Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA

Evaluating Compliance-Without-Pressure Techniques for
Increasing Participation in Online Communities
Mikhil Masli and Loren Terveen
GroupLens Research
Department of Computer Science and Engineering
University of Minnesota, Minneapolis, MN, USA{masli, terveen}@cs.umn.edu
ABSTRACTSocial psychology offers several theories of potential use fordesigning techniques to increase user contributions to online
communities. Some of these techniques follow the “compliance without pressure” approach, where users are led tocomply with a request without being subjected to any obvious external pressure. We evaluated two such techniques –foot-in-the-door and low-ball – in the context of Cyclopath, ageographic wiki. We found that while both techniques succeeded, low-ball elicited more work than foot-in-the-door.
We discuss design and research implications of applying
these (and other such techniques) in online communities.
Author Keywords

Increasing participation; social production; online
communities; compliance; foot-in-the-door; low-ball
ACM Classification Keywords

H.5.3 Information Interfaces and Presentation: Group and Organizational Interfaces
General Terms

Human Factors, Design• Low-ball (LB): Once a person commits to a request, he/she
is more likely to perform it at a later stage, even if its costis increased [8].
While these techniques have been evaluated extensively inseveral offline contexts, there has been very little evaluationin the world of computer-mediated communication [16, 17],and none in online social production communities.
We evaluated FITD and LB techniques in the context of Cyclopath1 , an online geographic wiki that offers route-finding
services for cyclists in the metropolitan area of MinneapolisSt. Paul, Minnesota, USA. We carried out a work campaign
in which we requested Cyclopath users to contribute information to the map in the form of tags with the goal of improving
the map for the next cycling season. We conducted a fieldstudy and a follow-up survey and found that LB succeeded ineliciting more contributions than the control condition, while
FITD had limited success.
This paper is organized as follows. We first survey relevant
related work and explain the motivation to carry out empirical evaluation in the online context. Second, we describe
our field experiment, its results and their interpretation using theories from social psychology. Third, we describe ourfollow-up survey, and conclude with implications for design
and future research.

INTRODUCTION

A large body of literature from social psychology suggests
techniques that may be used to motivate people to contributeto these communities. One set of these techniques is known
as compliance without pressure [12]: these techniques are designed to increase compliance to requests in the absence of
any obvious sources of pressure. Two of the most popular
techniques are:• Foot-in-the-door (FITD): Once a person performs a small
request, he/she is more likely to perform a subsequent,larger demand [12].

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RELATED WORK
Social Production Communities

Social production communities [2, 14] let loosely-connected
users work together to produce information and artifacts ofvalue [10]. Collaborative filtering systems like MovieLens2
and Amazon leverage users’ ratings of items (movies, consumer products, etc.) to enable personalized recommendations. Q&A sites like Yahoo! Answers and Stack Overflow
form knowledge economies, where users spend points to ask
or boost the priority of questions and earn them for answering. Wikis take user-provided content to its logical end: anyone can add, edit, or delete anything. Wikipedia is among the
top 10 most popular sites on the Web, and smaller wikis are
ubiquitous. Because of the significant value produced by online communities, ensuring that they receive adequate member participation is an important research topic.
1
2

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cyclopath.org
www.movielens.org

Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA

Compliance Without Pressure

Compliance without pressure techniques are designed to leadpeople to comply with requests without any obvious sourceof external pressure. Researchers from social psychology andmarketing have developed several techniques that fall under
this category, e.g. FITD, LB, door-in-the-face [7], that’s-notall [3] and bait-and-switch. FITD is one of the oldest andthe most popular of them with well over a hundred studies
devoted to it over the last 50 years [4]. LB has also been foundto be one of the most effective of these techniques [21, 22].
Because of their effectiveness, FITD and LB are interesting
candidate solutions to the problem of under-contribution in
online communities, and we thus chose to investigate them.
Several theories have tried to explain why and how FITD
and LB work (or not). The most popular explanation forthe success of the FITD technique is Bem’s self-perception
theory [1], which postulates that when a person is induced
to comply with a smaller request, he/she is more likely tocomply with a subsequent, larger request because of perceiving himself/herself as the type of person that does such tasks.
Alternative theories including those citing psychological reactance, conformity to existing social norms including reciprocity and cognitive dissonance [11] have also been used to
explain both successes and failures of the FITD technique.
The LB effect has been generally explained using the theoryof commitment [8], which says that people generally tend to
stick to their commitments when acting in public view. We
elaborate on these techniques in a later section in this paper
while interpreting the results of our field experiment.
While compliance-without-pressure techniques may have potential to increase participation in online communities, if
users perceive these techniques as manipulative, their use
could negatively impact long-term member satisfaction andcommitment. Accordingly, in this work, along with evaluating how successful FITD and LB are in an online social production context, we also evaluate the extent to which they areharmful and discuss the pragmatic issues designers of online
communities might face when employing some of them.

