Social search interfaces aim to improve information seeking through collaboration. Three studies evaluated FeedMe, SearchTogether, and Coagmento. FeedMe allowed one-click link sharing but raised privacy concerns without public knowledge triggers. SearchTogether supported large group collaboration but users wanted more real-time features. Coagmento effectively supported group awareness but received low marks for personal awareness. Overall, more research is needed on privacy protections within social search interfaces to fully realize their benefits while respecting user privacy.

1. Social Search Interfaces in Information Retrieval
Jennifer Kott
College of Information Science
and Technology, Drexel
University
Jmk376@drexel.edu
ABSTRACT Google and Microsoft have come out with two good collaboration
This paper examines social web search, collaborative interfaces interfaces which support social search. User studies from both of
tools and their role in seeking information. The literature these interfaces are reviewed in this paper. Study one looks at
referenced in this paper, is a combination of several studies on FeedMe, a plug in for Google. FeedMe is a behind the scenes way
user preference, habits and how users share information using of sharing content with friends by sharing links. [1]. FeedMe
collaborative interfaces. prompts users to share web links with friends and asks them their
opinion on what was shared. Another study tested the
Participates of the collaboration tool studies were chosen at SearchTogether a browser plug-in from Microsoft. [4].
random and paid for their responses. Feedback was given based SearchTogether is a real-time collaboration tool giving users the
on user experience and testing of software features. Collaboration opportunity to view fellow user’s searches and socialize with
software evaluated included: FeedMe, SearchTogether and them during the searching process.
Coagmento. Each study lasted a period of about two weeks. The
user habit models discussed includes: the Random Walk Model, The goal of each user study was to measure the products
Resource Recommendation Model, Tagging Model and Link effectiveness as a collaboration tool. Side benefits of each study
Sharing. were user suggestions on product enhancements which would
make collaboration easier. The first step to making improvements
To create better collaboration tools you need to evaluate the
on collaborative interfaces is to fully understand how social files
existing ones and identify where improvements can be made. In
sharing works. We do that by first examining user habits,
these studies, the users identified a few areas where tools could
preferences and users need to share information.
help with improving content sharing. For example, privacy
concerns were noted in the FeedMe study. Users made a 2. LITERATURE REVIEW
suggestion to help with the privacy issue. They requested that a Literature shows, user preferences play a key role in determining
public knowledge trigger be added to the software. What is how successful the social sharing will be. User preferences in the
unclear is what will happen if the public knowledge trigger fails. literature showed users shied away from the advanced search
Would the creators of the FeedMe tool be held liable? features in favor of smaller searches. It’s not clear why, but two
Creators of collaboration tools need to take things slow. theories point to anything from a lazy user to lack of knowledge
Additional studies need to be done comparing the benefits versus when searching. [4] The user tends to use multiple word queries to
legal implications of changing some of the collaboration tools. search for information or relays on others to find information for
Users may play a very important role in determining the them. On more advance searches users typical involve librarians.
collaboration tools of the future.
Identifying a user as lazy maybe a bit harsh, a more reasonable
Categories and Subject Descriptors explanation may point to the preparation of the user prior to
H5.2 . Information interfaces and presentation (e.g. HCI) engaging in the search. Users who take the time to plan, organize
and set goals prior to seeking information tend to have more
General Terms successful outcomes. [3] The figure below illustrates a three step
Design, Human Factors, Verification. process a user goes through when seeking information. We break
each step by; 1) purpose, 2) gathering of requirements and 3)
Keywords formulate representation. 68.7 % were self-motivated searches
Social link sharing, blogs, RSS, social search, navigational search, amd 31.3% were motivated by some type of external source. [3]
query, tagging, taxonomy, informational, user-centered, social
collaboration, personalization, data.
1. INTRODUCTION
The search for information has become more of a collaborative
effort. Methods of sharing information have evolved over the past
few years with WEB 2.0. Web users can not only submit content
but enhance it through personalization. A magnitude of
information is out on the internet for users to sift through, make
sense of, to find what is relevant. Studies into online behavior
show users will seek help from others when having difficulty Figure 1. Shows prepartion prior to seeking information. (Evans, 2009)
locating information online. A recommendation by another user
can aid in that search. Recently developed interfaces help to
support different types of searches.

