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Promoting Serendipity Online:
Recommendations for Tool Design
Jacquelyn Burkell
Faculty of Information and Media
Studies
ICT Research Cluster
University of Western Ontario
Tel.: 1 (519) 661-2111 ext. 88506
jburkell@uwo.ca
Anabel Quan-Haase
Faculty of Information and Media
Studies
ICT Research Cluster
University of Western Ontario
Tel.: 1 (519) 661-2111 ext. 81405
aquan@uwo.ca
Victoria L. Rubin
Faculty of Information and Media
Studies
ICT Research Cluster
University of Western Ontario
Tel.: 1 (519) 661-2111 ext. 81405
vrubin@uwo.ca
ABSTRACT
Some researchers have suggested that opportunities for
serendipitous discovery of information may be limited in the
online environment as a result of technological facilitation of
information behavior. In response, they suggest building tools that
enhance opportunities for serendipity. Based on our model of
everyday serendipity, we offer design suggestions for tools that
could enhance various conceptual facets of everyday
serendipitous chance encounters.
Categories and Subject Descriptors
H.1.2 [Information Systems]: User/Machine Systems – human
factors, human information processing, software psychology;
H.3.3 [Information Storage and Retrieval]: Information Search
and Retrieval; H.5.2: [Information Systems]: Information
Interfaces and Presentation – User Interfaces; K.4 [Computers
and Society]
General Terms
Design, Human Factors.
Keywords
Serendipity, serendipitous discovery, opportunistic information
encountering, chance encounters; psychology of system design,
information behavior, information-seeking; conceptual model,
system development suggestions.
1. INTRODUCTION
Chance encounters with information, objects, or people that lead
to fortuitous outcomes are an integral part of everyday
information behaviour. Erdelez stresses that “[r]esearch-driven
and anecdotal evidence suggests that users often find interesting
and useful information without purposeful application of
information searching skills and strategies” [3, p. 1013]. She
labels this type of discovery ‘information encountering’ [3]; other
terms include “opportunistic discovery of information” and,
perhaps most commonly, “serendipitous discovery”. Some
researchers have expressed concern that opportunity for this type
of encounter may be reduced as a result of technological
facilitation of information behaviour [5]. In response to this
concern, work in information systems has proposed the
development of interfaces that support or enable serendipity [5,6].
In previous work [7], Rubin, Burkell, and Quan-Haase developed
a model identifying the facets involved in everyday chance
encounters. In the current paper, we explore the ways in which
information systems could be designed to support the various
facets of serendipity identified in the model.
2. FACETS OF SERENDIPITY
Based on a review of the literature [7], Rubin, Burkell, and Quan-
Haase, identified two necessary conditions for serendipity: (1) a
chance observation that is (2) instrumental in bringing about a
fortuitous outcome. In that same paper we used a grounded theory
approach to the analysis of naturally occurring accounts of
serendipitous encounters (defined by the two necessary conditions
mentioned above) in order to identify the facets of serendipity in
everyday life and to explore their inter-connections. Based on our
results, we developed a model of everyday serendipitous
encounters (see Figure 1).
Figure 1. The Conceptual Model of Serendipity Facets in
Everyday Chance Encounters [per 7].
In our model, we conceptualize ‘the find’ as the key to
understanding serendipity because it is the focus of the
serendipitous encounter. ‘The find’ is the information, object or
person that, when encountered unexpectedly, triggers or facilitates
the fortuitous outcome. Serendipity necessarily involves an
element of chance (or at least the perception thereof: Facet C),
since it occurs only when the encounter with the find is
unanticipated, either because the find is encountered in an
unexpected place or at an unexpected time, or because the very
existence of the find is unknown to the individual. In order to
result in a fortuitous outcome, the find must be noticed (Facet B)
or brought to consciousness. Finally, the meaning or significance
of the find is defined in relation to a prior problem, possibly (or
even necessarily) a problem that is, at the time of the encounter,
not ‘top of mind’ or the focus of activity. Thus, a prepared mind
(Facet A) is necessary for a serendipitous encounter, and in most
cases the relevant problem must be activated or brought to the
foreground before the significance of the find can become
evident.
3. DESIGNING FOR SERENDIPITY
Based on this model, what are the recommendations for the
design of tools to support serendipitous encounters? Our position
is that serendipity-enhancing tools should promote or support one
or more of the facets that are the preconditions for a serendipitous
encounter: Chance, Noticing, and Activation of the Prepared
Mind. We will present strategies to support these facets in the
context of a common online activity: searching.