can work from the confines of their homes), thereby raising questions over the effectiveness of the FITD and LB
techniques.
2. Nature of online communication. Email and similar
modes of communication are used most often by onlinesocial production communities to interact with their members, as it is the norm on the Internet. These modes arefundamentally not as personal as face-to-face or telephone
communication – modes used by most studies of compliance in offline situations. Further, due to problems of email
overload, it easy to ignore incoming messages. These reasons affect any interventions that use email as the underlying mode of communication.
Although online communities are different from their offline
counterparts in some respects, they are similar in many others. Indeed, the social sciences have provided design inspiration and specific techniques that Computer Supported Cooperative Work (CSCW) designers and researchers have used tocreate more effective online communities [28]. Researchers
have successfully applied theories and models like the Collective Effort Model [23, 25], goal-setting [25] and social comparison [20] to address the problem of under-contribution.
Closer to this work, the FITD technique has been shown tobe effective over email [16, 17].
Drawing inspiration from these successes, our research extends prior work in significant ways:• We empirically evaluate the FITD and LB techniques in thecontext of an online social production community using alive field experiment and a follow-up survey.
• We demonstrate that the LB technique is largely successful in eliciting a higher quantity of contributions, while the
FITD technique receives mixed results.
• Based on what we learned from our studies, we discuss theadvantages and limitations of employing these (and similar) techniques in real-world online social production communities.

NEED FOR EMPIRICAL EVALUATIONRESEARCH PLATFORM

This research focuses on empirically evaluating the techniques of FITD and LB in the context of an online social production community. Is this necessary? Could we not merely
assume findings from the offline settings of social psychology? Online communities have several key differences thatmakes them unique, and justify the need for an empirical evaluation of proven offline techniques:

Cyclopath went live in the summer of 2008. As of May 17,
2011, Cyclopath had 3,232 registered users and visits from69,754 different IP addresses. Cyclopath has served as an
excellent research platform for prior research on user behavior in social production communities, including studying efficient ways of eliciting contributions [29], user lifecycles [27]and specialization of contributions [26].

1. Anonymity on the Internet. Psychological phenomena
like cognitive dissonance, considered one of the factors behind the FITD and LB effects, as well as the LB effectitself have been shown to be more effective in public situations [5, 32], where visibility is higher (and consequently,
anonymity is lower). However, since obtaining an identity
on the Internet is cheap [13], online communications have ahigher degree of anonymity than offline situations. Hence,
it is not clear if online social production communities are
public (contributions are shared) or private spaces (people

Like any wiki, users contribute information to Cyclopath insets of edits called revisions. When a user makes the desirededits in the Cyclopath interface (e.g. add a point) and clicks“Save Changes”, they are saved as a single revision associatedwith the username of the user (if the user is logged in), IP address and a time-stamp (see [30] for a more in-depth description). All revisions are publicly visible and revertible (via the
Recent Changes list). So far, the Cyclopath map has seen
12,949 revisions (11,258 by 699 registered users and 1,691
anonymously).

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Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA

Each revision may contain edits to points, blocks, regions,notes and tags. Blocks (roads and trails like the Kennilworth
Trail) are useful for route-finding, points help define route
endpoints (e.g., from CS Building to Lagoon Theater), tags
enable more customized route requests (e.g., a route that ismore scenic, but less bumpy), and notes supplement blocks
included in a route with subjective information useful forevaluatint the route (e.g., “icy during the winter”).
Prior work in Cyclopath suggests that many notes contain potential tags [33]. If extracted, these tags could provide more
options for users to customize their routes. Further, this task
could be performed by any person, regardless of his/her familiarity with the note or the area on the map where the note
was applied (just like the task of fixing intersections [29]).
Hence we chose to ask Cyclopath’s users to do the task ofextracing tags from notes. Prior to the start of our experiment, users had added 6,373 tags (applied to 4,312 blocks
and points) and 8,405 notes (applied to 6,084 blocks).
EXPERIMENT DESIGN
Hypotheses and Variables

