I wasn’t really aware that computer science went into research directions like that. It seems either like classic social science (in this case communication studies) territory or like business economics territory.
What approach are you taking when looking at budding and failed social networks? Did you do a quantitative study or were you looking for patterns in a more qualitative fashion?
You're right, it's a bit outside the normal ambit of computer science. I'm interested in multidisciplinary questions; we do also have non computer scientists among the authors, for example Prof. Nissenbaum http://www.nyu.edu/projects/nissenbaum/
Overall, as you suggest, our analysis is a mixture of CS, economics and social science.
While on the face of it such a study is closer to social science than anything else, the maths and stats involved in studying connections between people, computers and other man-made nodes, and even the communication of materials & information around the natural world, have massive overlaps.
It is one of those areas where the same maths is applicable to seeming disconnected practical/physical areas, like how psychologists are starting to use the maths of quantum probability to model certain human behaviours (apparently it seems to much more accurately model the fuzziness of our thought processes than any "traditional" statistics methods).
The applicability of the same maths to seemingly disconnected areas is one of the things that convinces many that a "grand theory of everything" may one day be possible rather than there being disparate base laws at different scales and locations (or the third possibility of course: turtles all the way down).
Computer science _is_ a social science* -- especially when it comes to success and failure of a social network. You can't separate the software from the social and organizational context it's used in.
That's going to be a hard sell. I do research in programming languages now and I think you'd be hard pressed to argue that the fundamental nature of my work is a social science. Especially since the initiating paper included a proof of correctness...
Well, it's not _just_ a social science. There's still plenty of interesting work to do with 1's and 0's and proofs. But even in "hard CS" areas like programming languages, the social since aspects are pretty significant. What influences the success of new languages and evolutions of existing ones? Why haven't some obviously good featuers like pre- and post-conditions and invariants been better integrated by most mainstream languages? How to make functional programming accessible to a lot more people?
One dude putting a paper online arguing something doesn't make it true. CS is not a social science. At best, when you stretch definitions of 'within the field' enough, you can study things that are related to CS and have social implications, yes. That doesn't make CS a 'social science'.
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I wasn’t really aware that computer science went into research directions like that. It seems either like classic social science (in this case communication studies) territory or like business economics territory.
What approach are you taking when looking at budding and failed social networks? Did you do a quantitative study or were you looking for patterns in a more qualitative fashion?
It's a purely qualitative study.
You're right, it's a bit outside the normal ambit of computer science. I'm interested in multidisciplinary questions; we do also have non computer scientists among the authors, for example Prof. Nissenbaum http://www.nyu.edu/projects/nissenbaum/
Overall, as you suggest, our analysis is a mixture of CS, economics and social science.
While on the face of it such a study is closer to social science than anything else, the maths and stats involved in studying connections between people, computers and other man-made nodes, and even the communication of materials & information around the natural world, have massive overlaps.
It is one of those areas where the same maths is applicable to seeming disconnected practical/physical areas, like how psychologists are starting to use the maths of quantum probability to model certain human behaviours (apparently it seems to much more accurately model the fuzziness of our thought processes than any "traditional" statistics methods).
The applicability of the same maths to seemingly disconnected areas is one of the things that convinces many that a "grand theory of everything" may one day be possible rather than there being disparate base laws at different scales and locations (or the third possibility of course: turtles all the way down).
Computer science _is_ a social science* -- especially when it comes to success and failure of a social network. You can't separate the software from the social and organizational context it's used in.
* more at http://achangeiscoming.net/docs/cssocsci.html
That's going to be a hard sell. I do research in programming languages now and I think you'd be hard pressed to argue that the fundamental nature of my work is a social science. Especially since the initiating paper included a proof of correctness...
Well, it's not _just_ a social science. There's still plenty of interesting work to do with 1's and 0's and proofs. But even in "hard CS" areas like programming languages, the social since aspects are pretty significant. What influences the success of new languages and evolutions of existing ones? Why haven't some obviously good featuers like pre- and post-conditions and invariants been better integrated by most mainstream languages? How to make functional programming accessible to a lot more people?
One dude putting a paper online arguing something doesn't make it true. CS is not a social science. At best, when you stretch definitions of 'within the field' enough, you can study things that are related to CS and have social implications, yes. That doesn't make CS a 'social science'.