Adding an element of chance to online searching is perhaps the
most obvious intervention to support serendipity. The
combination of deterministic computational algorithms for search
and relevance determination and utilization of social
recommender approaches for item and resource identification can
result in predictable search results [see 5]. One obvious approach
to supporting serendipity in the online context is to reduce the
predictability of these results by explicitly introducing a random
element into search strings (one search engine, BananaSlug, does
exactly this), perturbing the order in which search items are
returned, or using algorithms to extend and enhance search
strategies [see 2]. The goal of these strategies is to effectively
broaden the search space, promoting encounters with items that
might not, under existing algorithms, be identified.
Noticing is obviously critical to serendipitous encounters.
Although noticing can be influenced in a top-down fashion by
problem requirements [7], the primary influences on noticing are
perceptual in nature. Thus, for example, we are apt to notice
elements on the basis of perceptual characteristics: unique colour,
animation, brightness, etc. [4]. Serendipity-enhancing tools can
capitalize on this tendency of the visual system to orient to salient
items by giving potentially relevant items ‘interesting’ perceptual
characteristics (e.g., putting them in a slightly larger font in a
results display). This ‘low level’ approach to encouraging
noticing is potentially better than the ‘push’ notifications used by
some tools [2] because users are better able to ignore the
suggested items, particularly if they are focally engaged in an
alternative task.
Perhaps the most complex, yet potentially the most important,
way to support serendipity is to support the activation of the
prepared mind. Serendipitous encounters often involve a switch
of focus from a problem that is ‘top of mind’ to one that is, at the
time of the serendipitous encounter, still active but not the
immediate focus of cognitive activity. Tools that support this
facet of serendipity could assist searchers to maintain an active
‘problem list’, perhaps scanning encountered information and
alerting the user (using the noticing strategies identified above)
when something relevant to a background problem is
encountered. Prompting a switch of ‘problem set’ could be as
simple as allowing the user to associate each problem with a
specific colour, and presenting potentially relevant search results
in the appropriate coloured font. Tools that allow users to quickly
and easily annotate and associate search results could support the
activation of relevant problems by supporting the recording of
even fleeting associations, allowing users to return later for a
fuller exploration.
Everyday serendipitous encounters are experienced as ‘happy
accidents’, sometimes drawing the encounterer away from a focal
task, but never requiring that shift. In fact, interventions that
demand attention (even if the end result is positive) are likely to
be experienced as distractions [1], and tools that support
serendipitous encounters should ideally blend seamlessly into the
user’s online environment. This is perhaps the most critical aspect
of tools to support serendipity, and the one that may be most
difficult to achieve.
4. CONCLUSIONS
As we move toward larger integration of digital tools into
everyday information seeking, it is necessary to better understand
how these tools affect the chance encountering of information.
The current paper presents an approach to designing tools to
support various facets of serendipity.
5. REFERENCES
[1] André, P, schraefel, m.c., Teevan, J., and Dumais, S.T. 2009.
Discovery is never by chance: designing for (un)serendipity.
Proceedings of the 7th ACM Conference on Creativity and
Cognition (Berkeley, Cal, US, Oct 26-30, 2009), 305-314.
[2] Campos, J. and Dias de Figueiredo. 2001. Searching the
unsearchable: Inducing serendipitous insights. In
Proceedings Workshop Program at the Fourth International
Conference on Case-Based Reasoning – Technical Note
AIC-01-003. Washington, DC: Naval Research Laboratory,
Navy Center for Applied Research in Artificial Intelligence.
[3] Erdelez, S. 2004. Investigation of information encountering
in the controlled research environment. Information
Processing and Management, 40, 1013-1024.
[4] Folk, C.L., Remington, R., and Johnston, J.C. 1992.
Involuntary covert orienting is contingent on attentional
control settings. Journal of Experimental psychology:
Human Perception and Performance. 18, 1030-1044.
[5] Thom-Santelli, J. 2007. Mobile social software: Facilitating
serendipity or encouraging homogeneity? Pervasive
Computing, 6, 3, 46-51.
[6] Toms, E. and McCay-Peet, L. 2009. Chance encounters in
the digital library. Springer-Verlag, City.
[7] Rubin, V. L., Burkell, J. and Quan-Haase, A. 2011. Facets of
serendipity in everyday chance encounters: A grounded
theory approach to blog analysis. Information Research-an
International Electronic Journal, 16, 3, available online at
http://informationr.net/ir/16-3/paper488.html.