Archive for the ‘social networks’ Category

Pervasive Social Computing Seminar

Wednesday, October 29th, 2008

I gave a seminar yesterday in the Mobisys weekly seminars at UCL and I would be pleased to share my slides with you. It was about Pervasive Social Computing, or how to support social networks in pervasive computing environments in order to enable social interactivity between mobile users.

Any feedback is welcome and if you have any question I will pleased to answer.

Pervasive Social Computing

Mobisys Seminar 28/10/08

From: poline_sonia, 7 minutes ago

Mobisys Seminar 28/10/08

View SlideShare presentation or Upload your own. (tags: pervasive social)

SlideShare Link

Social network collaborative filtering

Monday, October 13th, 2008

Interestingly, “This paper demonstrates that “social network collaborative filtering” (SNCF), wherein user-selected like-minded alters are used to make predictions, can rival traditional user-to-user collaborative filtering (CF) in predictive accuracy. “

Informal Networks from Movements

Saturday, October 11th, 2008

I’m looking for  academics/practionaires interested in the following research  and for companies willing to give me access to relevant data ;-) My website. My email:

To facilitate the flow of information or to promote cultural change, companies often focus on formal organizational charts. Alas, those charts do not reveal the invisible networks that employees use to get things done. One way of identifying invisible networks is to keep track of how staff moves and, more specifically, “who talks to whom”. This can be done automatically by programming mobile phones to keep track of their owners’ location and proximity to other people.  By aggregating data on those phones, one  then produces “informal networks” and can harness them to:

  • Make change stick by identifying influential employees. If management can persuade influential people to be proponent of a big change, then the change is far more likely to succeed.
  • Focus on points in an informal network where relationships should be expanded or reduced. Imagine that, from its informal network, a company finds out that old personnel are extraordinary well-connected and central to collaboration, while many newcomers are stuck on the periphery. To fix the situation, the company may launch “mentoring programs” in which old personnel (central to collaboration) mentor newcomers. That is just one example of how the study of informal networks can break down barriers that hinder collaboration.
  • Measure the effectiveness of major initiatives. Informal networks are also a way for companies to measure the impact of changes. By measuring key network metrics (such as density, cohesion, and centrality) before and after a change, companies can asses whether the change has been a positive one. For example, if an informal network shows higher density after introducing a mentoring program, then the program has been a positive change in that it has reduced the number of steps for any individual to get in touch with a colleague.

KDD-08 video lectures

Tuesday, October 7th, 2008

KDD-08 videos include:


Creating Social Networks Will No Longer Be a Luxury

Thursday, October 2nd, 2008

In early August, the specialized publication Infoworld gave an award to Elgg, a platform for creating social networks, in the category of best open-source software for collaboration. At that time, hardly anyone other than specialists even knew what it was. That remains the case but things could change in the future. Specialized blogs have celebrated the recent release of version 1.0 of Elgg ( as evidence that open-source software is ready to have its voice be heard in the world of social network creation platforms. In short, Elgg provides a content-management solution that lets anyone create and manage their own social network. The fact that it uses the general public license means it can avoid the limitations of proprietary social networking sites, such as YouTube, Facebook and MySpace, for instance, which make their own rules for admission and content.


Analysis of Social Networks using Ucinet and Siena @ Ox

Thursday, October 2nd, 2008

A one-week workshop on Analysis of Social Networks using Ucinet and Siena, taught by Martin Everett and Tom Snijders, will be held in Oxford, December 15-19, 2008. Registration will be opened soon at the website of the Oxford Spring School. It will be possible to register independently for the Ucinet part (Monday-Tuesday, taught by Martin Everett) and for the Siena part (Wednesday-Friday, taught by Tom Snijders). The program is available at

Weaving a Web of Trust

Saturday, September 27th, 2008

Jennifer wrote a piece (which is well worth reading) in Science Magazine: “Increasingly, people are studying social and collaborative Web technologies for use in science. However, issues such as privacy, confidentiality, and trust arise around the use of these technologies. Science is crucially based on knowing provenance–who produced what, how and where–and on the Web, trusting scientific information is becoming more difficult for both scientists and the general public. User-generated content, even from professionals, can be opinionated (both informed and uninformed), inaccurate, and deceiving.” More.

