Identifying User Issues and Request Types in Forum Question Posts Based on Discourse Analysis

Ágnes Sándor, Nikolaos Lagos, Ngoc-Phuoc-An Vo, Caroline Brun

Abstract: In this paper we propose the detection of user issues and request types in technical forum question posts with a twofold purpose: supporting up-to-date knowledge generation in organizations that provide (semi-) automated customer-care services, and enriching forum metadata in order to enhance the effectiveness of search. We present a categorization system for detecting the proposed question post types based on discourse analysis, and show the advantage of using discourse patterns compared to a baseline relying on standard linguistic features. Besides the detailed description of our method, we also release our annotated corpus to the community.