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Expertise-finding systems may be useful in helping people find trustworthy collaborators
with knowledge of and interest in a particular topic. Expertise-finding systems are systems de-
signed to help users identify people with a particular type of knowledge within a specific organi-
expertise-finding system. Users register with Aardvark, tagging themselves with areas of expertise
and providing information about their social network. Users then post questions to Aardvark, which
are routed to members of their immediate or extended network based on the expertise information.
Collabio (
Bernstein et al.
,
2009
) is a tagging-based Facebook game designed to augment the social
network with metadata that can be used for expertise finding.
Because expertise is a common motivation for answering others' questions, accounting for
31.9% of all answers in the study by
Morris et al.
(
2010c
), connecting an individual with an infor-
mation need with an expert related to that need can sometimes be enough to get the individual's need
satisfied. However, a collaborative search/expertise-finding hybrid could augment experts' profiles
to include information about their information goals. This would allow people to identify experts
with shared goals to collaborate on search tasks.
Another common reported motivation for turning to others rather than searching alone was
that a particular topic was ill-suited for individual search using a search engine.
Morris et al.
(
2010c
)
found that 5.4% of people in their survey reported enlisting the help of their social network to find
something after trying to use a search engine on their own and obtaining no results or low-relevance
results. They also found that 15.2% of people believed that search engines were fundamentally
incapable of answering the categories of questions they were asking, such as questions relating to
breaking news or subjective opinions, and so turned to social tools to satisfy their information need
without ever attempting to find the information on their own.
In Chapter 3 (
What
), we discussed the common topics people search for collaboratively.
Search engines detecting that users are exploring these topics might identify such interactions as
opportunities to remind users of collaborative search features in order to create a more satisfying
experience. Some topics that are challenging to investigate with search engines might be particularly
ripe for a combination of search and social approaches, such as cases where information resources
may not be instantiated online (as in Jim's recommendation for a particular mold inspector).
Combining social information with traditional Web search can also potentially broaden a
searcher's initially (perhaps overly) narrow definition of the search topic; Indeed, combining mul-
tiple users' perspectives on how to approach a particular topic can be one of the benefits of col-
laborative searching, increasing users' coverage of the information space by combining their differ-
ent information-seeking strategies, and perhaps ultimately improving their individual search skills
through increased exposure to the approaches other users take to investigating a topic (
Morris, M.R.
,
2007
).
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