We conducted a field study in Cyclopath during winter 201011. Like bike-riding (at least, in colder climates), Cyclopath
use is seasonal – it sees over 150 route requests per day andover 100 revisions per week during the summer and only
about a third of those numbers during the winter. This madewinter a good time for our field study – any effects we observeare primarily due to our manipulation and not the general motivations that drive contributions during summer. As a part ofour field study, we requested Cyclopath users to contributetags to the resource.
Our experiment design was guided by two hypotheses:
H1. The FITD technique will result in higher compliance forthe contribution request than the request being presented
alone.
H2. The LB technique will result in higher compliance forthe contribution request than the request being presented
alone.
We measured compliance using two outcome (dependent)
variables:• Response: Whether the user responded at all and the number of responses per user (we allowed users to respond multiple times, as described later) to the target request.
• Quantity of Work: The amount of work done by the user
in response to our request, measured in terms of number oftag-applications to blocks and points, and number of newtags introduced into the tag vocabulary.
MethodPartitioning Users

We partitioned users into three groups – FITD (953 subjects),
LB (953 subjects), and a control group (951 subjects). However, since participation on Cyclopath is highly unequal (likemost voluntary online activities), we took care to ensure thatuser experience levels were more-or-less evenly distributed

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among the three groups, i.e. not all highly experienced users(measured by the number of prior revisions made) were assigned to the same group. Specifically, we ordered users indescending order by the number of revisions they saved andstepped through this list assigning users to control, FITD and
LB groups in a cyclic fashion.
Procedure

General structure. All communication with users was conducted via email. We presented both experimental groups(FITD and LB) with their initial contacts on December 9,2010 at 5 pm. We then followed this up with the target request (the real request for which we wanted compliance) toall groups, via email 6 days later3 , on December 15, 2010 at
5 pm.
It is important to note here that essentially, we are comparing 3 techniques of eliciting work: “simply asking users to dowork” (control) and two “enhanced ways of asking users to dowork” (FITD, LB). We could have evaluated other, intermediate techniques like Freedman and Fraser’s familiarity-only(related to FITD) [12] and commitment-but-no-increase-incost (related to LB) as well. However, in this paper, we have
explicitly chosen to evaluate FITD and LB in their entirety
and not part-by-part.
The following paragraphs detail the initial contact and the target request for the various groups (the control group received
no initial contact).
Initial contact – FITD. We sent email to the subjects in the
FITD group asking them to do the initial (small) task of extracting just one tag from a single note, with the subject line
“A tiny favor: Cyclopath needs your help!”. The key passage
was: Would you spare a minute to help this campaign? All
we are asking you to do is to read the following note and extract only one meaningful tag (one or two word label) from it.
The email also contained the note itself (we thought that oncethe subject eyeballed it, the task of extracting one tag would
seem trivial), a sample note-tag pair, and a link to an interface to submit the tag. This link launched a simple HTMLbased interface where the subject could re-read the note andenter the tag he/she extracted (see Figure 1(a)). For example,
a subject extracted the tags “Dirt path” from the note “dirtpath connects to Arcade beware of curb”. Since the initial
FITD contact had to be short and easy, we limited subjects tojust one attempt at it: if a subject clicked the link again, thesystem would display a message saying he/she has alreadycompleted the task. After the subject submitted the tag fromthe HTML interface, he/she was thanked.
Initial contact – LB. We asked the subjects in the LB group(with the same subject line) to agree to extract one tag froma single note, explicitly asserting that this task should takeonly a minute to complete. The key passages were: Would
you spare a minute to help this campaign? All we are asking
you to do is to read a note and extract only one tag (single
word label) from it (this should just take you a minute) and3
Prior research suggests that a short (near-zero) delay between theinitial and the target requests when both originate from the same
requester can tend to counteract the FITD effect [4, 19].

Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA(a) FITD Interface

Figure 2. Target request. Each subject could perform as many experimental trials as he/she wishes. The blue box showing the area the subject
was asked to work in, with the “I’m Done” button to end the trial at the
top right.

launched an experimental trial (the procedure as well as thecode for conducting trials was adapted from [29]):
1. Begin trial. The subject begins the trial by clicking on thelink provided in the email.

(b) LB Interface
Figure 1. Initial contact. We designed simple HTML-based interfaces
for the FITD subjects to perform their small task, and for the LB subjects to express their commitment.

