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\textbf{\small{WORKSHOP REPORT}
}\\\vspace{-0.5cm} \rule{17.5cm}{1pt}
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\vspace{1cm}\textbf{The Search and Social Media Workshop at SIGIR 2009}}


\author{Eugene Agichtein\\
       Emory University \\
       \emph{eugene@mathcs.emory.edu}
       \and
       Marti A. Hearst\\
       UC Berkeley \\
       \emph{hearst@ischool.berkeley.edu} \\
       \and
       Ian Soboroff \\
       NIST\\
       \emph{ian.soboroff@nist.gov}\\
       \date{}}

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%TODO: summary of sessions 4, 5
%Revise future


\section{Introduction}
\label{sec:introduction}


Social applications are the fastest growing segment of the web. They
establish new forums for content 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~\url{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 make the 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?

\section{Workshop 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 additional presenters were
invited to participate in panel discussions.

For two blocks of time, a focus topic was chosen and led off by a
keynote speaker.  Then other 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 combination of 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 (using the hash key \#SSM09) next to the main projector
screen. We report selected tweets in the corresponding sections, with the
full twitter stream also available\footnote{SSM 2009 Twitter archive
available at \url{http://twapperkeeper.com/ssm09/}}.
The workshop program, listing
the contributed and invited presentations,
is available on the workshop website\footnote{Available at \url{http://ir.mathcs.emory.edu/SSM2009/program.html}}.


\section{First Session: Online Communities and Recommender Systems}
\label{sec:session1}

Prof. Joseph Konstan of University of Minnesota led off the
workshop with a talk entitled ``Help Is Out There: Online Community,
Community Artifacts, And A New Way Of Harnessing Knowledge.''

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{\bf xamat} Joe Konstan: friends in SN are like our imaginary friends when\\
we were 8 y.o. : they would not lend you money or help you with a move\\\\
{\bf xamat} Joe Konstan: It's really easy to get people to do work for your\\
system... just ask them\\\\
{\bf xamat} Joe Konstan: setting goals helps getting people to contribute\\
(he asks for 1K tweets during the session)\\
{\bf xamat} Joe Konstan: Disagreement stirs contribution from users, rating\\
is fun! (wonder if this leads to \#gameswithapurpose)\\\\
{\bf xamat} Joe Konstan: paying people 30\$ was the best way to get good\\
quality answers (talking about Google Answers)\\\\
{\bf ian\_soboroff} Harper \& Konstan: QA quality study from CHI 2008:\\
http://bit.ly/hYju8 \#ssm09 (thx @eugeneAgichtein)\\\\
{\bf BrianDavison} Listening to Joe Konstan at \#ssm09, suggests that search\\
engines should classify QA questions as conversational vs informational\\\\
{\bf yardi} If Q\&A abt social support as well as info-seeking, should Q\&A\\
sites be organized by social similarity instead of topical similarity?\\\\
{\bf jelsas} are some answerers more likely to respond to\\
conversational vs. Informational q's?\\\\
{\bf xamat} Joe Konstan: if you ask for advice with a *short* question, you\\
are likely to get wrong answers (you need to add context!)\\\\
{\bf xamat} Joe Konstan: the time invested in the english Wikipedia=only the\\
amount of time Americans spend watching TV commercials on a weekend.\\\\
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\caption{Selected tweets during Joe Konstan's keynote presentation}
\label{fig:tweets1}
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The talk discussed studies that explore how online communities create
and organize information and how we can draw lessons on how social
psychology, economics, and other sciences of human behavior can be
harnessed to understand and then design effective online
communities. In particular, Konstan looked at cases where computation
and machine learning have the potential to improve the functioning of
such communities and how to derive insights into the future of
searching in social media. Some tweets made about this talk
are reported in Figure~\ref{fig:tweets1}.


After this talk, Konstan joined a panel discussion on the topic of
recommender systems with Manish Agrawal, Scott Golder, and David
Carmel.  Agrawal from UIUC spoke about crowdsourcing local newsletters
with a Facebook application, Golder of Cornell spoke
about preliminary work in analyzing social networks for finding
people, and David Carmel from IBM explained the SAND project for
content/people recommendation in large companies.
%\newpage



\section{Second Session: Collaborative Search}
\label{sec:session2}


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{\bf BrianDavison} Jaime Teevan giving tutorial of who/what/when/where/why\\
collaborative search\\\\
{\bf ian\_soboroff} popular collab search tasks: travel planning,\\
shopping, technical information/literature\\\\
{\bf jerepick} @ApolloGeek I agree; domains for collaborative search definitely\\
have more in common with non-web srch than with web-ish known-item srch\\\\
{\bf ApolloGeek} We have seen some benefits from collaboration for\\
recall-oriented search.\\\\
{\bf ApolloGeek} Search jamming is a wonderful metaphor.\\\\
{\bf ian\_soboroff} @xamat my view is indeed, search is secondary in SM, \\
but I wonder how much of that is we don't have tools or know the tasks yet\\\\
{\bf ApolloGeek} Search using social media to support collaboration\\
seems very interesting, but is it what we mean by ``searching social
media''\\
\hline
\end{tabular}
}
\vspace{-0.2cm}
\caption{Selected tweets during the session on collaborative search}
\label{fig:tweets2}
\end{wrapfigure}

