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Web Forum Retrieval and Text Analytics: A Survey



Author(s): Doris Hoogeveen;Li Wang;Timothy Baldwin;Karin M. Verspoor

Source:
    Journal:Foundations and Trends® in Information Retrieval
    ISSN Print:1554-0669,  ISSN Online:1554-0677
    Publisher:Now Publishers
    Volume 12 Number 1,
Pages: 167(1-163)
DOI: 10.1561/1500000062

Abstract:

This survey presents an overview of information retrieval, natural language processing and machine learning research that makes use of forum data, including both discussion forums and community questionanswering (cQA) archives. The focus is on automated analysis, with the goal of gaining a better understanding of the data and its users. We discuss the different strategies used for both retrieval tasks (post retrieval, question retrieval, and answer retrieval) and classification tasks (post type classification, question classification, post quality assessment, subjectivity, and viewpoint classification) at the post level, as well as at the thread level (thread retrieval, solvedness and task orientation, discourse structure recovery and dialogue act tagging, QA-pair extraction, and thread summarisation). We also review work on forum users, including user satisfaction, expert finding, question recommendation and routing, and community analysis. The survey includes a brief history of forums, an overview of the different kinds of forums, a summary of publicly available datasets for forum research, and a short discussion on the evaluation of retrieval tasks using forum data. The aim is to give a broad overview of the different kinds of forum research, a summary of the methods that have been applied, some insights into successful strategies, and potential areas for future research.