USENIX Association Tenth Symposium On Usable Privacy and Security 295
We divided our dataset into two groups (scenario 1 and 2). This
was done by analyzing the answers to one of the survey ques-
tions, which explicitly asked participants if they have any strangers
among their Facebook friends. 62% of the participants confirmed
that they did. Then, we compared these two groups in how much
they used each of the friendship factors. In what follows, we de-
scribe the results of our comparison.
We found that while only 68% of participants in S1 consider
the knowledge of the requester in real life (KRL) in their decision
process, this number jumps to 91% for S2, with th difference being
statistically significant (Mann-Whitney’s test: p = 0.0003 < 0.05).
We interpret this result as an indicator for the level of awareness in
these two groups.
For profile name (PRN), although we did not see much difference
between the groups, participants in S1 reported more interest than
those in S2 (80% vs 87%) for using profile name as a factor.
For common background, we looked at four types of background
information, including city of birth (CityB), city of Living (CityL),
schools/universities attended (School), and common hobbies/interests
(HOB). For the first three factors, we could not find statistically
significant difference between participants in S1 and S2. However,
S2 participants were slightly more interested in them (CityB: 19%
vs 12%, CityL: 21% vs 15%, School: 29% vs 25%). The differ-
ence was significant when it came to “common hobbies/interests”
(HOB). While 40% of participants from S1 employed this as a
friendship factor, there were only 25% in S2 who did so (Mann-
Whitney’s test: p = 0.03 < 0.05). This result could be leveraged as
a cue by socialbots to customize profile information in order to in-
crease the chance of getting their friend requests accepted. “Being
active” (BAF) was also more popular among S1 (76%) members
rather than S2 members (64%), although the difference was not
statistically significant.
Regarding the “number of mutual friends” (NMF), we saw sig-
nificantly more members in S1 (37%) than S2 (19%) employing
it as a factor in their decisions (Mann-Whitney’s test: p = 0.01
< 0.05). Also, comparison of S1 and S2 in terms of “closeness
of mutual friends” (CMF) indicated that more participants in S2
(77%) cared about it than in S1 (57%) (Mann-Whitney’s test: p =
0.03 < 0.05). The results of comparison for NMF and CMF sug-
gest that informing users about the closeness of the requester with
the mutual friends would be more effective than only showing the
number of such friends (available in current interface).
For user’s activity pattern, we found that participants from S2
were slightly more interested in UAP than from S1. We suspect that
the absence of statistically significant results in regards to UAP is
due to the difficulty of finding a pattern, as we had this feedback in
exploratory study. Regarding closeness of friendship relationship,
we did not find statistically significant difference between S1 and
S2. This result is expected, as it more relates to scenarios in which
friendship requests are sent from known users, according to our in-
terview data. Finally, we could not find statistically significant dif-
ference between participants in S1 (20%) and S2 (25%) regarding
application-based friendship (APF), although we expected to ob-
serve significantly more participants in S1 who rely on this factor.
This might be because of the shortage in the number of participants
who have received this type of friendship requests.
4. DISCUSSION
Considering the first goal defined for the survey, we analyzed the
data related to each of the factors to investigate how much they are
used. As the result, except for UAP and APF, all other friendship
factors were employed by at least more than 50% of participants,
which shows the validity of friendship factors inferred from the ex-
ploratory study. In addition, we asked survey participants to share
with us other friendship factors if they have any. Analysis of an-
swers to this question did not add to the factors themselves. The
participants who answered this question, mostly suggested features
that could be added to the friend request decision dialogues. As
mentioned earlier, since having access to user’s wall is usually not
possible, people may not consider UAP as a factor. However, ac-
cording to the exploratory study, participants prefer to have infor-
mation about the activity patterns of requesters. For APF, a low
percentage was expected from the interview study, in which only
few participants reported receiving friendship requests from appli-
cations.
For the second goal, the idea of focusing on the results of groups
who have strangers in their Facebook friends, and comparing it to
those who do not have, helped us to investigate and uncover the
impact of the friendship factors. As the results show, we found
four friendship factors (KRL, HOB, NMF, CMF) could play a no-
table role and influence users’ decisions. This result could be lever-
aged for improving the interface design so that users make more
informed decisions.
4.1 Interface Design Recommendations
As discussed before, the results from the analysis of our survey
data revealed interesting points about friendship factors that could
be used for improving the Facebook interface. Therefore, we offer
the following suggestions for designing user interfaces for accept-
ing friendship requests:
• The interface should convey the importance of making accu-
rate decisions about friendship requests and encourage users
to make informed decisions. For instance, users could be no-
tified by a pop-up window (similar to current design) asking
users to go to another page in order to make an informed de-
cision, using useful information or a check list. Having such
a feature in the interface is supported by the OLFFA model
since it helps users to appreciate the importance of these de-
cisions.
• The interface could contain a message box so that requesters
can briefly specify how they know the user. Another sug-
gestion is to give access to photos selected by each user to
better recognize the requester. We had reports from partici-
pants of both studies complaining about unclear small pho-
tos. This kind of improvement would facilitate the investiga-
tion/maintenance actions (in the decision making process of
OLFFA model) for users.
• It could be helpful if user had access to statistics (number of
likes, number of comments, number of personal messages,
number of common photos) about interaction with his/her
friends. In this case, it is easier to investigate closeness of
mutual friends, which was shown to be more useful than
only the number of mutual friends. In other words, this fea-
ture would facilitate the Investigation Actions in the OLFFA
model for finding out closeness of mutual friends.
• The interface could encourage the user to specify the access
level for new friends at the time the user accepts a friend re-
quest. We suggest this because our analysis showed that 31%
of participants in S1 did not define any access level for their
friends while 9% in S2 reported similar behavior. Therefore,
this could be helpful (at least for users who accept stranger’s
requests) as a facilitator for performing maintenance actions
and help users to be more cautious about the level of access
they grant to their Facebook friends.