If you agree now, we’ll contact you with specific instructions
in near future, after we have heard from more people. The
email also contained a sample note-tag pair and a link to aninterface to express commitment. This link launched a simple
HTML-based interface (similar to the FITD interface) where
the subject was thanked for agreeing (see Figure 1(b)).
Target request – all groups. Our target request to all threegroups was to extract as many tags as possible from a given
set of notes. To avoid any biases resulting from subjects’ selfselection, this email request was sent to every subject in the
FITD and LB groups, regardless of their response to the initial contact. Crucially, for the FITD and LB conditions, we
needed to explain why we were asking for more work thanin the original request. Our explanation was that Cyclopath
had miscalculated the amount of work required of each user
and that more work per user was needed in order to analyze
all notes by spring time4 . The key passage in this email was:
You will be presented with a area on the map. Read any notes
you find on blocks in this area and extract around 2-3 potentially useful tags (one or two word labels) from each note.
This should take you 15-20 minutes. The link in the email
4This argument was also included in the email sent to the control
group for uniformity, though not framed as an “excuse”.

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2. Select viewport. The system chooses a viewport (100 km2
area) randomly on the map, ensuring that there are at least
5 notes available to extract tags from.5
3. Display viewport. The map pans and zooms to the selected
viewport, and highlights it with a blue box. An instruction
dialog box pops up that details the task to be done, withbrief instructions on how to do it and links to help (see Figure 2). All blocks and points with notes were highlighted
with a purple halo.
4. Subject does work. The subject is now free to use the system. Although we explicitly asked the subject to work in
the assigned area, the system did not restrict him/her in any
way – the subject was free to make edits anywhere on themap.
5. End trial. The subject clicks a button labeled “I’m Done”,
which results in the completion of one trial. The subject
can now either leave Cyclopath, use it for other purposes,
or start another trial.
We recorded when the subjects started and finished the trials,
the number of trials requested, and everything they did as apart of those trials.
5This was to ensure that there was some work available to do. Further, at the outset of our analyses, we also verified that there were no
statistically significant differences in the number of notes available
per user and per trial among the three groups.

Session: Crowdsourcing & Peer Production II

Group
FITD
LB

CHI 2012, May 5–10, 2012, Austin, Texas, USA(a) Tags created per user.

Response
11.4% (109)
12.7% (121)

Table 1. Response to the initial contact. Response rates are low, but
typical of contributory behavior in social production communities.

Group
Control
FITD
LB

Response
6.14% (58)
5.14% (49)
7.35% (70)

Trials per subject
0.22 (205)0.10 (92)0.29 (272)Group
Control
FITD
LB

Total
70
99
193

Mean
0.07
0.10
0.20

SD
0.65
1.05
1.64

p
∗

(b) Tags applied per user.

Table 2. Response to the target request. The numbers in parantheses
are the respective absolute counts. There are no statistically significant
differences between the three groups of subjects.

Group
Control
FITD
LB

Total
542
571
1702

Mean
0.57
0.60
1.79

SD
5.07
6.05
18.07

p
∗

Table 3. Tagging work done per user in response to the target request.
∗ indicates statistical significance at the 0.1 level when compared with
control.

Results

We took a snapshot of the database on January 16, 2011. By
this date, 190 users completed 597 trials. We removed 28
trials from our analyses – 15 were unusually long (over 2
hours6) and 13 were done by 6 users who were not in anyof our groups (these users joined Cyclopath after the experiment started). This left us with 569 trials by 177 subjects. We
present our results organized by our outcome variables.
Response

Initial contact response. Table 1 shows the response to theinitial contact. Out of the 953 subjects in the FITD condition
to whom we sent the initial contact emails, 109 (11.4%) completed the short task. Out of the 953 subjects in the LB condition to whom we sent the initial contact emails, 121 (12.7%)
responded.
Target request response. Table 2 shows how subjects responded to the target request. We see no significant differences among groups in the response rates, or the number oftrials per subject. However, we found interesting differencesin the quantity of work done, as described in the following
sub-section.
Quantity of Work

Metrics. When a tag that does not already exist in the system
is applied to a new map feature, a new tag is introduced into
the tagging vocabulary. We call such an action “creating atag.” On the other hand, if an existing tag is applied, it ismerely re-used, i.e., a new connection is added between theexisting tag and the map feature to which it is applied. We
call such an action “applying a tag.” Naturally, when a tag iscreated, it is also applied to some map feature (e.g., a block),
resulting in a tag application. We counted the number of tag
applications (split into tag applications on blocks and points)
and the number of new tags added, per user and per trial.
Work done per user. LB subjects applied more tags on average (about 3 times) than FITD or control subjects. These
results were statistically significant. We performed statisticaltests (for p-value computations) on log(1 + x)-transformed
variables to account for the non-normality (long-tail nature)
6
The median length of a trial was 1.5 minute. We hypothesize thatthe unusually long trials represent cases where the subject forgot toclick the “I’m done” button, remembering only much later. Consequently, we could not idenfity, with reasonable confidence, the partsof the trial that were done as a response to the target request.

