CIR paper at SIGIR 2014 conference

I’m very happy to report that our paper on Collaborative Information Retrieval (CIR) is accepted for the ACM SIGIR 2014 conference, to be held in July in Gold Coast, Australia.

Here’s the full citation:
Soulier, L., Shah, C., & Tamine, L. (2014). User-Driven System-Mediated Collaborative Information Retrieval. Proceedings of ACM SIGIR 2014 Conference. Gold Coast, Australia: July 6-10, 2014.

And here’s the abstract:
Most of the previous approaches surrounding collaborative information retrieval (CIR) provide either a user-based mediation, in which the system only supports users’ collaborative activities, or a system-based mediation, in which the system plays an active part in balancing user roles, re-ranking results, and distributing them to optimize overall retrieval performance. In this paper, we propose to combine both of these approaches by a role mining methodology that learns from users’ actions about the retrieval strategy they adapt. This hybrid method aims at showing how users are different and how to use these differences for suggesting roles. The core of the method is expressed as an algorithm that (1) monitors users’ actions in a CIR setting; (2) discovers differences among the collaborators along certain dimensions; and (3) suggests appropriate roles to make the most out of individual skills and optimize IR performance. Our approach is empirically evaluated and relies on two different laboratory studies involving 70 pairs of users. Our experiments show promising results that highlight how role mining could optimize the collaboration within a search session. The contributions of this work include a new algorithm for mining user roles in collaborative IR, an evaluation methodology, and a new approach to improve IR performance with the operationalization of user-driven system-mediated collaboration.

Introduction to CIS video

Proponents of collaborative information seeking discuss why supporting people’s innate behavior and the need for working together while seeking and using information are important to software engineering. Featured speakers include Chirag Shah, Rob Capra, Madhu Reddy, Meredith Ringel Morris, Roberto González-Ibáñez, and Michael B. Twidale. From IEEE Computer‘s March 2014 issue.

Coagmento in research uses

Coagmento has been used in various research projects, even those that do not call for collaboration. Why? Because Coagmento offers one of the most basic and powerful thing for lab-based studies – log data collection as long as the participants are doing something within their browsers.

We keep seeing examples of such usage from around the world. The most recent one was caught at the CSCW 2014 conference in Baltimore. It was  presented by Ryan Kelly of University of Bath in a paper titled Collaborative Web Search in Context: A Study of Tool Use in Everyday Tasks.

Want to use Coagmento for your research studies? It’s available as an open-source tool from Coagmento website, or you can opt for Coagmento Collaboratory if you’re a bit tech-savvy and want a greater flexibility.


Coagmento Collaboratory

We are happy to announce the availability of Coagmento Collaboratory – an open-source toolkit for constructing user studies with individual or collaborative users.

Coagmento Collaboratory is a version of Coagmento designed to be:

  • Modularized: Coagmento Collaboratory splits up functionality into separate classes which are easier to understand and maintain
  • Extendable: We provide stateless web-services so you can develop your own tools on top of our framework.
  • Documented: Coagmento Collaboratory is well documented through GitHub.

The framework contains the following:

  • Core classes which provide the foundation for Coagmento Collaboratory giving APIs for accessing user data (Bookmarks, Snippets, etc.) and research studies (Projects, Stages)
  • Web-services for accessing the core classes through HTTP requests
  • The Firefox plugin which uses the web-services as an example of practical usage of Coagmento Collaboratory

Find more information and download links from Note that we are still continuing to do more development and welcome contributions from others interested in this project. Comments and feedback always welcome!

Roberto’s dissertation

PhD Dissertation by Roberto I. González-Ibáñez: “A Study of Positive and Negative Affective States in Collaborative Information Seeking” (Defended in Sept. 2013 at Rutgers University; Supervised by Chirag Shah)

Emotions and other affective processes have long been considered essential elements in people’s lives. Whether during intimacy or in social contexts, human beings experience a wide spectrum of emotions every day, all the time. Despite emotion research conducted in various domains, little is known about the role of affects, emotions, feelings, and mood in the information search process, especially when this is carried out by teams. In this regard, this dissertation aimed to understand whether the affective dimension plays a role in collaborative information seeking (CIS) through four research objectives: (1) study how initial affective conditions influence information practices; (2) investigate what affective processes are typically expressed and experienced in information search; (3) examine how initial affective conditions and those derived from social interactions during the collaboration process influence team performance; and (4) study positivity ratio in collaborative search and their relation to team performance. To accomplish these research objectives, a controlled lab study with 135 participants distributed in fixed experimental conditions and a control group was conducted. In each experimental condition, participants were individually treated with affective stimuli in order to elicit positive and negative affective states.