Talks @ OII

Friday, September 12th, 2008

Two interesting upcoming events at the Oxfor Internet Institute:

  • 23 September: Tracking the Internet into the 21st Century (Tuesday , 11:00 – 12:00)
    by Vint Cerf! Chief Internet Evangelist for Google
  • 20 October: Making Sense of YouTube (Monday, 15:00 – 16:00)
    by Jean Burgess
    “This presentation reports on a recent study of YouTube that relied principally on a survey of 4300 of the most ‘popular’ videos… The analysis produced new knowledge about the extent of particular uses of the platform (such as vlogging, political commentary, or the ‘distribution’ of broadcast content); and the relationship between different modes of ‘audience’ engagement (commenting, responding, rating) and particular content genres. “

Semantic- Social Networks

Friday, September 5th, 2008

Here is a very interesting talk (Slides+Audio) by Story Henry a researcher at Sun Microsystems interested in the Semantic Web and Social Networks.

Henry gave this presentation at JavaOne 2008, and at the Internet Identity Workshop and the Data Sharing Summit in Mountain View this May.

The slides cover data portability between Social Networks, linked data, foaf (Friend Of A Friend project), security in distributed social networks, OpenId, they demo a real semantic Address Book written in Java, explain how it works,  SPARQL (a query language for the semantic Web), introduce one to rules, and give some ideas as to what a semantic desktop will look like…

You can view it here:



Dataset and R code for our paper on genres/artists affinity

Tuesday, August 19th, 2008

Justin Donaldson and I have a paper at ISMIR entitled “Uncovering affinity of artists to multiple genres from social behaviour data”. The paper details a project we worked on for the past year or so involving popular music listening activity from a pool of MusicStrands users.

We provide not only the paper, but also the dataset and the code used in our analysis. All of this is available at the website we have set up for the project:

The main contribution of the project is an analysis and illustration of genres as “fuzzy sets” rather than boolean labels. Through a co-occurence analysis of hundreds of thousands of user playlists, a frequency based “affinity” metric is formed between artists and genres. This affinity metric is a more detailed expression of the style of a given artist’s music. The idea and awareness of predominant genres are a trivial part of any person’s understanding of the vast corpus of popular music. However, genres typically are used as Boolean categorical labels. I.e. an artist is understood to be associated with only one given genre.

By expressing a connection to multiple genres through our affinity metric, a more detailed picture of the artist emerges. We give a lot more examples in the website, so be sure to check it out. -


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Are Social Networking Sites Useful for Business?

Thursday, August 14th, 2008

“To get the most out of social networking sites, small companies should look past the hype, set concrete business goals, then start experimenting”. From this morning’s BW.

The uses vary by application or site:

  • (for both networking and human resources) LinkedIn can be helpful in connecting with people you want to meet for one reason or another.
  • (for gaining exposure to larger audiences) Twitter and Facebook can be helpful when you’re trying to notify a group of people about something you want to promote or about a happening of some kind

Advertise to the Influencers

Friday, July 11th, 2008

Google has applied for a patent for a method that seeks to identify who the “influencers” in a social network are (see related blog post here). This is interesting- the idea of identifying structure and influence in graphs has been around for quite some time, but now there is a money-making application: serve targetted adds to the influencers. Will this affect how innovations are diffused throughout society? This also seems to reinforce a related post (assuming your influence is proportional to how much people trust you): “trust is not evenly distributed.”

Connected We Work – The power of informal networks

Thursday, July 3rd, 2008

This very interesting report is about how companies can harness networks of employees to improve collaboration.


The ladder of fame: Few tyrants at the top

Thursday, July 3rd, 2008

To write down a decent research statement (one showing a “vision”), I turned into a McKinsey research analyst these days – I’m reading far more McKinsey Quarterly reports than academic papers, and they aren’t that bad! ;-) In a report that dates back to Aug 07, the authors surveyed 573 users of 4 leading video-sharing websites in Germany and found out:


Social Systems

Monday, June 30th, 2008

This month’s Data Engineering Bulletin is about Recommendation and Search in Social Systems. It sports thoughts on robustness and user experience.