2919(a) Tags created per trial.

Group
Control
FITD
LB

Total
70
99
193

Mean
0.34
1.08
0.71

SD
1.08
2.43
2.54

(b) Tags applied per trial.

Group
Control
FITD
LB

Total
542
571
1702

Mean
2.66
6.23
6.25

SD
7.20
13.11
13.79

Table 4. Tagging work done per trial in response to the target request.

of the data and compensate for counts of zero. We first dida one-way analysis of variance (ANOVA) on the number oftag applications (F (2, 2854) = 2.78, p = .06), then did posthoc pairwise comparisons using Tukey’s HSD test (the difference between LB and control groups was marginally significant, p = .06). On an average, LB subjects also created nearly thrice as many tags as control subjects (ANOVA:F (2, 2854) = 2.70, p = .07, then Tukey’s HSD: LB vs. control: p = .08). Table 3 summarizes the number of tag applications and new tags added per user by subjects from thethree groups.
Work done per trial. We see evidence of the success of the
LB technique at the per-trial level too. The average LB trial
produced more than twice as many tags (6.25) as the averagecontrol trial (2.66). Table 4 summarizes these comparisons.
Looking back at Table 2, we see that the average FITD subject
did fewer trials than the average control subject. This explains
why there is a significant difference between the FITD andcontrol groups in terms of work done per trial, despite there
being none in terms of work done per user.
Summary of results. Our results suggest that the LB technique significantly increased the quantity of work subjects putin (hypothesis H2). The FITD technique, on the other hand,is not as successful – an average FITD trial produced morework than a control trial, but on an average, FITD subjects
did no more work than control subjects (0.57 ≈ 0.60) (hypothesis H1). There also was evidence that the LB technique
fared better than the FITD technique.

Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA

Discussion – Why these results?

We have just described an empirical investigation of the FITD
and LB techniques of compliance-without-pressure in thecontext of an online social production community, Cyclopath.
Why did we obtain the results we saw? What aspects of ourprocedure caused these results, and what aspects produced
opposing forces? Answering these questions is important forcrafting recommendations concerning the use of these techniques for designers of online communities. We now referback to relevant social psychological theories to make senseof our results.
Why did LB succeed?

The LB effect is theoretically simpler: it is generally explained by the theory of commitment. The seminal work on
the LB effect [8] attributed its success to the development ofcommitment to the task in the minds of the person as a consequence of the initial contact. Further research [6] has shownthat commitment to the requester, not the task, is actually responsible for the increased likelihood of compliance to thetarget request. In our case, either is possible: task commitment, since we explicitly asked LB subjects to agree to thetask of extracting a tag from a note, or requester committment, as Cyclopath is a community resource, and people tend
to care for the communities they are a part of.
Why did FITD meet with limited success?

There have been several attempts at explaining the FITD effect (or the lack of it) using a variety of psychological processes and theories [4]. Based on these theories, we speculate
on the following reasons behind our results.7
Self-perception not strong enough. The self-perception theory [1] is the most popular explanation for the success of the
FITD effect. The reasoning is that, when a person is induced
to comply with the smaller request, he/she infers from thisbehavior that he/she is the kind of person that does such tasks
and supports the cause behind the request; this self-perception
later causes him/her to comply with the larger request. However, if a weak FITD effect is observed (as our results indicate), then we can hypothesize that the inferential process of
self-perception triggered by the smaller request did not takeplace or was not strong enough.
Reactance as a result of excessive requesting. Psychological reactance may also undermine the FITD effect – the subject may simply feel badgered and pressured by the repeatedrequests and refuse the second, larger request. Our results
showed a significant difference in the work done per trial, but
no difference in the work done per user between the FITD
and control groups. This is because although the numberof subjects from the FITD group who responded to the target request is about the same as that from the control group,
the FITD group completed fewer trials than the control group(see Table 2). A possible hypothesis for this behavior is that
7
Burger’s review [6] of about 100 FITD studies clearly points outthat the degree to which each of the psychological processes known
to enhance/reduce the FITD effect operate depends on the specificprocedures used in the intervention. Hence, one must exercise caution while generalizing any speculations we make regarding how
strongly they operated in our case.

