By Jamie McCorriston & Morgane Ciot Facebook offers an easily accessible API allowing data analysts or application developers obtain the public content of a user’s profile. While publicly viewable content offers an interesting dataset for social analytics, private messenger data contains a more raw version of a user’s online verbal footprint. Due to privacy constraints, […]
IntroductionPublic platforms like Twitter, Facebook, and Weibo have provided a way for individuals of many cultures to create content and interact with those from other cultures and those speaking other languages. Often, when individuals speak multiple languages, they engage in code switching, where they communicate using a mixture of both languages. Code switching is readily […]
If you happen to be one of millions of users afflicted with Reddit addiction who has managed to shake off their finger-cramping, eye-twitching obsession for long enough allow your pupils to re-adjust to the three-dimensional world, you may have realized Reddit’s potential as a multi-faceted resource. Reddit is a website where users post content that […]
Are you interested in capturing social trends over Twitter? So are we! To give you a head start, in this post, we’ll look at how Twitter handles its own data.Twitter uses the JSON format to store data and segregates it into meaningful fields. Attached to every tweet is the metadata, that is the information about […]
This past year, I’ve had the privilege of serving as Data Co-Chair for the ICWSM conference – a top venue for the publication of research into social media.I’m excited to announce that this year we’ve launched the ICWSM Data Sharing initiative. Starting this year and moving forward, authors of papers published at ICWSM are encouraged […]
For all the wonderful things we hear about how compute clusters enable the analysis of massive datasets, the sad truth is that few researchers can use them to analyze large network datasets. This is due both practical and theoretical issues.From a practical perspective, clusters are expensive, their administration requires non-trivial time and technical knowledge, and […]
The Network Dynamics Lab is run by Professor Derek Ruths and is part of the McGill University School of Computer Science. We consist of one professor, a band of graduate students, and a cohort of undergrads - but more importantly we're curious people who enjoy writing code, playing with UNIX, and seeing what social media can tell us about the human condition. In our research we seek to develop new ways of measuring and modeling large-scale human behavior including online social platforms, NYT bestsellers, human communities, political parties, and ancient civilizations.
For more about our work and activities, visit our PI's homepage.
Recent News and Posts
- Facebook Messenger Analytics – Part 1: Data Collection
- Code-switching in Twitter #wow #TrèsIntéressant
- Parsing Reddit – PRAW to the Rescue
- Anatomy of a Tweet
- ICWSM data sharing goes live!
- Conducting network analysis without a cluster
- Tweets pay tribute to the New iPad
- Workshop teaches street fighting with Python
- McGill CS ranks 23rd in the world
We're always looking for enthusiastic, talented undergraduates, graduate students, and post-docs.
Our work requires proficiency in UNIX, programming (python is preferred!), and data analysis. Most importantly, though, we want self-motivated, critical thinkers who would jump at the chance to spend the odd weekend trudging through gigabytes of data to find the answer they're in search of.
If this sounds like you, send Professor Ruths an email. In addition to the usual details, describe a really hard problem you solved and how you did it. Extra points if it involves social informatics.