The second session was on the relatively new topic of collaborative
search.   Collaborative search is a different angle on social media;
it is social in the sense that multiple people are searching together aided
by collaborative software tools.
The panelists were Jaime Teevan of Microsoft Research, Ivana Marenzi of
Hannover University, and Jeremy Pickens of FXPAL. The speakers then
answered questions from the audience as well as those submitted via Twitter.
The consensus was that some search tasks are inherently collaborative, and
new search interfaces and modalities are just starting to emerge to support such
tasks. Selected tweets posted during this panel are reported in Figure~\ref{fig:tweets2}.


\section{Second Keynote: Twitter Search}
\label{sec:keynote2}

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{\bf jeffd} is watching the twitter address at the SIGIR \#SIGIR09 SSM\\
workshop. I love the audience participation!\\\\
{\bf redlog} Blown away by @abdur's animated visualization of Super\\
Bowl. Fine-grained temporal data FTW!\\\\
{\bf redlog} Q: when trends cover the world, every subculture/community gets\\
washed out, right? How to prevent building hegemony into the system?\\\\
{\bf BrianDavison} @abdur: ``algorithms have very few ethics''\\\\
{\bf jteevan} Just to repeat myself, I think searching social media is\\
particularly cool bc yr SN can instantiate what you're seeking if not there.\\\\
{\bf xamat} @abdur giving all sorts of examples of location based\\
twitter search to identify trends\\\\
{\bf craig\_macdonald} research on twitter is of interest, but will not be\\
sufficiently attractive without available static data instead of the feed?\\\\
\hline
\end{tabular}
}
\vspace{-0.5cm}
\caption{Selected tweets during Abdur Chowdury's keynote presentation}
\label{fig:tweets3}
\end{wrapfigure}

Abdur Chowdury, head of search for Twitter, gave the second keynote,
dropping provocative questions for the audience to
consider.\footnote{The 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}
He focused the discussion in Twitter Trends, which try to capture
important topics that people around the worlds are discussing.  He
noted that hackers band together and try and game the system to
influence the trends.  He also discussed efforts to group trends by
geolocation and by category.  He also noted that one of the big uses
of Twitter is shared events, as evidenced by its use for the search
and social media workshop itself.
Selected tweets are summarized in Figure~\ref{fig:tweets3}.\\\\


\section{Concluding Sessions: Tags and Search in Social Media}
\label{sec:sessions45}
The last two sessions of the workshop considered user-generated {\em 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
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.
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{\bf Ian\_soboroff} who is the audience of a tag? Who is the audience of a hashtag?\\\\
{\bf HCIR\_GeneG} Hashtags in twitter make it easy to name topic \& save space in\\
140 char limit. Also makes for high recall!\\\\
{\bf Craig\_macdonald} Hashtags remind me of manually assigned indexing terms - \\
c.f. \#ssm09 or \#ssm2009 problem we experienced earlier.\\\\
{\bf HCIR\_GeneG} \@craig\_macdonald Nice thing about manual assignment of hash-\\
tags is that it's done by consensus \& seems to converge quickly.\\\\
{\bf BrianDavison} Marti Hearst: {\em ``how much is a tweet with a link like anchor text?''}\\
\hline
\end{tabular}
}
\vspace{-0.3cm}
\caption{Selected tweets during the concluding workshop sessions}
\label{fig:tweets45}
\end{wrapfigure}
After a short break, Seo continued the topic of expert finding as applied
to online forums. The next paper, by Ganjisaffar et al., examined exploiting user reviews to
improve search in wikipedia, followed by Seki who described automatically
identifying spam blogs (also known as ``splogs''). The last session was concluded by
Doug Oard, who asked which aspects of research on search in social media connect to other areas
of information retrieval and natural 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 the tweets during these sessions
is in Figure~\ref{fig:tweets45}.

%    * Jangwon Seo and W. Bruce Croft. Thread-based Expert Finding
%    * Yasser Ganjisaffar, Sara Javanmardi and Cristina Lopes. Using
%    * User Reviews to Improve Search in Wikipedia
%    * Shohei Sato, Mikito Yoshikawa, Kazuhiro Seki and Kuniaki
%    * Uehara. Splog Detection Exploiting Link Structure and Contents
%    * Based on Few Labeled Examples
%    * Doug Oard: wherefore search in social media research?




\section{The Future}

Although an important field, research is still sparse in this area.
The third workshop on Search and Social Media will be held in
conjunction with Third ACM International Conference on Web Search and
Data Mining (WSDM 2010) in New York City in February
2010\footnote{http://ir.mathcs.emory.edu/SSM2010/}.  The SIGIR
membership is urged to submit demos, posters, and position papers
to this workshop.

\subsubsection*{Acknowledgements}
The SSM workshop organizers thank the SIGIR 2009 organizers for hosting
this workshop, and the members of the SSM'09 program
committee for their work helping to make this workshop a success:
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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