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some FITD subjects might have either felt badgered by therepeated requesting or felt that they have “already done theirpart” when they complied with the smaller request.
Reciprocity: Cyclopath did not return the favors asked.
Expectation of reciprocity may actually work against the processes driving the FITD effect. If the subject, after complying
with the smaller request, expects the requester to give something in return, then the fact that he/she instead comes backwith a larger request has the potential of inviting a refusal on
the part of the subject. On the other hand, had the subject
turned down the initial contact, then the norm of reciprocity
would drive him/her to comply with the target request even
if it is larger. Indeed, 21 subjects who did not respond to
our initial request did respond to the target request. Whether
reciprocity was the reason for this behavior is worthy of investigation.
Conformity to norms: Was the target request not to be
done? Another factor that might affect compliance is theknowledge of existing social norms. For example, if the subject learned that the norm is that the larger request is not complied with, then he/she also might refuse. However, in thisstudy, Cyclopath saw nearly 500 revisions to the map after
the target request was sent out: so, if any norm was present,
it was the norm of contributing.
Consistency needs. The cognitive dissonance theory [11]stipulates that people have a need to appear consistent and resolve any dissonances in their selves as soon as possible, even
if it means making irrational decisions. In the FITD context,
when a subject is presented with the larger request, he/she
behaves consistently with his/her prior behavior in a similar
context, i.e., the compliance to the initial smaller request. Although social psychologists have developed a scale to measure the preference for consistency [15], any conclusion we
draw here would be about the people who use Cyclopath, andnot the design of the system itself.
We conducted a follow-up study to investigate which of theseprocesses may have affected our results.
FOLLOW-UP STUDY
Research Questions

We designed a follow-up study to address the following research questions that we constructed from analyzing the results of our field study:
RQ-FITD. Why did the FITD technique meet with limited
success? Possible reasons include:• FITD subjects did not perceive themselves to be the type of
people who respond to requests from community sites like
Cyclopath (self-perception).
• FITD subjects did not feel motivated enough to comply
with the target request because they felt that they had already done their part when they responded to the initial
contact (reactance).
• FITD subjects felt that the repeating requesting behavior
from Cyclopath was badgering them (reactance).

Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA

study; e.g., the FITD group was presented with the scenario:
Imagine this: You receive an email from Cyclopath asking you
to do a task. The task is an easy one: you’re asked to read a
20-word note, and create a single meaningful tag for it (a 1-2
minute task). What would your response be? We took thisapproach (of asking people to imagine) instead of relying on
subjects’ memories of their experimental experience for two
reasons: First, the interval between the start of the experimentand the survey was about 4 months, and it was unlikely that
subjects would accurately remember their experiences oversuch a large interval. Second, this approach made it possible
for us to administer the survey even to those who had notparticipated in the experiment.
Note that for subjects who participatedin the field study, weassigned them a survey consistent with their experience in thefield study, i.e. FITD-relevant items be presented only to the
FITD group, and so on. Users who registered after the startof the experiment (and hence were not assigned to any group)
were randomly assigned to one of the three groups for the
purpose of the survey.
Subjects were asked to rate several statements on a 7-point
Likert scale (1-completely disagree to 7-completely agree)with regards to each scenario. Figure 3 lists some of the items.
Results and Discussion

We received 148 responses to our survey by April 20, 2011,a week after it was launched. Out of these, 43 (29%) of theusers were among those who had participated in the previously described field study, whereas 105 (71%) were new.
There were no statistically significant differences in the responses of these two sets of users. Table 5 presents the mostimportant results. Our survey results showed some conditionspecific patterns and some general population-wide patterns.

Figure 3. Follow-up survey items. Each experimental group was presented with a different set of scenarios and items. Subjects rated each
item (except the first of the general statements) on a 7-point Likert scale.

