ABSTRACT
This extended abstract presents a new spatial model for collaboratively recommending "compelling" comments in an online discussion forum that promote consensus among a diverse group of users. In this application our goal is to promote comments that are rated highly by dissimilar users, which in some sense is a dual to traditional recommender problems. We propose a model for weighting and aggregating comment ratings that gives greater influence to positive ratings from users who tend to disagree with the commenter, and we compare it with various alternate methods. The model has the added benefit of being resistant to manipulation by false ratings and sybil attacks.
We test the model on comments in Opinion Space, a new online discussion tool that allows users to visualize where they stand with respect to other users in terms of their opinions on a set of controversial propositions. Comments in the system are recommended visually, where more "compelling" comments are emphasized with larger sizes.
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Index Terms
- A spatial model for collaborative filtering of comments in an online discussion forum
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