Gabor Szabo

Predicting the popularity of online content

Early patterns of Digg diggs and YouTube views reflect long-term user interest.

Trends in Social Media: Persistence and Decay

Social media generates a prodigious wealth of real-time content at an incessant rate. From all the content that people create and share, only a few topics manage to attract enough attention to rise to the top and become temporal trends which are displayed to users. The question of what factors cause the formation and persistence of trends is an important one that has not been answered yet. In this paper, we conduct an intensive study of trending topics on Twitter and provide a theoretical basis for the formation, persistence and decay of trends. We also demonstrate empirically how factors such as user activity and number of followers do not contribute strongly to trend creation and its propagation. In fact, we find that the resonance of the content with the users of the social network plays a major role in causing trends.

Friendlee: A Mobile Application for Your Social Life

We have designed and implemented Friendlee, a mobile social networking application for close relationships. Friendlee analyzes the user’s call and messaging activity to form an intimate network of the user’s closest social contacts while providing ambient awareness of the user’ social network in a compelling, yet non-intrusive manner.

Diversity of online community activities

Web sites where users create and rate content as well as form links display many long-tailed distributions. Using one such site, Essembly, we propose causal mechanisms to explain these behaviors. Unlike purely descriptive models, our mechanisms use only information available to each user. We find the long-tails arise from large diversity of user activity and qualities of the rated content. The models not only explain overall behavior but also allow estimating the qualities of users and content from their early history on the site.