Elicitation of preferences is a critical task in modern application of voting protocols such as group recommender systems. This paper introduces a Bayesian elicitation paradigm for social choice. The system maintains a probability distribution over the preferences (rankings) of the voters. At each step the system asks the question to one of the voters, and the distribution is conditioned on the response. We consider strategies to pick the next question based on value of information, conditional entropy, and a mix of these two notions. We develop this idea focusing on scoring rules and compare different elicitation strategies in the case of Borda rule.