On Wikipedia, the largest online encyclopedia, editors who contribute to the same articles and exchange comments on articles’ talk pages work in collaborative manner engaging in communication about their work. Thus they can be considered as peers who are likely to influence each other. In this...

Peer influence through word-of-mouth (WOM) plays an important role in many information systems but identification of causal effects is challenging. We identify causal WOM effects in the empirical setting of game adoption in a social network for gamers by exploiting differences in individuals’...

On Wikipedia, the largest online encyclopedia, editors who contribute to the same articles and exchange comments on articles’ talk pages work in collaborative manner engaging in communication about their work. Thus they can be considered as peers who are likely to influence each other. In this...

For social networking platforms like Facebook, understanding the peer effects on it can be valuable to many applications, such as designing efficient advertisements with social endorsement. Therefore, we propose a statistical methodology that provides such understanding. These platforms contain...

We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where each individual has his own specific reference group. Interactions are thus structured through a social network. We assume that correlated unobservables are...