Results from this study suggest that initial affective states may define and/or shape information processing strategies. Additionally, in collaborative settings, it was found that the interplay of similar or different affective processes could change the way searchers interact with each other, their frustration levels, affective load, and the quality of their work. This dissertation and the findings presented have theoretical implications in the study of collaborative and individual information seeking. Specifically, it gives the affective dimension a central role that could define the way people search, evaluate, and make sense of information. In terms of practical implications, if affective processes play such a key role in information seeking, this may redefine the design of information system by incorporating the ability to identify searchers’ initial affective states and provide the necessary resources to support their information processing strategies. Finally, this dissertation also contributes with a research framework and a methodological approach to carry out experimental evaluations to investigate the role of the affective dimension in both collaborative and individual information seeking.


What is Coagmento?

Coagmento is not just about collaboration or search or collaborative search, not anymore. It’s a Latin word that means “connect”. Yes, in the beginning (circa 2007-2010) it did stand for people connecting/collaborating, specifically for searching.

But now, and lately, Coagmento, meaning connect, has been seen and used more generally. Connect, in this new context, means connecting people to information in more meaningful way than known before; connecting useful sources and suggestions to information seekers; and of course, connecting people through and around information.

How do we do this? Or what do we need to do this? Well, that’s what the Coagmento project is about. We have started the work and have some initial thoughts, systems, and results. For instance, Coagmento toolbar for Firefox and Chrome allow a web user to keep track of their browsing, searching, and collaborators. The CSpace available through the Coagmento website offers three innovative interfaces to the user for navigating through information: timeline, cover flow, and 3D.

So what next? We are working in new algorithms that could identify potential collaborators for an information seeking task. And another algorithm that can extract meaningful roles that people can play while working in collaboration. We are also working on a new framework that allows us to understand user strategy for their underlying information seeking process.

Watch out is space for these and more outcomes coming out soon. Stay connected!

Tim Cook’s views on collaboration

Jay Yarrow from BI’s transcription for Tim Cook’s 2013 commencement speech at Duke:


What qualities do you look for in terms of what you think will produce effective collaboration?And what’s your role as CEO in fostering that kind of collaboration?

You look for people that are not political. People that are not bureaucrats. People that can privately celebrate the achievement, but not care if their name that is in the one in the lights. There are greater reasons to do things.

You look for wicked smart people. You look for people who appreciate different points of view. People who care enough that they have an idea at 11 at night and they want to call and talk to you about it. Because they’re so excited about it, they want to push the idea further. And that they believe that somebody can help them push the idea another step instead of them doing everything themselves.

I’ve never met anyone in my life, maybe they exist, that could do something so incredible by themselves in companies with global footprints. In our world, in Apple’s world, the reason Apple is special is we focus on hardware, software, and services. And the magic happens where those three come together.

And so, it’s unlikely that somebody that’s focused on one of those in and of itself can come up with magic and so you want people collaborating in such a way so you can produce these things that can’t be produced otherwise. And you want people to believe in that.

CIS book preface

We live in a society where information is, without a doubt, a powerful force. This statement may sound like a cliche, but it always amazes me how often we forget. May be that’s the purpose (or should be) of the technology that surrounds such information. The other aspect of information technology that amazes me is the fact that it is so new, considering human history. The clock that tells us the precise time of the day dates back only to the sixteenth century. The base 10 numbering system is only 500 years old, and mechanical devices used to calculate and present information have existed for only a couple of centuries. Of course, today when we say “information technology”, we are probably thinking about computers and other digital devices, and they are merely a few decades old.

What intrigues me the most is how we have been able to integrate such new concepts and technologies with long-standing human behavior. Take for example, working in groups and living as a society. This behavior has proven to be extremely important for the survival and prosperity of our species. Back in the days of hunting together to today’s office work, mankind has understood the need to work and thrive together. It is this behavior – the one of collaborating with each other – that has made it possible to achieve great feats in the history. How else can one man (or woman) build the pyramids or crack the human genetics code.

Of course, not all problems call for people working together. While Einstein had help and drew inspirations from others, he did come up with many significant findings himself. Leonardo de Vinci and Picasso, similarly, worked alone. Claude Shannon, considered to be the father of digital information age, was known to have worked in solitude behind closed doors. But let’s put geniuses aside and talk about the remaining 99.99% of us (which of course, still includes a lot of smart people!). We do, often need to work in collaboration. I’m sure even Einstein needed help placing his furniture in his Princeton house; he was a genius, not a superhuman!

This book is about those times when people work in collaboration – an eternal human behavior, in the light of new and innovative technologies in the information age that we live in. More precisely, it is concerned about situations pertaining to information retrieval/seeking/sense-making where people are collaborating or should be collaborating.

