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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.
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