WORKSHOP REPORTThe Search and Social Media Workshop at
SIGIR 2009
Eugene Agichtein
Emory University
eugene@mathcs.emory.edu

Marti A. Hearst
UC Berkeley
hearst@ischool.berkeley.edu

Ian Soboroff
NISTian.soboroff@nist.gov

1Introduction

Social applications are the fastest growing segment of the web. They establish new forums forcontent creation, allow people to connect to each other and share information, and permit novel
applications at the intersection of people and information. However, to date, social media has been
primarily popular for connecting people, not for finding information. While there has been progress
on searching particular kinds of social media, such as blogs, search in others (e.g., Facebook,Myspace, of flickr) are not as well understood.
To address these questions, the second workshop on Search and Social Media (SSM 2009)
was held at SIGIR 2009 in Boston, MA in July 2009. The main workshop website is available
at http://ir.mathcs.emory.edu/SSM2009/. SSM 2009 followed on the highly successful SSM
2008 workshop held at CIKM 2008 in Napa, CA. As in the previous year, the workshop had nearly
50 attendees from academia and industry.
The purpose of this workshop was to bring together information retrieval and social media
researchers to consider the following questions: How should we search in social media? What are
the needs of users, and models of those needs, specific to social media search? What models makethe most sense? How does search interact with existing uses of social media? How can social
media search complement traditional web search? What new search paradigms for information
finding can be facilitated by social media?

2Workshop Format

Search in social media is still a new field, so submissions were solicited in the form of late-breaking
and novel research results, and position and vision papers discussing the role of search in social
media. Eight contributed papers were accepted for presentation and a number of additionalpresenters were invited to participate in panel discussions.

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For two blocks of time, a focus topic was chosen and led off by a keynote speaker. Thenother speakers made brief presentations, and then they all joined a discussion panel including
participation from the audience. The other two sessions were panels consisting of a combinationof submitted presentations and invited speakers. The workshop organizers attempted to bring
the feel of social media to the workshop by projecting the results of a live Twitter feed (usingthe hash key #SSM09) next to the main projector screen. We report selected tweets in thecorresponding sections, with the full twitter stream also available1 . The workshop program, listing
the contributed and invited presentations, is available on the workshop website2 .

3First Session: Online Communities and RecommenderSystemsProf. Joseph Konstan of University of Minnesota led off the workshop with a talk entitled “HelpIs Out There: Online Community, Community Artifacts, And A New Way Of Harnessing Knowledge.”
Joe Konstan: friends in SN are like our imaginary friends when
The talk discussed studies that explore xamat
we were 8 y.o. : they would not lend you money or help you with a move
how online communities create and organize xamat Joe Konstan: It’s really easy to get people to do work for yourinformation and how we can draw lessons on system... just ask themJoe Konstan: setting goals helps getting people to contributehow social psychology, economics, and other xamat(he asks for 1K tweets during the session)
Joe Konstan: Disagreement stirs contribution from users, rating
sciences of human behavior can be harnessed xamat
is fun! (wonder if this leads to #gameswithapurpose)
to understand and then design effective online xamat Joe Konstan: paying people 30$ was the best way to get goodcommunities. In particular, Konstan looked at quality answers (talking about Google Answers)
soboroff Harper & Konstan: QA quality study from CHI 2008:
cases where computation and machine learn- ian
http://bit.ly/hYju8 #ssm09 (thx @eugeneAgichtein)ing have the potential to improve the func- BrianDavison Listening to Joe Konstan at #ssm09, suggests that searchengines should classify QA questions as conversational vs informationaltioning of such communities and how to deriveyardi If Q&A abt social support as well as info-seeking, should Q&A
insights into the future of searching in social sites be organized by social similarity instead of topical similarity?
media. Some tweets made about this talk are jelsas are some answerers more likely to respond toconversational vs. Informational q’s?
reported in Figure 1.
xamat Joe Konstan: if you ask for advice with a *short* question, you
After this talk, Konstan joined a panel are likely to get wrong answers (you need to add context!)
Joe Konstan: the time invested in the english Wikipedia=only thediscussion on the topic of recommender sys- xamat
amount of time Americans spend watching TV commercials on a weekend.
tems with Manish Agrawal, Scott Golder, andDavid Carmel. Agrawal from UIUC spoke Figure 1: Selected tweets during Joe Konstan’s
about crowdsourcing local newsletters with a keynote presentation
Facebook application, Golder of Cornell spoke
about preliminary work in analyzing socialnetworks for finding people, and David Carmel from IBM explained the SAND project for content/people recommendation in large companies.

