Facts or friends? distinguishing informational and conversational questions in social Q and A sites

Max Harper, Daniel Moy, Joseph A Konstan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

190 Scopus citations

Abstract

Tens of thousands of questions are asked and answered every day on social question and answer (Q&A) Web sites such as Yahoo Answers. While these sites generate an enormous volume of searchable data, the problem of determining which questions and answers are archival quality has grown. One major component of this problem is the prevalence of conversational questions, identified both by Q&A sites and academic literature as questions that are intended simply to start discussion. For example, a conversational question such as ikdo you believe in evolution?" might successfully engage users in discussion, but probably will not yield a useful web page for users searching for information about evolution. Using data from three popular Q&A sites, we confirm that humans can reliably distinguish between these conversational questions and other informational questions, and present evidence that conversational questions typically have much lower potential archival value than informational questions. Further, we explore the use of machine learning techniques to automatically classify questions as conversational or informational, learning in the process about categorical, linguistic, and social differences between different question types. Our algorithms approach human performance, attaining 89.7% classification accuracy in our experiments.

Original languageEnglish (US)
Title of host publicationCHI 2009
Subtitle of host publicationDigital Life New World - Proceedings of the 27th International Conference on Human Factors in Computing Systems
Pages759-768
Number of pages10
DOIs
StatePublished - Dec 1 2009
Event27th International Conference Extended Abstracts on Human Factors in Computing Systems, CHI 2009 - Boston, MA, United States
Duration: Apr 4 2009Apr 9 2009

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other27th International Conference Extended Abstracts on Human Factors in Computing Systems, CHI 2009
CountryUnited States
CityBoston, MA
Period4/4/094/9/09

Keywords

  • Machine learning
  • Online community
  • Q and A

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