• FITD subjects who turned down the initial contact felt obligated to comply with the target request on the grounds ofreciprocity (reciprocity).
RQ-LB. Why did the LB technique succeed in eliciting more
contributions? Possible reasons include:• LB subjects complied with the target request because theyfelt a sense of commitment towards the task of extracting
tags from notes (task commitment).
• LB subjects complied with the target request because theyfelt a sense of commitment towards Cyclopath (requester
commitment).
MethodWe sent out a survey on April 13, 2011 to subjects from all
the groups. In the survey, subjects were asked to imagine
scenarios similar to the experimental procedure of our field

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We observed general ideological patterns across all groups:
respondents said they would do the requests because theycame from Cyclopath (M ≥ 5.13, 1.23 ≤ SD ≤ 1.38 in
all cases) and would not do so in general (M ≤ 3.13, 1.58 ≤SD ≤ 1.73 in all cases). Moreover, respondents from thecontrol group disagreed with the statement that the task requested of them (the target request) was too much of a favor(M = 2.64, SD = 1.15)! This shows users’ general commitment to the Cyclopath community and can be a powerfulmotivation to contribute whenever requested.
FITD. Respondents from the FITD condition agreed withthe statement that they would perform the task requested
in the initial contact because it was small and easy (M =5.42, SD = 1.54) – a verification of the FITD design. Further, we saw that FITD respondents agreed with the fact thatthey felt that they had done their part towards helping Cyclopath (M = 5.47, SD = 1.16) and that asking them to dosomething more after just a week had passed by was too often(M = 4.62, SD = 1.32). This is an indication that a likely
reason for the lower-than-expected contributions to the FITD
target request was that people felt that they were badgered.
The results also seem to indicate that this reason outweights
the self-perception effect: contributions from the FITD groupin the field study were lower despite FITD respondents in theSession: Crowdsourcing & Peer Production II

Group
FITD

FITD
FITD

LB

LB

Control

CHI 2012, May 5–10, 2012, Austin, Texas, USA

Survey Item
Initial contact: How would you respond?
I would do the task because it was requested by Cyclopath.
I would do the task because it is small and easy.
I would do the task regardless of who requested it.
Initial contact: How would you feel after you did it?
I have done my part towards helping Cyclopath.
I am the type of person who typically responds to requests from community sites.
Target request: How would you respond?
Asking me to do something else after only a week has gone by is too often.
I’m the type of person that helps Cyclopath whenever called upon.
Initial contact: How would you respond?
I would commit to such a request because it was requested by Cyclopath.
I would commit to such a request regardless of who requested it.
I would commit to such a request because it is small and easy.
Target request: How would you respond?
This is unfair, Cyclopath just increased the amount of work it asked me to do.
I’m a person of my word: I agreed to help, so I’ll do it now.
Target request: How would you respond?
I would do the task because it was requested by Cyclopath.
I would do the task regardless of who requested it.
It is too much of a favor to ask on the part of Cyclopath.

Mean (M )Std. Dev. (SD)

5.53
5.42
3.13

1.23
1.54
1.73

5.47
4.70

1.16
1.65

4.62
4.43

1.32
1.39

5.57
2.65
4.98

1.35
1.58
1.50

4.47
4.63

1.50
1.50

5.13
3.00
2.64

1.39
1.63
1.15

250

Table 5. Results of our follow-up survey.

150
100
50

Dec 2011

Sep 2011

Jun 2011

Mar 2011

Dec 2010

Sep 2010

0

LB. Respondents from the LB group verified the LB design
by agreeing to the statement that they would commit to therequest in the initial contact because it was small and easy
(M = 4.98, SD = 1.50). Further, they also agreed to thestatement that they would contribute to the target request because they were persons of their word (M = 4.98, SD =1.50); in other words, committed to doing the task requested.

Total revisions

We did not find any statistically significant evidence for reciprocity; however, one respondent said, “yeah if you help us
back, this ain’t a one-way street buddy” as a response to how
he/she would feel after responding to the initial contact.

Control
FITD
LB

200

survey agreeing that after doing the task requested during theinitial contact, they would feel like they are the type of people
that would respond to requests for help from community sites(M = 4.70, SD = 1.65).

IMPLICATIONS AND SUMMARY

We believe this work is useful to both researchers and practitioners designing interventions to increase community participation. The success of the LB technique showed that an intervention as subtle as requesting prior commitment produced
large, significant increases in participation. This low-costhigh-returns mechanism is potentially of great use to large
scale campaigns such as WikiProjects and crowd-sourcing
initiatives. However, care should be taken while applying theories from social psychology to online communities: there aresubtleties and points of caution that must be considered.
Compliance-without-pressure in the online world. Earlier
in the paper, we outlined how features such as anonymity andthe loose, detached nature of online communication (as opposed to the more involved face-to-face) motivated the needfor an empirical evaluation of the FITD and LB techniques.
Looking at our results in the light of these premises, we see

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Figure 4. One-shot Effect. Our intervention saw a burst of activity justafter the experimental emails were sent out (Dec, 2010), which dropped
off steeply soon after. Note that the activity of Cyclopath’s most prolificcontributor has been excluded from this figure.