4

Second Session: Collaborative Search
1
2SSM 2009 Twitter archive available at http://twapperkeeper.com/ssm09/
Available at http://ir.mathcs.emory.edu/SSM2009/program.html

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Jaime Teevan giving tutorial of who/what/when/where/whyThe second session was on the relatively new BrianDavison
collaborative search
topic of collaborative search. Collaborative ian soboroff popular collab search tasks: travel planning,search is a different angle on social media; it shopping, technical information/literature@ApolloGeek I agree; domains for collaborative search definitely
is social in the sense that multiple people are jerepick
have more in common with non-web srch than with web-ish known-item srch
searching together aided by collaborative soft- ApolloGeek We have seen some benefits from collaboration forware tools. The panelists were Jaime Teevan recall-oriented search.
of Microsoft Research, Ivana Marenzi of Han- ApolloGeek Search jamming is a wonderful metaphor.
soboroff @xamat my view is indeed, search is secondary in SM,
nover University, and Jeremy Pickens of FX- ian
but I wonder how much of that is we don’t have tools or know the tasks yetPAL. The speakers then answered questions ApolloGeek Search using social media to support collaboration
seems very interesting, but is it what we mean by “searching social media”
from the audience as well as those submitted
via Twitter. The consensus was that some Figure 2: Selected tweets during the session onsearch tasks are inherently collaborative, and collaborative search
new search interfaces and modalities are juststarting to emerge to support such tasks. Selected tweets posted during this panel are reported
in Figure 2.

5Second Keynote: Twitter Searchis watching the twitter address at the SIGIR #SIGIR09 SSM
Abdur Chowdury, head of search for Twitter, jeffd
workshop. I love the audience participation!
gave the second keynote, dropping provocative redlog Blown away by @abdur’s animated visualization of Super
questions for the audience to consider.3 He fo- Bowl. Fine-grained temporal data FTW!
Q: when trends cover the world, every subculture/community gets
cused the discussion in Twitter Trends, which redlog
washed out, right? How to prevent building hegemony into the system?
try to capture important topics that people BrianDavison @abdur: “algorithms have very few ethics”
around the worlds are discussing. He noted jteevan Just to repeat myself, I think searching social media isthat hackers band together and try and game particularly cool bc yr SN can instantiate what you’re seeking if not there.
@abdur giving all sorts of examples of location based
the system to influence the trends. He also dis- xamat
twitter search to identify trends
cussed efforts to group trends by geolocation craig macdonald research on twitter is of interest, but will not be
sufficiently attractive without available static data instead of the feed?
and by category. He also noted that one of
the big uses of Twitter is shared events, as ev- Figure 3: Selected tweets during Abdur Chowidenced by its use for the search and social me- dury’s keynote presentation
dia workshop itself. Selected tweets are summarized in Figure 3.

6Concluding Sessions: Tags and Search in Social MediaThe last two sessions of the workshop considered user-generated tags, a key characteristic of social
media, and how tags and other features of social media can be exploited for search. The first presentation of paper by Harvey et al. described using tag clouds for content indexing. Joshi described
3The summary of this talk was aided by a blog post at Jeff Dalton’s Search Engine Caffe blog,
http://www.searchenginecaffe.com/2009/07/sigir-social-media-workshop-abdur.html

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using community information to improve image search. Heymann analyzed tags to determine potential usefulness for search, and Yeung discussed identifying expertise in collaborative tagging systems.
After a short break, Seo continued the topic Ian soboroff who is the audience of a tag? Who is the audience of a hashtag?
GeneG Hashtags in twitter make it easy to name topic & save space inof expert finding as applied to online forums. HCIR
140 char limit. Also makes for high recall!
The next paper, by Ganjisaffar et al., ex- Craig macdonald Hashtags remind me of manually assigned indexing terms amined exploiting user reviews to improve c.f. #ssm09 or #ssm2009 problem we experienced earlier.
GeneG craig macdonald Nice thing about manual assignment of hashsearch in wikipedia, followed by Seki who de- HCIR
tags is that it’s done by consensus & seems to converge quickly.
scribed automatically identifying spam blogs BrianDavison Marti Hearst: “how much is a tweet with a link like anchor text?”(also known as “splogs”). The last session was
Figure 4: Selected tweets during the concluding
concluded by Doug Oard, who asked which asworkshop sessions
pects of research on search in social media connect to other areas of information retrieval andnatural language processing, and challenged the workshop attendees to consider the definitions
and boundaries of social media. This panel naturally transformed into an open discussion about
research in social media and key research directions to pursue in the future. Summary of thetweets during these sessions is in Figure 4.

7

The Future

Although an important field, research is still sparse in this area. The third workshop on Search andSocial Media will be held in conjunction with Third ACM International Conference on Web Searchand Data Mining (WSDM 2010) in New York City in February 20104 . The SIGIR membership isurged to submit demos, posters, and position papers to this workshop.
Acknowledgements
The SSM workshop organizers thank the SIGIR 2009 organizers for hosting this workshop, andthe members of the SSM’09 program committee for their work helping to make this workshop asuccess: Eytan Adar Ed Chi, Abdur Chowdhury, Natalie Glance, Bernardo Huberman, Matthew
Hurst, Pranam Kolari, Craig Macdonald, Gilad Mishne, Nitya Narasimhan, Nicolas Nicolov, Doug
Oard, Iadh Ounis, Maarten de Rijke, Markus Strohmaier, and Andrew Tomkins,

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http://ir.mathcs.emory.edu/SSM2010/

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