SocialCom 2011

here are few papers presented at socialcom (our two papers on personality and language are summarized here)

Funf: Open Android Sensing Framework. One tutorial at socialcom was dedicated to Funf. This is an open source set of functionalities running on phones and servers that enable the collection (sensing), uploading, and configuration of a wide range of data types (location, movement, usage, social proximity). This framework has been built by a professional developer within Sandy Pentland's group (thanks to a Google grant), and has just been made publicly available on the android market (well done!) (download link ). The conference featured a considerable number of papers that made use of the framework. A case in point is [1]. This paper is about predicting "who installs which (mobile) app" based on one's social network (here the term network refers to a composite graph made of different types of phone-sensed networks). It turns out that one has more common apps with familiar strangers than with friends (i'm not 100% sure though, you need to check the paper). A cute bit of the framework is its fun dashboard - this allows researchers to run studies in which personal data is shown to the participants and consequential changes of behaviour can be automatically traced. The ubicomp paper [2] highlights the vision behind the framework.
[1] Composite Social Network for Predicting Mobile Apps Installation
[2] the social fMRI: Measuring, Understanding and Designing Social Mechanism in the Real World. Ubicomp 11.

Another "special" session was dedicated to cyber-bullying - an extremely interesting topic in need of research (pdf overview). Folks at the media lab built an initial model to spot cyber-bullying from conversation in social media. Interestingly, they trained the model using the data from this site. The paper will soon be published and will be titled "Commonsense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying"

Predicting Reciprocity in Social Networks. This paper studied the factors that are associated with the probability that a node w reciprocates and links to a node v in a social network. The most important factor is the difference in status between the two nodes v and w: status(v)/status(w), where status(v)=in_degree(v)/out_degree(v).
The larger that fraction, the more likely w will reciprocates the link. That is because a large denominator and small numerator indicate that v has many in-links and few out-links and that w has many out-links and few in-links. This suggests that v has higher "status" than w will be more likely to reciprocate.

Link Prediction in Social Networks using Computationally Efficient Topological Features. Using katz measure, these researchers effectively predicted social ties in a variety of networks. This isn't a very novel work, yet it's interesting that Katz measure performed best.

The new director of the media lab, Joi Ito, gave a interesting keynote on "Open Standards and Open Networks". He recounted his involvement in a post-disaster radiation monitoring effort in Japan. During his talk, I also learned that the a large number of governments are realising their data (not pictures or videos, but data) under creative common licence.

Fortune Monitor or Fortune Teller: Understanding the Connection between Interaction Patterns and Financial Status. This paper studied the relationship between interactions monitored using mobile phones and financial status. Apparently people with high income don't talk longer but their meeting patterns (mobility) tend to be more diverse than those of people on low income. They also studied people's personality traits and found that people high in
1) Agreeableness tend to have more friends and interact with diverse users (as per face-to-face interactions monitored with bluetooth)
2) Happiness [i hope they measured satisfaction with life] tend to be more diverse contact (it would be cool to double check the measure of diversity used here)

The workshop NetMob was running in parallel and featured a lot of interesting talks that used mobile phone data to answer very interesting societal questions. The full program is in pdf. Salvo fully attended it, so he might be able to tell you more about it ;)

Comments (0) Trackbacks (0)

No comments yet.

Leave a comment

No trackbacks yet.