, NY, USA. ACM.
[33] Wang, S. S., Moon, S.-I., Kwon, K. H., Evans, C. A., and
Stefanone, M. A. (2010). Face off: Implications of visual
cues on initiating friendship on facebook. Computers in
Human Behavior, 26:226–234.
[34] Wright, P. H. (1984). Self-referent motiviation and the
intrisic quality of friendship. Journal of Social and Personal
Relationships, 1:115–30.
[35] Yoder, C. and Stutzman, F. (2011). Identifying social
capital in the facebook interface. In annual conference on
Human factors in computing systems. ACM.
1685
... These tactics have received increasing scholarly attention, given that they may thwart exposure to opposing political views, which is an essential aspect of well-functioning democracies (Kim and Chen 2015). Although extant research has provided important theoretical contributions on the content features that spark users' rejections (e.g., Neubaum et al. 2021a;Skoric et al. 2018) and the role that different social connections may play in social media curation (e.g., Sibona 2014), scant attention has been paid to users' perceptions of the online filtering process. Drawing upon social exchange theory (Homans 1958(Homans , 1961, this study aims to fill this gap in the literature by examining how users manage online exchanges of undesired content, how this content is comprised, and subsequent reactions towards it. ...
... Score of studies have suggested that social media filtering is a plausible pathway that users activate when they are exposed to content that they somehow dislike (e.g., Goyanes and Skoric 2021;John and Agbarya 2020;Sibona and Walczak 2011). Social media allows posts of all kinds, but it also enables users to freely conduct curating strategies in their feeds such as unfriending (Sibona 2014). Through these tactics, users engage in selective avoidance and break the social link with the source of the undesired information, thereby preventing further exposure to similar content (Skoric et al. 2018;Zhu et al. 2017). ...
... Similarly, online users appear to be more tolerant towards defiant content when they share a strong bond with the person who posted it (Valenzuela et al. 2018), whereas curation mechanisms may have consequences in face-to-face relationships (Yang et al. 2017). The opposite occurs with acquaintances and distant friends, who are the most common targets of filtering strategies (John and Dvir-Gvirsman 2015;Sibona 2014). Other recent studies have highlighted how a user's tolerance threshold seems to increase with relationally close users who provide them with emotional support (Neubaum et al. 2021b). ...
Article
Full-text available
Filtering strategies enable social media users to remove undesired content from their feeds, potentially creating homophilic environments. Although previous studies have addressed the individual-level factors and content features that influence these decisions, few have solely focused on users’ perceptions. Accordingly, this study applies social exchange theory to understand how users socially construct the process of unfriending. Based on 30 in-depth interviews with young Spaniards, we identify a widespread pattern of rejection over repetitive, opinion-challenging, and offensive posts, which we conceptualize as out-of-place content, a type of social media stimulus that hinders substantive online exchanges and challenges users’ understanding of social reality and individual values. This study contributes to current literature on unfriending by suggesting that filtering strategies are implemented gradually when posts overwhelm users’ tolerance threshold. Our findings also suggest that their deployment hinges on the closeness of the relationship between peers and social commitments formed in specific platforms. Future research is needed to assess to what extent the patterns identified in our interviews are present in the overall population.
... Here w ij does not need to be non-negative and takes values in R. We consider two update rules: dynamics is motivated by tie dynamics that can be traced back to Schelling's model of residential segregation [57]. In modern society, tie changes on Facebook [58] and Twitter [65,38] can be easily triggered by disparities on their opinions [35,58], especially among the users who are most politically engaged. ...
... Here w ij does not need to be non-negative and takes values in R. We consider two update rules: dynamics is motivated by tie dynamics that can be traced back to Schelling's model of residential segregation [57]. In modern society, tie changes on Facebook [58] and Twitter [65,38] can be easily triggered by disparities on their opinions [35,58], especially among the users who are most politically engaged. ...
... Por ejemplo, los usuarios más jóvenes están migrando hacia plataformas de redes sociales que ofrecen una comunicación más efímera, centrada en la temporalidad y la celebración social de momentos compartidos, en lugar de en la persistencia de los rastros de sus interacciones digitales (Bayer et al. 2015). En las PRS tradicionales, la gente limpia sus redes sociales de las voces disonantes o simplemente irritantes a través de acciones de filtro post hoc, como, por ejemplo, eliminar una amistad o dejar de seguir a alguien (Yang, Barnidge y Rojas 2017;Sibona 2014); lo que, en último término, crea entornos sociopolíticos más homogéneos. Dado que es mucho más probable que se eliminen o bloqueen las relaciones personales débiles, no podemos hablar de su fortaleza (John y Dvir-Gvirsman 2015). ...