2. 2.1 User Preferences by speeding up retrieval relevant content because it shorten the
User habits and preferences are only one aspect of understanding number of clicks needed to locate the content.
the user. Equally important is an understanding of what the user is This diagram shows how the random walk model works. Side (a)
searching for. The three types of searches discussed in the illustrates the synonym part of the model and side (b) illustrates
literature include navigational, transactional, and informational. the homographs using user preferences.
Literature suggests social search works best the informational type
search. [3]
In an information search, users are on a journey to seek out
relevant information. They do not follow a specific path to find
information and may not be familiar with the topic. This type of
behavior is known as forging. In forging for information users
start in one direction and may be led into another direction by a
simple click. In social search, users are influenced by their peers
often leading them different directions. Interfaces like CiteULike
and Del.icio.us help users gather the forged information. These
two systems are social tagging systems. Social tagging links the
user to a resource. Figure 2: Random walk model (Clements, 2009)
It’s important to note, a tagged resource does not mean
automatically equal a good resource. Users need to keep in mind,
a tag is a recommendation, and other factors may play into the 3.2 Resource-recommendation Model
reason why a resource was tagged. These factors may include
education and interests of tagger. When seeking information the The Resource-recommendation model examined the social
results need to be deemed relevant and creditable in order to be tagging behaviors and time and tagging behaviors of users. The
useful. study used tag and time behaviors to come up with ratings using a
dataset from CiteULike. The recommended resource model used
2.2 User Opinions tag-weight rating, time-weight rating and a tag time rating.
Research varies on the usefulness of tagged content but tagged Overlapping ratings combined to form a user similarity
content used in conjunction with user opinions carries more calculation. The output of the model is the recommended
weight. Rating systems built into interfaces allow users to rate the resource. The diagram below illustrates the framework of the
quality of the content. Content is put in to specific categories Resource-recommendation model.
based on each rating. Placing content into specific categories,
based on a rating given by a user, is still seen as subjective [2]
Content chosen based on a rating system is flawed, because the
rating is based on opinion rather that fact.
3. Tagging Models
A side benefit of social tagging and rating is building content.
LibraryThing keep track of books they have read, tag them and
rate them. Users can use the benefits of tag and rating to find
recommend reading on various subjects of interest. The study on
LibraryThing showed the parallel between number of tags and
number of web searches. [2] In LibraryThing, users tag content
for a variety of reasons. A tag can be used to describe content, a
location or a status. Tags are good for putting books in to specific
categories. Tagging is another way to help users find content.
3.1 Random Walk Model Figure 3. Framework: Resource recommendation Model (Zheng,
Vocabulary remains a hurdle in many tagging systems. Variations 2010)
in words, use of synonyms and homographs have a directly affect
on search results. Similar problems occur in plural forms of the
words. To overcome this hurdle, a studying using a method called
clustering. Clustering puts tags into groups, groups were 3.3. Link Sharing
determined by how closely they relate to each other. Link sharing is another form of sharing content. A survey [1]
The Random Walk Model looked at the outcomes of clustering conducted by 40 web users asked four basic questions on link
when synonyms were used. These clusters helped improve sharing: 1) What tools do you use to share content 2) How do you
outcomes. Shorter queries of four or less terms showed the best go about finding and reviewing new web content? 3) Which is the
results. strongest motivator when you share links? 4) Which is the biggest
concern you have when you share links?
To overcome the homograph hurdle evaluators used the same Findings of the survey show email as the number one method of
random walk model to pair up the query tag and the target user sharing content. Favorite ways of discovering new content were
preference. The matching of user preference to query tag worked, visiting favorite websites a few times a week and receiving URLs
via email from unknown recipients. What motivates a user to

3. share a link? Answer given most often, they thought the topic features in SearchTogether include thumbs up/down, peek and
might interest the other person. A respondent were uncertain on follow browsing and on-line chatting via a add/comment box. [5]
the links relevance to the other user but shared them anyway. A
main worry among users was the possibility of too much email The user study published by Morris & Horvitz, 2007b and
being forwarded to one person. evaluated by Wilson [5] highlighted four areas where users
wished to have better control over collaboration. In peeking and
User sharing habits showed a tendency to share link more following, users wanted to know who is peeking and who is
prevalent between friends over someone they did not know. The following them. Rights to see the same URL another user is
survey theorized this was because friends know the interests of currently viewing and being able to push pages to other users with
their friends the best. For example, if your friend liked to cook ease. Along with the flexibility, to edit and annotate any search
and you came across a recipe, you would be more likely to share summary pages.
