We hypothesize that some of the errors made by the local classifier could be corrected by employing a global joint model that performs a collective classification taking into account the conversational dependencies between sentences (e.g., adjacency relations).
unlike synchronous conversations (e.g., phone, meeting), modeling conversational dependencies between sentences in asynchronous conversation is challenging, especially in those where explicit thread structure (reply-to relations) is missing, which is also our case.