that the LB technique succeeded due to a heightened feeling of commitment despite the relative anonymity associatedwith the online community. However, FITD only produced
limited success because it was very easy for subjects to simply close their browsers if they felt badgered by the repeatedrequesting. Thus, differences between online and offline interactions must be carefully considered before planning any
intervention using a compliance-without-pressure technique.
Short versus long-term effects. We have seen in the past thatinterventions that try to boost member participation succeed
in doing so only while they are active, and that participation

Session: Crowdsourcing & Peer Production II

CHI 2012, May 5–10, 2012, Austin, Texas, USA

drops to pre-intervention levels once it is withdrawn [29]. Our
FITD and LB interventions fell within the same category. We
saw a burst of activity (measured as number revisions saved)
immediately following the initial contact and the target request, which dropped off steeply soon after (Figure 4). The
self-perception effect, one of the explanations for the successof the FITD technique, is one of the most likely processes
that could have caused long-term effects, whereas psychological reactance would work against any. In our case, we did
not see any evidence for self-perception, which is consistent
with our understanding of why our work campaign produced
a one-shot effect.

how busy they are or how much effort is needed when they
make a commitment in the future [31]. LB studies that vary
the amount of time between the initial contact and the target
request are required to test this explanation.

While the failure to cause a long-term increase in participation levels is a limitation of the techniques we evaluated, we
believe that they have utility in one-shot interventions. Online social production communities do require one-shot burstsof member participation at times – e.g, if a WikiProject inWikipedia wishes to categorize several hundred articles intoa hierarchical structure, or if a geographic open content community like FixMyStreet8 needs to identify all potholes in a
locality as a part of a neighborhood campaign.

Summary. We described an evaluation of the compliancewithout-pressure techniques foot-in-the-door (FITD) andlow-ball (LB) in the context of an online social production
community, using a field experiment and a follow-up survey.
We found that despite the subtlety in its manipulation, the LB
technique elicited nearly 3 times more participation. However, while both techniques managed to produce an increasein contribution, this was short-lived. These findings are applicable to both researchers and designers who create interventions to boost participation in online communities. However,more research is needed to look into other techniques (likethe norm of reciprocity) that may yield lasting effects.

That said, research efforts should try to focus on producing long-term increases in participation. In other words, researchers must try to devise techniques that enable the community to support itself. One way of tackling this issue is toemploy the powerful and ubiqutous norm of reciprocity, anapproach we are currently exploring.
Member satisfaction and retention. From past research, weknow that although users can be manipulated into behaving ina particular manner, they tend to detect the manipulation andbecome less satisfied with the system [9]. This reduces thevalue of perhaps the greatest asset of an online community:
the trust and commitment of its members.
Similarly, in the context of our study, we must consider the
possible effects on member satisfaction of implementating
the type of compliance-without-pressure techniques we studied. Our users certainly felt that the repeated emailing wasexcessive (in case of FITD), and that increasing the cost of
the requested task was unfair (LB) (Table 5). From an online
community designer’s perspective, users might be viewed asworkers – in which case they can be manipulated to achieve
maximum throughput – or as community members – in whichcase they must be carefully preserved and nurtured. Recognizing the strengths of the community (e.g., existing levelsof user commitment) is critical: if apparently effective in the
short term, techniques like FITD and LB might do more longterm damage to users’ perceptions of and commitment to acommunity. After all, the tangible product of a group activity
is not the only outcome that matters; in the long run, users willcontinue to participate only if their needs are met [18, 24]. Finally, since there are so many online communities, users who
are not satisfied with one are likely to leave it in favor of analternative, more attractive one that serves the same purpose.
Limitations and future work. An alternative explanation
for the LB effect is the role of time: people tend to discount8

www.fixmystreet.com

2923

Our study used a simple survey to conduct the qualitative
follow-up to the field experiment. A limitation of post-hoc
surveys are that they are presented out-of-context. Although
we tried to mitigate this problem by making the survey asstandalone as possible, better qualititative information could
be collected if the survey was interwoven into the field experiment itself.

ACKNOWLEDGEMENTS

We thank the members of GroupLens Research, the Cyclopath team, the Cyclopath user community, and our reviewers. We also thank Dr. Reid Priedhorsky, Katie Panciera, Jason Weaver, Dr. Donald Ross Jr., Dev Oliver, and Ginny Simsfor providing valuable feedback and guidance on research andwriting. This work was supported in part by the National Science Foundation grant IIS 08-08692.
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