Check out the Great Minds Think Alike game for iPhone, iPad and iPod Touch. It is a word association game that lets users build semantic concept networks and explore similarity relations between people and media content. Starting from a single word, the player builds a chain of words by selecting semantically related terms. Get the game from the App Store!
NaN had a strong presence at Hypertext 2009 in Torino:
- Mark’s paper What’s in a session: tracking individual behavior on the web was nominated for the Best Paper Award.
- Heather presented the demo Incentives for social annotation about the prototype Firefox extension for GiveALink.org, and the tagging game. (Heather is also demoing at SIGIR’09 in Boston.)
- I presented the demo Sixearch.org 2.0 peer application for collaborative web search about the latest release of Sixearch.
- Ben presented his poster on A scalable, collaborative similarity measure for social annotation systems.
I gave four invited talks in Spain, Italy, and Switzerland this summer:
- June 18: Social similarity at Yahoo! Labs Barcelona (host: Ricardo Baeza-Yates) — this is where I got the idea of a foosball table in the lab…
- June 19: Dynamics of Online Popularity at the University of Barcelona’s Department of Fundamental Physics (host: Marian Boguna)
- June 25: Social similarity at DEI, Politecnico di Milano (host: Stefano Ceri)
- June 26: Modeling text generation at the Faculty of Informatics, University of Lugano (host: Fabio Crestani)
Thanks to my wonderful hosts and their groups for engaging discussions and delightful hospitality!
Research and Creativity Activity profiles research by CNetS faculty Filippo Menczer and Alessandro Vespignani and their groups in a special issue on networks. More…
I will be using Tuesday (3/24) as a practice talk for AIRWEB 2009. Hope everyone had a nice spring break!
Title: Social Spam Detection
The popularity of social bookmarking sites has made them prime targets for spammers. Many of these systems require an administrator’s time and energy to manually filter or remove spam. Here we discuss the motivations ofsocial spam, and present a study of automatic detection of spammers in a social tagging system. We identify and analyze six distinct features that address various properties of social spam, finding that each of these features provides for a helpful signal to discriminate spammers from legitimate users. These features are then used in various machine learning
algorithms for classification, achieving over 98% accuracy in detecting social spammers with 2% false positives. These promising results provide a new baseline for future efforts on social spam. We make our dataset publicly
available to the research community.
No, it’s not an Italian spin-off of the popular TV show. CSI Piemonte is organizing a meeting on Understanding Complexity: a Journey through Science to be held November 22-23 at the Lingotto Convention Center here in Torino. We will have demos and posters on 6S, GiveALink, and the egalitarian effect of search engines. I look forward in particular to seeing my good old friend Dario and my mentor, Domenico.