Social Information Processing in Social News Aggregation

The rise of social media sites — blogs, wikis, and Digg — underscores the transformation of the Web to a participatory medium in which users are collaboratively creating, evaluating and distributing information. The innovations introduced by social media have lead to a new paradigm for interacting with information: social information processing. We study how the social news aggregator Digg exploits social information processing to solve the problems of document recommendation and rating. First, we show that social networks play an important role in document recommendation. The second contribution of this paper consists of a mathematical model that describes how collaborative evaluation of documents emerges from the independent decisions made by many users. The model takes into account users behavior: e.g., whether they are reading stories on the front page or through a Friends interface. Solutions of the model reproduce the observed ratings received by actual stories on Digg.

• Type: Journal
• Year: 2007
• Where: CORR
• Authors: Kristina Lerman
• Keywords: CORR 2007, Education, Social, Social Media, Social Media Sites