This Gephi plug-in implements the Link Communities algorithm proposed in the paper:
Yong-Yeol Ahn, James P. Bagrow & Sune Lehmann, Link communities reveal multiscale complexity in networks, Nature 466, 761–764 (05 August 2010)
The algorithm purpose is to reveal communities in undirected and unweigthed networks. It is an agglomerative method (like hierarchical clustering) that compares two links and, if similarity value is below a fixed threshold, puts those links into the same community. This method maintains communities overlap, because a node can belong to multiple links and so to different communities.
This plugin has been developed by Danilo Domenino and Massimiliano Vella, under the supervision of Prof. Giancarlo Ruffo
Great Minds Think Alike is a word association game for iOS® that lets you build semantic concept networks and explore similarity relations between people, tags, and media. Starting from a word, build a chain by entering or selecting related terms among suggested options. You earn points entering new words or exploring content from Flickr, YouTube, Last.fm, Twitter, the Web, or other social media. Words are geo-tagged and players are linked to their Facebook profiles so you can find similar people near you.
Great Minds Think Alike is an instance of a Games With A Purpose (GWAP), or crowdsourcing through play, that are a class of digital games designed in a way that players can help solve hard computational problems while having fun. So, we invite to help science by playing games. Advancing research has never been so easy, or fun!
Great Minds Think Alike can be downloaded from the Apple Store for free and it has been developed by Rossano Schifanella in collaboration with our friends at Indiana University (IU). For more information, visit the Great Minds website that IU is hosting.
MobHinter, a recommender system for mobile devices proposed originally in 2008 and recently developed as part of IS4.MOBI project. MobHinter is designed for spreading of information on a geographic proximity basis, and it allows for timely advertising and notification of context-aware events.
Current Android implementation of MobHinter makes use of PhoneGap, that is a HTML 5 based mobile framework that supports many different platforms.
We have a nice Prezi presentation of MobHinter (italian only, sorry!).
SocRec is a social-oriented recommender system developed for iPad that allows the aggregation, filtering, tagging and rating of content pulled from three popular social media (Flickr, YouTube, and LastFM). Social features have been included by means of Facebook API and OAuth identification. The user is allowed to tag and rate content to let a remote server learn something about his/her interests and tastes.
Likir is the infrastructure of a new structured Peer-to-Peer network (DHT) based on Kademlia that poses the user identity at the heart of its architectural design. The goal of Likir is to provide a simple, secure and general purpose framework to develop distributed identity-based applications and to make easier the integration between them. Likir has the potential to denote a real social network, in which each user interacts with others, through an extensible suite of custom applications, on the basis of the reciprocal knowledge of their identity.
DeHinter is a Peer-to-Peer (P2P) recommender system that exploits social filtering techniques in order to implement a fully decentralized resource sharing platform. The system provides to users a way to share, search and retrieve content in a scalable, flexible and efficient way. The spontaneous relationships between users that show similar interests shape highly connected thematic clusters that can be exploited to provide personalized advices. DeHinter’s goal is to reduce the impact of the information overload providing a decentralized, autonomous and efficient way to filter contents exploiting social-oriented phenomena. The P2P communication layer of DeHinter is based on the P2P Gnutella protocol, that is a fully distributed overlay network.
RD-PVR (Recommendation and Discovery for Personal Video Recorder) was a 15 months regional research project partially supported by the Torino Wireless Foundation, and commissioned by company InRete S.r.l.. The project aimed at creating an integrated recommendation system based on social networking and the so-called long tail of users, in the context of Personal Video Recorders and set top boxes enabling IPTV services. Social networking techniques of latest web-based services, have been exploited for pushing personalized programming to the end users, for social recommendation, and content control.
An old, but still adorable, computer-graphic short video clip with the goal of communicating, in an accessible way, some of the concepts behind computer technology. The video is still used in many introductory course of Computer Science at the University of Turin.