Colliding Computer & Social Sciences at the VU
Source: Think Links
One of the things that I think is great about the VU (Vrije Universiteit Amsterdam) where I work is the promotion of interdisciplinary work through organizations like the Network Institute. Computer Science is often known for interacting with biology, physics, and economics but we are now seeing the application of computing to Social Science problems. This is great for CS because domains often introduce new fundamental CS problems.
To talk about the overlap and potential opportunities for greater Social Science and Computer Science collaboration at the VU, Iina Hellsten (from Organization Science) and I organized a half-day symposium on Tuesday, June 29, 2010. We had a great environment for the discussion in the Intertain Lab (a space for investigating new interactive environments).
We had 17 participants about half from the Social Sciences (covering organization science, communication science, to psychology) and half from Computer Science.
We started off with talks setting the scene from myself (on the CS side) and Peter Groenewegen and then moved to a series of shorter talks giving us a glimpse of the different focuses of some of the attendees. Even during these talks, there was clearly excitement about the possibilities for collaboration and there were several interesting conversations about the work itself.
The last part of the symposium was a session where we identified challenges and opportunities. We ran this as a post-it note session where each participant wrote two challenges and two opportunities on post it notes. (I got this idea from Katy Börner at her NSF Workshop on Mapping of Science and the Semantic Web. Thanks Katy!). Amazingly, these post-it notes always cluster together. Below is an image of the results of the session:
The group identified 8 different groupings of the 60 challenges and opportunities listed by the participants. They were:
- How do we bridge the vocabulary gap between social science and computer science?
- We have the opportunity to build new applications using insights from social science.
- Writing new proposals and fundraising.
- Knowing who in the other discipline is working on a particular subject and maintaining connections between the disciplines.
- Being able to answer new research questions.
- Having an opportunity to apply research results in the “real world”.
- Automating parts of social science analysis (think network extraction from data sets).
- Overcoming the differing research styles of the two disciplines especially in terms of publication cycles.
Below we list the actual text of the post-it notes grouped into the 8 areas.
The outcome of the symposium is that now that we’ve identified clusters of challenges and opportunities, we need to focus on concrete collaborations to address these areas. We will hold another session in September to discuss concrete actions.
Overall, this event showed me that at the VU, we have both the right structures but the right people to engage in this sort of interdisciplinary research.
Results of Post-it Note Session:
|post-it content||challenge or opportunity (c/o)||category|
|More user centered/friendly systems. Not only usability, but also privacy strong communication ties||o||no category|
|convience peers (e.g reviewers)||c||no category|
|learn to give data (LOD) the right intrepretation||o||no category|
|use the methodological rigor (of social science?) to scope your results||o||no category|
|exploring/studying area for “design” of techno-social systems||o||vocab|
|seduce social scentists to think technical and computer scientist to think social||c||vocab|
|mix technical(cs) and social theoris and modes to advance understanding||c||vocab|
|deal with some fuzziness of social science models||c||vocab|
|time consuming coordination or alternatively miscommunication||c||vocab|
|different mindsets conceptualizations||c||vocab|
|it is difficult to develop shared understanding of theory||c||vocab|
|it is difficult to find common levels of abstraction||c||vocab|
|integrate low level network analysis with higher level models from social sciences||c||vocab|
|different sorts of thinking in cs and social social science||c||vocab|
|combining conceptual work to “bridge” the gap||c||vocab|
|very different outlook on research||c||vocab|
|speaking/interacting using the “same” vocabulary||c||vocab|
|finding coomon language between computer & social sciences||c||vocab|
|talk similar language||c||vocab|
|new applications of technology||o||new apps|
|teaching each other concepts/methods||o||new apps|
|developing new technology bundles together (e.g. pda-based surveys)||o||new apps|
|processing huge bulks of data||o||new apps|
|socio-technical support for agile social networks in organizations||o||funds|
|cross-polinization & cross-fertilization for developing meaningful insights||o||funds|
|keeping the connections across exisiting projects||c||who’s who|
|knowing who is doing what||c||who’s who|
|give overview of who is doing what in this field at the VU (via webpage?)||o||who’s who|
|identify the true webscience problems in the convergence of cs & ss||o||answering new questions|
|find relevant problems that are now solvable because of ICT solutions||o||answering new questions|
|generating new ideas||o||answering new questions|
|seeing research problems from new perspectives||o||answering new questions|
|provide overview of available methods, etc.||o||answering new questions|
|if we work together we can integrate our knoweldge and get a better idea about the big picture||o||answering new questions|
|make technical & interpretive knowledge come together||o||answering new questions|
|designing studies that have a greate change of producing real insights||o||real results|
|understand the social web phenomena like wikipedia, facebook (motivation/quality)||o||real results|
|share (experience) tools for network vizualization & analysis||o||real results|
|linking concepts that wouldn’t have been associated earlier (underlying frames)||o||real results|
|applying the results of the detailed tracking of people||o||real results|
|ending up with a lot of manual work to compensate for technical errors||c||automated analysis|
|combining social networks and content networks||o||automated analysis|
|automating social and content analysis||o||automated analysis|
|losing valuable information that might be essential to understanding phenomena||c||automated analysis|
|automated analysis & interpretations of social phenomena||c||automated analysis|
|thinking that one side (your side) always does things “the right way”.||c||research styles|
|interests are divergent||c||research styles|
|research timeframes are divergent||c||research styles|
|cs need short-term “help” -> pulbication cycle||c||research styles|
|different scientific approaches and styles (e.g. publication)||c||research styles|