One may ask – Why this book? Why now? There is a simple two-fold answer to both these questions. Using technology to understand and support collaborative behavior has been around for a while – what is known as Computer-Supported Cooperative Work (CSCW), but it is in the recent years that we have seen more specialized attention given to applying CSCW methods and frameworks for information seeking situations. On the other hand, the field of Information Retrieval (IR, or broadly speaking IS, information seeking) has found (or re-realized) the importance of considering social and collaborative aspects of search, synthesis, and information use.

This has led to a newly developed interest in the field that is still emerging at the intersection of several other well-established fields, including CSCW, IR, HCI, and social media/networking. This book as an attempt to introduce the relatively young domain of collaborative information seeking (CIS) research by discussing how it came to be, what it currently offers, and where it is headed next. The best part is that we all get to define and contribute to this future.

Personally, my journey on this path started during the summer of 2007 when I was an intern at FXPAL, working with Gene Golovchinsky and Jeremy Pickens. Back then, we worked on something called Collaborative Exploratory Search (CES), and argued that IR systems need to have “smart” components that could mediate collaborative activities and produce results that are “better” than any individual IR process. And we succeeded with at least one kind of situation (time-limited, recall-oriented task with two people collaborating under assumed roles). We did continue this work further by identifying more situations and defining other roles, but as I returned to UNC and continued working on my dissertation, I started moving in the direction of user-mediated collaboration. My dissertation provided a framework (among other things) for studying and supporting user-focused CIS. I have continued working on various aspects of CIS (both user and system sides) as a faculty at Rutgers University. In the meantime, I have also participated in a number of professional events around CIS, including half a dozen workshops – two of which I co-organized.

This book is a culmination of all of these experiences, and while they have made me biased on the topic, I have tried my best to incorporate others’ views as well. In the end, my hope is that those working in this domain, and the larger field of IR see this book as a record of modern day CIS research that has tried to incorporate many view-points and contributions to inform those looking for a comprehensive treatment of this topic, along with wonderful opportunities (and challenges) it presents.

Social search

Recently there has been a lot of talk about social search. Just last week I attended Microsoft Faculty Summit in Seattle, and one of the sessions was dedicated to social search. The panelists talked about social Q&A using Yahoo! Answers and Facebook status messages. It occurred to me during that session that all of the talks were really about social information seeking/retrieval, and not about social search. I raised this question after the panel presentations and Merrie Morris immediately agreed that everything that she was talking about social search was indeed technically social information seeking!

I kept thinking about what really is social search. Fortunately, the next day was the Social Media Day that allowed me to have more focused discussions with more specialized experts in the field. During the “birds of feather” lunch, I was at the social search table and through our discussions, it became clear to me that there are two ways of thinking about social search: a search done on social objects, or search done in a social network.

What is a social object? Two ways of defining it: (1) an information object that has social attributes such as name, age, gender, location, and (2) an information object created through a social construction, such as a Wikipedia article.

How is search done in a social network? It’s usually done by broadcasting information need to one’s social network. Think of people posting questions as their Facebook status updates.

Often social search is defined as a method of searching that takes into account connections among people in addition to connections among information objects. The above explanation/understanding of social search does hold with this definition.

Tutorial on CIS at SIGIR 2012 conference

I’m really looking forward to engaging this year’s SIGIR attendees in a half-day tutorial on the subject of collaborative information seeking (CIS)! Following is the summary of the tutorial. Hope to see you in Portland for this (and SIGIR, of course)!

The course will introduce the student to theories, methodologies, and tools that focus on information retrieval/seeking in collaboration. The student will have an opportunity to learn about the social aspect of IR with a focus on collaborative information retrieval and seeking (CIR and CIS) situations, systems, and evaluation techniques.

The assumption of information seekers being independent and IR problem being individual has been challenged often in the recent past, with an argument that the next big leap in search and retrieval will come through incorporating social and collaborative aspects of information seeking. This course will introduce such works to the students, with an emphasis on understanding models and systems that support collaborative search or browsing. To put CIS in perspective, the course will show the students how various related concepts, such as collaborative information behavior (CIB), co-browsing, co-search, collaborative filtering, can be placed on the dimensions of human-system and explicitness-implicitness along with CIR and CIS for exploration and developmental needs, as well as evaluation purposes. Specifically, the course will (1) outline the research and latest developments in the field of collaborative IR, (2) list the challenges for designing and evaluating collaborative IR systems, and (3) show how traditional single user IR models and systems could be mapped to those for CIS. This will be achieved through introduction to appropriate literature, algorithms and interfaces that facilitate CIS, and methodologies for studying and evaluating them. Thus, the course will offer a balance between theoretical and practical elements of CIS.

The course is intended for those interested in social and collaborative aspects of IR (from both academia and industry), and requires only a general understanding of IR systems and evaluation.