network dynamics @ mcgill

2013.05.21 - Network Dynamics' principle investigator, Derek Ruths, hosted the 2013 Sunbelt Workshop on the analysis of twitter data.

Sunbelt is the premier academic venue for social network informatics work.

It's 35 attendees got a full day crash course in using the API, storing and filtering data, and performing sentiment analysis, latent attribute inference, and topic classification.

Course materials are freely available here.

2013.05.13 - Social media have changed the way news about notable events spreads. With funding from Public Safety Canada, we have initiated a project to to turn social media into a crisis response system.

Our research aims to create a social media powered tool to give disaster, military, and aid workers real-time situational awareness in the wake of catastrophic events.

2012.10.11 - To learn about the manuscript-submission process, we conducted a survey of 100,000+ manuscripts published in a range of journals in the life sciences to learn about the articles' submission histories.

Among other results, we found evidence that the peer-review process does work: papers that have gone through at least one round of rejection-resubmission receive more citations.

Read more in our paper entitled, Flows of Research Manuscripts Among Scientific Journals Reveal Hidden Submission Patterns, published in Science.

2012.09.13 - You may love or hate Apple, but their iPhone announcements are always fascinating, energetic events. We studied how people responded on Twitter to the unveiling of the 5th generation iPhone on September 12th.

We were surprised by the sheer volume of tweets and the prevalence of international tweets (given that the event happened in the United States).

For more on these and other unusual facts about the event, check out the Tweets on the iPhone 5 infographic we made.

2012.04.15 - We just received a four year SSHRC Insight Grant supporting research into inferring the demographic attributes of online populations.

Our work will focus on devising new methods for learning the distribution of features such as age, gender, and education in groups of Twitter users.

The goal of this work is to give social scientists, urban planners, and policy makers more accurate tools for characterizing the populations and communities they are trying to understand or serve.