Manuel Gomez Rodriguez and Monica Rogati
In the 21st International Conference on Information and Knowledge Management (CIKM 2012)
Abstract
The online and oine worlds are converging. Location-based services, ubiquitous mobile devices and on-the-go social network accessibility are blurring the distinction between in-person activities and their virtual counterpart. An important e ect of this convergence is the rapid and powerful impact of oine events (meetings, conferences) on the evolution and temporal dynamics of the online connectivity between members of social and professional networks. However, these e ects have been largely unexplored.
We study these e ects by using data from LinkedIn, a popular business-related social networking site. We find that online events may induce connectivity changes in the online network – there is a dramatic increase in the number of connections between event attendees shortly after the date of the event. Building on these insights, we describe a non-supervised method that exploits connectivity changes temporally correlated to real world events to successfully infer more than 40% of speci c event attendees. Finally, we revisit the link prediction problem by including user contributed information about on line events to achieve higher link prediction performance.