Notes on CSS WS 2015

I have participated computational social science winter symposium (#CSSWS15) at Cologne for the past three days.
It is organized by GESIS located in Cologne.
#CSSWS15 invites a lot of superstars to give great talks, half of the participants are with socialogy backgrounds.
I keep some notes here about #CSSWS15.

1) Professor Sune Lehmann’s work on mobility is impresive.
Nice visualization, clear motivation and solid methodology.
The idea of using a user’s cores to predict his location is quite similar to our work.
The difference is that the cores of a user is discovered through mobility profile in Lehmann’s work
while we find cores (communities) through community detection on social graph.

2) Professor Lehmann also presents that time itself can be a good indicator on community detection.
This means if we simply observe users’ behaviors at differnt timestamp and
construct a sub social network out of it, then the community is naturally discovered.
Users’ mobility behaviors are a strong evidence for this kind of task
but the location data from location-based social networks might be too sparse.
Only Lehmann’s dataset can support that kind of idea.
I mean a project which provides 1,000 smartphones for freshman of DTU really astonished me.
No data can be better than this in academia.

3) Sensor map from goodcitylife.org is by far the coolest data analysis project I have ever seen.
In fact this is the main reason I participate #CSSWS15.

The goodcitylife team starts by discussing how we understand food with 5 difference senses
and map it to how we think about the city we live in.
For “see”, they publish a work on the happiest route to the destination.
For “hear”, they will (?) publish a work on analyzing urban sound.
For “smell”, they publish a work on digitalize the urban smell map.
This one is really cool and it has never been touched by anyone before.
For “feel”, psycological map of a city is brilliant.

I guess they will publish at least one more work on how we “taste” the city.
It is very interesting to understand where restaurants are located
and how people feel about the food in each area.

The general idea of computational social science is to bring social good to people (in my opinion).
Many speakers have talked about how to use social media to fight againest mental illness, depression, etc.
Therefore, I believe that to be a good computational social scientist
or start a great computational social science project,
one has to be really motivated to help others with their brilliant minds and hard working.
I know this last sentence is weird, it is easier to express it in Mandarin:
伟大的计算社会学家要有情怀。

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