Saturday started off with a fascinating keynote from Damon Centola on How Behavior Spreads. He talked about how weak and strong ties affect the spread of both simple and complex contagions. Despite our intuition that weak ties will be best for diffusion, Damon pointed out that this is in fact only the case when looking at simple contagions. More complex contagions require social reinforcement before people are willing to adopt them - meaning that stronger ties are better at facilitating the spread of these types of behaviors.
Next up was Aaron Clauset, discussing how Scale-Free Networks are Rare, followed by the final keynote of the morning from Marta C. Gonzalez about Modeling and Planning Urban Systems with Novel Data Sources.
The days breakout sessions featured short talks on a range of diverse topics, including Gender, Corporations, Collective Behavior, Personality, Social Movements and Music.
In the Personality session, Kazutoshi Sasahara's talk, You Are What You Eat: A Social Media Study of Personality Traits, discussed how food preference is an indicator of one’s identity and associated with health, environment and politics. Kazutoshi revealed that language used on Twitter, which is associated with food can be ‘Food Left’ and Food Right’. Those that are politically left leaning use language such as ‘slow food’, ‘organic farming’ and those that are politically right leaning use language such as ‘frozen foods’ ‘massive portions’ and ‘fried foods’.
In the Collective Behavior session, Joshua Becker discussed how groups can form accurate beliefs, coming to the conclusion that we can learn from the wisdom of the crowd if all of the members are somewhat equally influential.
The Future of Computational Social Science
David Lazer gave the final keynote of the day, discussing The Future(s) of Computational Social Science and reflecting on how far we have come since his seminal paper on the emergence of the field was published in Science in 2009.
He spoke about the differences between those coming to the field from a computer science and social science background and highlighted some of the potential pitfalls for each. For computer scientists, he talked about the need to apply social theory and, for social scientists, the need to become significantly more computational. He emphasized that we do not need to train social scientists to be computer scientists, but that we need to bridge the gap.
In terms of what's next, David highlighted two different potential futures: a fusion of the two disciplines vs two separate roads. He spoke about idea of building a full spectrum of competencies, taking social science research design and combining it with various computer science methods. To get there, he urged that we develop adequate training for both computer and social scientists at undergraduate level; that we develop an infrastructure that supports computational social science; and that we practice an ethos of social consequence.