ic2s2 Thursday morning keynotes

Daniel Romero - Examining the Effects of Exogenous Shocks on Social Networks and Collaborative Crowds

We are looking at the dynamics of social networks. The dynamics of networks are becoming increasingly well understood, but the question here is what happens to a network when there is a big external shock to the system?

One example that they looked at came from a hedge fund, the data included full IM communication amongst about 182 people, about 22M items. They also have the trading history of the hedge fund.

In this system an external shock will be a big change in the market. How do those changes change the structure of the network?

What they found was signals coming from the network turn out to be more predictive of future trading behaviour than just looking at the shocks that are happening in the market.

He looks at the subgraph of the hedge fund related to people who talk about a specific stock.

When there is a big change in the price more people talk about it, the networks get bigger.

Those networks also become more clustered and ties become stronger. Those networks also become more inward looking.

They also looked at shocks in wikipedia, and censorship from China on Chinese Wikipedia. Large censorship activity started happening with editors getting blocked from the site. This really started to pick up in 2005. They looked at the fraction of edits that were contributed by blocked editors to get a sense of the impact of the shock on the system. They looked at a number of measures on the network, pre and post shock event.

Many articles have no blocked contributors, so they can use those articles almost as a null hypothesis set.

The higher the level of the shock, the lower the activity that happens on those articles.

The result on centralisation is interesting. You expect a larger change with more shock, but at high sock levels the change in centralisation actually starts to decrease again. They don’t know for sure why this might be the case, but they think it might be that those articles that attract a large number of contributes have a high level of inflow of new editors, which compensates for editors being blocked from the site (this intuitively makes a lot of sense, but it would be nice to think of a way to get to that result via another route).

Milena Tsvetkova - Social Science Research with Games and Gamification

There are 1.8B gamers online. 41% are female. The average age is 35years old.

You can do gamified experiments.

If you create a gamified experiment you can bring the marginal cost of participation per person close to zero.

You can do new kinds of experiments at much larger scale than before.

Gamification has been used in the natural science for tagging images, for protein folding, for quantum computing and some others.

In the 1980’s Axelrod asked people to contribute strategies for the prisoners dilemma.

David Lazer’s platform volunteer science has some gasification elements, but this platform does not allow for person to person interactions.

This researcher is looking at segregation and also on inequality.

Schelling’s work shows that even if people are tolerant, you can end up with segregation. Even when people actively seek diversity you can end up with segregation, so the conclusion is that public policies might be futile.

Tsvetkova’s research created four real-time multi-player games. They took these games to 20 high school’s in Sweden where they demonstrated the game. The goal was for players to get as many points as possible.

The gameplay takes about two minutes to play.

They key thing here is that they did not pay participants, they got participation because they provided a game environment.

Their findings on this data are interesting and don’t fully support the work of Schelling, but perhaps more interesting in this talk is that they got this data with participants trying to improve their “utility” without being paid, and the framework of this kind of system for getting insight is actually promising.

On the other hand gasification can introduce unintended consequences.

A new project is starting on the emergence of inequality. How does strong inequality emerge when we know that skills are distributed fairly, and people like to drive towards equality.

They want to try to study feedback loops, and what happens when certain characteristics are visible to others (such as wealth or reputation).

Their game design is going to be modelled on tamagotchi and FarmVille. In this case with an online game, unlike with high school students in the classroom, you now have to think about how to recruit and retain participants to the game. (In fact this now starts to look like a classic challenge of any internet startup). They are collaborating with ScienceAtHome for building out this new experiment.