Social Navigation: a scenario, a framework and an interface
Robert Spence
A SCENARIO
Many different scenarios can be classified as social
navigation. There is, for example, the ‘well-trodden path’ in
which the aggregation of many trajectories is exploited. I
focus here on one specific scenario: I assume that a person
(the ‘user’) wishes to seek help from a ‘provider’ – and
without unduly inconveniencing that person - in order to have
access to one or more footprint sets potentially relevant to a
topic or task of interest.
EXAMPLES
Three examples will illustrate the chosen scenario: (1) The
user needs to organise a large conference in London, never
having had that experience, and would welcome seeing the
relevant footprints of someone who has. Examination of the
provider’s footprints might, in fact, be more helpful than
talking to that person at length; (2) The user organises a
major Lecture every year, and every year intends to record the
actions involved but never does: here, it could be beneficial
for the user to examine their own footprints (user =
provider!); (3) I would like to quickly bring myself up to
speed on the subject of social navigation, and would value
knowing the footprints of a professional colleague whose
approach I respect.
To facilitate the efficient and rapid generation of a mental
model of potentially relevant pages it can be argued (see
below) that it helps to provide as rich a display as possible: in
other words, the user must be aware of as many nodes as
possible, and in as informative a manner as possible. Thus,
icons and/or miniatures and/or text related to the pages should
almost fill the display (Figure 1), but be sufficiently separated
for the user to see the context of the underlying graph.
Information extremely relevant to this first browsing of
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CRITIQUE
The use of footprints in this way can be challenged. What
advantage would accrue from these scenarios, for example,
over and above the use of a search engine? Typically, a more
focused identification of pages in which one has considerable
confidence. But what about the use of agents? Frequently,
and unfortunately, the effort spent in iteratively instructing an
agent would be far greater than that involved in examining
the relevant footprints of a respected provider. A cautionary
example is provided by the apparent simplicity of
optimisation algorithms which, to be at all effective, require
human domain expertise and human guidance via quite a
complex interface (Colgan et al, 1991).
FOOTPRINTS
I shall assume that a provider’s previous web (or other
information space) usage is characterised by a collection of
footprints, each being a linear directed graph in which each
node is identified with a web-site/-page and each link with a
transition. I assume that a subset of a provider’s footprints
are identified by some mechanism (e.g., as in document
visualisation) as being potentially relevant to one or a set of
keywords which the user employs to define their interest. I
shall ignore, here, the important issues of disclosure and
security and assume that the user has been afforded free
access to the footprints identified as potentially relevant.
BROWSING TO FORM A MENTAL MODEL
The user must – and preferably rapidly - examine available
footprints to form a mental model of the locations visited
and, if possible, quickly decide which pages or page outlinks
look promising.
Figure 1 A possible representation of footprints
available graphs can and should be encoded: node dwell-time
could be encoded by node colour, revisitation by node size
and bookmarking by pattern. The most effective encoding
will undoubtedly emerge with use and depend heavily upon
the skill of the visual designer.
NAVIGATION FRAMEWORK
Design to support browsing, as well as other aspects of
navigation, can usefully be discussed within a recently
presented framework for navigation (Spence, 1999).
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Figure 2 A Framework for Navigation
Following a broad definition of navigation as “cognitively
determined movement in information space based on browsed
information”, the framework (Figure 2) identifies four
activities within the navigation process: (a) browsing
(perhaps weighted), of externalised data (the footprints) in
order to register content which is then integrated to form an
internal (mental) model. Consideration of that model and any
available externalisation leads to an interpretation which,
again when combined with any available externalisation and
interaction, leads to the formulation of browsing strategy.
It is likely that traversal of the loop shown in Figure 2, and
defined as navigation, may be very rapid.
about browsing strategy following the initial view of the
externalisation (e.g., Figure 1) is a cognitive process
influenced by the user’s knowledge of available interaction
modes such as those described above, knowledge of which
can be enhanced, at least initially, by making those modes
explicit.
