As Computer Supported Collaborative Learning (CSCL) becomes increasingly adopted as an alternative to classic educational scenarios, we face an increasing need for automatic tools designed to support tutors in the time consuming process of analyzing conversations and interactions among students. Therefore, building upon a cohesion-based model of the discourse, we have validated ReaderBench, a system capable of evaluating collaboration based on a social knowledge-building perspective. Through the intertwining of different participants' points of view, collaboration emerges and this process is reflected in the identified cohesive links between different speakers. Overall, the current experiments indicate that textual cohesion successfully detects collaboration between participants as ideas are shared and exchanged within an ongoing conversation.