Reddit is a social news aggregation and discussion website. Users submit content to the site such as links to news, which are then voted up or down by other members who in turn, can comment on others’ posts to continue the conversation. In this work, we are interested in modeling how users interact with each other in Reddit debates, to discover the most dominant opinions in a debate. To this end, we introduce a user-based model for analysis of Reddit debates. In this model, comments by users are grouped per user, describing their opinion in relation to the root comment of the debate, and users are represented with a single node in a weighted graph, where node’s weights represent relevance of user’s opinions and edges represent agreement or disagreement relationships between users throughout the debate. In this model, agreement or disagreement between the opinions of two users is defined by aggregating the set of single interactions that have occurred between them during the debate. In this work we present a skeptical aggregation model for this task. For measuring the relevance of user’s opinions, we consider two models: one based on the score of all the user’s comments and other based on the user’s karma, as computed by the Reddit platform. We characterize the set of most dominant opinions with an argumentative-based model, using the information of disagreement between opinions and relevance of opinions.