Experi me
nt 2
We have examined how externalisation can be designed to
facilitate browsing: we now attempt to place interpretation
and the formulation of future browsing strategy within the
framework and suggest suitable externalisations and
interaction mechanisms.
INTERPRETATION
Quite quickly, the user will interpret the footprint details,
partly by referring to their mental model and partly by
viewing the externalisation of the footprint data, as shown in
Figure 1. Such interpretation can be supported by the use of
node encoding and node images and text. Preferably, no
interaction – only visual inspection – will be required.
The interpretation may be that the footprints offer no value;
that a small subset of nodes are worthy of more detailed
examination; that one particular footprint appears promising;
or that the web page represented by a node is clearly worth
examining in full. The interpretation may be influenced by
the nature of the graph’s connectivity. An open question here
concerns the most effect manner in which ‘scent’ of desirable
nodes can be provided in a display such as that of Figure 1.
FORMULATION OF A BROWSING STRATEGY
A decision as to how to proceed will be influenced by
knowledge of available interaction modes. For example, if
thresholding is available, a decision may be made to retain in
the externalisation only those nodes characterised by having
been bookmarked, by those having long dwell-times and/or
by those that have been revisited often: interaction to
accomplish such thresholding and reduce display clutter is
easy to provide, and knowledge of its provision may
influence the user’s choice of subsequent browsing strategy.
It is likely that the user will be trying to form another mental
model (but linked to the first (Tversky, 1993)), so that
guidelines suited to the first display of footprints are still
relevant, notwithstanding the fact that it may be helpful to
keep node positions fixed so that the new mental model can
be correlated with the old.
Browsing to help form the new mental model can also be
supported by a number of techniques design to display
additional detail. They include the use of Rapid Serial Visual
Presentation (RSVP) applied to text labels in a ‘Times
Square’ mode; the facility to ‘burst’ a bubble (Boardman,
2000) representing a node in order to examine the nearestneighbour pages (Figure 3); the use of RSVP in ‘carousel
mode’ (de Bruijn & Spence, 2000) in which (Figure 4) icons
or miniatures representing nearest neighbour pages emerge
from a node and follow a roughly circular path before
returning to the same node; and application of the Hyperbolic
Browser mechanism (Lamping & Rao, 1994) to facilitate
smooth node-sequence exploration within a graph. A decision
Figure 3 Bursting a node bubble Figure 4 RSVP of a node
COMMENT
Footprints can carry additional value, such as time
information (i.e., when each node was visited and in what
sequence) and association with a task: for example, the
purchase of flowers (for speakers) might not readily be
associated with conference organisation. Explicit indication
of why a node was found valuable would be beneficial, as
would contextual information such as process work flow.
ACKNOWLEDGEMENT
This presentation has benefited considerably from discussions
with Rick Boardman.
FOOTNOTE
Using RSVP, many images can be assessed in a few seconds,
as when riffling the pages of a new book. Images can, for
example, be recognised within a carousel mode RSVP such
as Figure 4 when each image appears in each position for as
little as 30 milliseconds in an ‘Is it there?’ type of task.
REFERENCES
Boardman, R. (2000) Bubble trees: visualization of hierarchical information trees, student poster (in extended abstracts)
CHI 2000, The Hague, April 2000.
Spence, R. (1999) A Framework for Navigation, International
Journal of Human-Computer Studies, 51, 5, pp.919-945.
De Bruijn, O. and Spence, R. (2000) Rapid Serial Visual
Presentation: A space-time trade-off in information
presentation, submitted to AVI’2000.
Colgan, L., Spence, R. and Rankin, P.R. (1995) The Cockpit
Metaphor, Behaviour and Information Technology, 14, 4,
pp.251-263.
Tversky, B. (1993) Cognitive Maps, Cognitive Collages and
Spatial Mental Models, in ‘Spatial Information Theory – a
Theoretical Basis for GIS’, Springer Verlag, Lecture Notes in
Computer Science, pp.14-24.
Lamping , J. and Rao, R. (1994) Laying out and Visualising
Large trees using a Hyperbolic Space, ACM, Proc. UIST’94,
pp.13-14.