Article
Full-text available
Los primeros estudios sobre redes sociales respaldaban visiones optimistas en relación con su impacto positivo en el desarrollo del capital social, y relacionaban su uso con la exposición a puntos de vista más diversos y a un mayor compromiso con la sociedad. Sin embargo, recientemente, los investigadores empezaron a analizar los comportamientos asociales que se pueden llevar a cabo en las redes sociales y a estudiar sus consecuencias sobre el desarrollo del capital social. En este ensayo, revisamos la literatura existente centrada en estudiar estas prácticas de evitación y desconexión selectiva y avanzamos en el concepto de ‘espacios digitales seguros’ -entornos online creados filtrando y eliminando post hoc a contactos en redes sociales-, con el objetivo de profundizar en el debate sobre sus consecuencias en las sociedades democráticas contemporáneas. Nuestros hallazgos apuntan al hecho de que los espacios digitales seguros pueden constituir un entorno fértil para la expresión cívica y política, especialmente para las minorías. Sin embargo, la creación de estos enclaves digitales puede también alejar aún más a las minorías del consenso político generalizado y podría llevar a una reducción de las oportunidades económicas y políticas de aquellos ciudadanos que están excluidos de los “espacios seguros”.
... Affordance utilization is driven by social identification and endorsement, which is also a manifestation of media control (Cabiddu, De Carlo, & Piccoli, 2014). Friending involves a subjective decision on whom to follow, which largely affects what appears in one's feed (Sibona, 2014). ...
Article
Full-text available
This study analyzed a survey sample from China and investigated how (1) news interest, (2) affordance utilization, and (3) friending were associated with consumptive news feed curation (CNFC), a practice of selective exposure, as well as the ways in which these associations were mediated and moderated by psychological factors. Findings showed that all 3 factors were positively associated with CNFC. Media locus of control (MLOC), namely, individuals’ beliefs in their ability to control their information environment, was found to be a positive mediator. Namely, the three independent variables led to greater MLOC before facilitating CNFC. Need for cognition (NFC) was a moderator. That is, the main associations became weaker among those with higher NFC, suggesting that people with a stronger preference for analytical and logical information processing were less likely to curate for consumptive purposes. Moderating effect of NFC was also found on the indirect effects of news interest and affordance utilization on CNFC.
Article
This study explores the antecedents and consequences of unfriending in social media settings. Employing an online panel survey (N = 990), this study investigates how exposure to hate speech is associated with political talk through social media unfriending. Findings suggest that social media users who are often exposed to hate speech towards specific groups and relevant issues are more likely to unfriend others (i.e., blocking and unfollowing) in social media. Those who unfriend others are less likely to talk about public and political agendas with those with cross-cutting views but tend to often engage in like-minded political talk. In addition, this study found indirect-effects associations, indicating that social media users who are exposed to hate speech are less likely to engage in cross-cutting talk but more likely to participate in like-minded talk because they unfriend other users in social media.
Chapter
Full-text available
With the popularity of social media, researchers and designers must consider a wide variety of privacy concerns while optimizing for meaningful social interactions and connection. While much of the privacy literature has focused on information disclosures, the interpersonal dynamics associated with being on social media make it important for us to look beyond informational privacy concerns to view privacy as a form of interpersonal boundary regulation. In other words, attaining the right level of privacy on social media is a process of negotiating how much, how little, or when we desire to interact with others, as well as the types of information we choose to share with them or allow them to share about us. We propose a framework for how researchers and practitioners can think about privacy as a form of interpersonal boundary regulation on social media by introducing five boundary types (i.e., relational, network, territorial, disclosure, and interactional) social media users manage. We conclude by providing tools for assessing privacy concerns in social media, as well as noting several challenges that must be overcome to help people to engage more fully and stay on social media.
Article
Calls to “break up” radical echo chambers by injecting them with alternative viewpoints are common. Yet, thus far there is little evidence about the impact of such counter-messaging. To what extent and how do individuals who inhabit a radical echo chamber engage with messages that challenge their core beliefs? Drawing on data from the radical right forum Stormfront we address this question with a large-scale content and longitudinal analysis of users’ posting behavior, which analyses more than 35,000 English language contributions to the forum spanning 2011 through 2013. Our findings show that engaging with oppositional views is actually a core practice among Stromfront users which invites active participation and encourages engagement. Indeed, many “echoes” in the echo chamber we studied were not core beliefs being restated, but the sound of opposing viewpoints being undermined and marginalized. These findings underscore the limited potential for counter-messages to undermine radical echo chambers.
Article
Full-text available
As social network sites like MySpace and Facebook emerged, American teenagers began adopting them as spaces to mark identity and socialize with peers. Teens leveraged these sites for a wide array of everyday social practices - gossiping, flirting, joking around, sharing information, and simply hanging out. While social network sites were predominantly used by teens as a peer-based social outlet, the unchartered nature of these sites generated fear among adults. This dissertation documents my 2.5-year ethnographic study of American teens' engagement with social network sites and the ways in which their participation supported and complicated three practices - self-presentation, peer sociality, and negotiating adult society. My analysis centers on how social network sites can be understood as networked publics which are simultaneously (1) the space constructed through networked technologies and (2) the imagined community that emerges as a result of the intersection of people, technology, and practice. Networked publics support many of the same practices as unmediated publics, but their structural differences often inflect practices in unique ways. Four properties - persistence, searchability, replicability, and scalability - and three dynamics - invisible audiences, collapsed contexts, and the blurring of public and private - are examined and woven throughout the discussion. While teenagers primarily leverage social network sites to engage in common practices, the properties of these sites configured their practices and teens were forced to contend with the resultant dynamics. Often, in doing so, they reworked the technology for their purposes. As teenagers learned to navigate social network sites, they developed potent strategies for managing the complexities of and social awkwardness incurred by these sites. Their strategies reveal how new forms of social media are incorporated into everyday life, complicating some practices and reinforcing others. New technologies reshape public life, but teens' engagement also reconfigures the technology itself.
