Recommendation systems usually try to “guess” a user’s preferences from the system’s view. We study another side of recommendation: active opinion-formation from the perspec- tive of the user. In real life, a user’s opinion evolves with time and refines when new evidence occurs. Then, how does an online user form his/her own opinion actively in large social networks? The problem has three challenges: the factor, the effect and the open environment. To address those challenges, we investigate: (1) what factors or channels a user will consid...