the recipe with your friend over a stranger whose taste you are not
familiar with. 4.3 Coagmento
Coagmento a plug-in from Firefox helps remote workers
4. SOCIAL SEARCH communicate, search, share and organize information over the
Social search defined in the literature as social interactions with web. [6] There are several good collaboration tools inside of the
others [3] Interactions can be explicit or implicit, co-located or Cogmento plugin. Information collection tools help users create
remote, synchronous or asynchronous. (Evans, 2009) To get users annotations and save and remove webpages. To help with
engaged socially the collaboration software must be easy to use. collaboration a side panel is equipped with a chat window and a
The fact is, a user who needs to jump through hoops to share history of search engine queries, saved pages and snippets for
information won’t bother do it! In theory, a good collaboration users to exchange thoughts and ideas. [6]
tool gives user’s a variety of ways to communicate, share, search
and organize information. This study focused on awareness in CIS. It used 84 participates
from the University of North Carolina at Chapel Hill and
4.1 FeedMe measured three conditions; Contextual awareness, work space
To test this theory, a study conducted over a two week period of awareness and examined the workspace area provided for group
time followed 60 users of FeedMe. FeedMe prompts users to collaboration. Personal peripheral awareness measured how well
share web links with their friends and asks them to give feedback the interface supported user’s personal history including, saved
on content shared. The purpose of the study is to gain a better documents, snippets and queries. Group peripheral awareness
understanding of the user. What features do they like? What looked at the same thing as personal peripheral awareness but
features could be improved in the software? from a group level perspective.
A few key things were learned from the FeedMe study. Features A key outcome of the Coagmento awareness study showed the
users scored most favorable were the one-click thanks feature and design of the Coagmento interface supported group awareness for
the later instead of now feature. The one-click thanks feature is an synchronous collaboration the best. [6] The product received low
automated response to thank the person sending you the link. The marks in the area of personal awareness. Group users had no
later instead feature is a view into the receipts email box. If the problems keeping up on the status of projects. They had full
sender thinks the recipient already has too many links waiting to visibility into what each member of the project was working on at
be viewed, they can schedule the link to show up later. The later all times and were able to collaborate with them through multiple
instead feature scored favorable among users because it allowed phases of the project.
users to share information in a polite way as to not overwhelm the Reported as unfavorable under group awareness was the lack of
recipient. [1] real-time collaboration. Users suggested some type of shared
User privacy concerns were one alarming finding of the study. notepad workspace be added to help with the real-time
Users feed recommended topics into the system based system collaboration issues. [6] Coagmento was designed for
suggestions of each user’s interest. Sharing information collaboration in synchronous or asynchronous mode. To support
concerning a disease, could potentially tip off other users to a synchronous-remote collaboration some major changes would be
health issue. Suggestions on how to fix the privacy issue, called need made to Coagmento. Another suggestion s was some type of
for a trigger called public knowledge to be added to the interface. alert system when new information added from a fellow group
The public knowledge control would be set by the user. [1] Only member. An alert would be helpful in those situations when a user
the public knowledge topics deemed by each user would show up needed to pick up some critical information about a task or a
as their interests. Users would decide when a topic was safe to change in a project.
discuss and when. This approach sounds reasonable but it’s
unclear if users would really take the time to setup public
5. Research Gaps
knowledge triggers. Additional studies would need to be done in A look at the data from all three user group studies show gaps in
this area. some of the research. Privacy and users rights to privacy are
missing. We do not know if any of the interfaces tested do a good
4.2 SearchTogether job at protecting the user’s right to privacy. Are some interfaces
SearchTogether from Microsoft is effective for those who like to better than others when it comes to protecting the user’s privacy
scan for information or learn from information. It supports large or is the burden of protecting private information solely on the
group collaboration by using group queries histories and split shoulders of the user? This question remains unanswered. One
searching. SearchTogether is not a structured search tool. Instead user pointed to privacy concerns in the FeedMe study by
it’s for the user who is not sure what they are looking for. They suggesting the need for a public knowledge trigger. A public
could just be browsing for ideas or information. Collaborative knowledge trigger would aid in protecting privacy concerns of the
information sharer but only if the user the trigger. Automatic

4. privacy protection needs to be built in to all of the products for it the user to share information, it appears more work is needed in
to be useful. the area of protecting the user’s privacy. Until interfaces can
protect the user’s privacy the benefits of social search may only
Social searching does not mean users have a right to know all of be shared friends.
your private business. A check box in the interface can help
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