Article
Full-text available
Recruiting populations for research is problematic and utilizing online social network tools may facilitate the recruitment process. This research examines recruitment through Twitter's @reply mechanism and compares the results to other survey recruitment methods. Four methods were used to recruit survey takers to a survey about social networking sites, Twitter recruitment, Face book recruitment for a pre-test, self-selected survey takers, and a retweet by an influential Twitter user. A total of 7,327 recruitment tweets were sent to Twitter users, 2,865 users started the survey and 1,544 users completed it which yielded an overall completion rate of 21.3 percent. The research presents the techniques used to make recruitment through Twitter successful. These results indicate that recruitment through online social network sites like Twitter is a viable recruitment method and may be helpful to understand emerging Internet-based phenomena.
Article
Full-text available
While the technology acceptance model (TAM), introduced in 1986, continues to be the most widely applied theoretical model in the IS field, few previous efforts examined its accomplishments and limitations. This study traces TAM's history, investigates its findings, and cautiously predicts its future trajectory. One hundred and one articles published by leading IS journals and conferences in the past eighteen years are examined and summarized. An open- ended survey of thirty-two leading IS researchers assisted in critically examining TAM and specifying future directions.
Article
Previous research has shown that similarity of values can significantly enhance interpersonal attraction. The present study sought to refine and clarify this finding within the context of friendship development. The relationship between value similarity and friendship choice for subjects was examined cross-sectionally after three periods of acquaintance: 1–2 months, 4–6 months, and 12+ months. Two factors, namely the importance of the values to the subjects and the uncommonness of the similarity for them, were hypothesized to affect this relationship. The hypothesis was supported. A further hypothesis was that the salience of these factors for subjects was dependent upon factors that related to the length of their friendships. The results offered only marginal support for this hypothesis. Additional data on unreciprocated friendship choices are presented. The results are discussed in relation to the hypothesized predictive function (to reduce interpersonal risk or uncertainty) as well as the supportive function of value similarity, and the wider implications of the results are considered.
Conference Paper
Recent analyses of self-reported data (mainly survey data) seem to suggest that social rules for ending relationships are transformed on Facebook. There seem to be a radical difference between offline and online worlds: reasons for ending online relationships are different than those for ending offline ones. These preliminary findings are, however, not supported by any quantitative evidence, and that is why we put them to test. We consider a variety of factors (e.g., age, gender, personality traits) that studies in sociology have found to be associated with friendship dissolution in the real world and study whether these factors are still important in the context of Facebook. Upon analyzing 34,012 Facebook relationships, we found that, on average, a relationship is more likely to break if it is not embedded in the same social circle, if it is between two people whose ages differ, and if one of the two is neurotic or introvert. Interestingly, we also found that a relationship with a common female friend is more robust than that with a common male friend. These findings are in line with previous analyses of another popular social-networking platform, that of Twitter. All this goes to suggest that there is not much difference between offline and online worlds and, given this predictability, one could easily build tools for monitoring online relations.
Article
Presentation of self (via Goffman) is becoming increasingly popular as a means for explaining differences in meaning and activity of online participation. This article argues that self-presentation can be split into performances, which take place in synchronous “situations,” and artifacts, which take place in asynchronous “exhibitions.” Goffman’s dramaturgical approach (including the notions of front and back stage) focuses on situations. Social media, on the other hand, frequently employs exhibitions, such as lists of status updates and sets of photos, alongside situational activities, such as chatting. A key difference in exhibitions is the virtual “curator” that manages and redistributes this digital content. This article introduces the exhibitional approach and the curator and suggests ways in which this approach can extend present work concerning online presentation of self. It introduces a theory of “lowest common denominator” culture employing the exhibitional approach.
Article
Interactants are strategic goal seekers in their interpersonal communication. However, to date, research has concentrated almost exclusively on the communicative strategies by which actors achieve a goal of relationship initiation. Relationship disengagement occupies an important motivational force, as well. This study initiated exploration of the communicative strategies by which actors disengage their relationships, focusing in particular on the verbal strategy of self-disclosure. Undergraduate volunteers were exposed to one of four hypothetical scenarios: Respondent Intent (Maintain or Disengage) and Other's Intent (Maintain or Disengage). Twenty Likert-type items of willingness to self-disclose on a variety of topics constituted the dependent measures and were clustered into three primary factors. Multivariate analysis of variance revealed that respondents were less willing to self-disclose when they desired to disengage the relationship.