Q&A services allow one to express an information need in the form of a natural language question and seek information from users of those services. Despite a recent rise in the research related to various issues of online Q&A, there is still a lack of consideration for how the situational context behind asking a question affects quality judgements. By focusing on users’ expectations when asking a question, the work reported here builds on a framework of understanding how people assess information. Mixed method analysis – employing sequentially the Internet-based survey, diary and interviews – was used in a study to investigate this issue. A total of 226 online Q&A users participated in the study, and it was found that looking for quick responses, looking for additional or alternative information, and looking for accurate or complete information were the primary expectations of the askers. Findings can help identify why and how users engage in information seeking within an online Q&A context, and may help develop more comprehensive personalised approaches to deriving information relevance and satisfaction that include user expectations.
TathamM.U.S. Visits to Question and Answer Websites Increased 118 Percent Year over-Year Yahoo! Answers receives 74 percent of all U.S. visits. Hitwise, 2008. Available at: http://www.webcitation.org/5k7EsNrUd
(accessed December 2015).
2.
BianJLiuYAgichteinEZhaH.Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media. In: Proceedings of the 17th International World Wide Web Conference, Beijing, China, 2008, pp. 467–476.
3.
GazanR. SQA. Journal of the Association for Information Science Technology (JASIST)2011; 62(12): 2301–2312.
4.
KimSOhSOhJS.Evaluating Health Answers in a Social Q&A Site. In: Proceedings of the American Society for Information Science and Technology (ASIST), Vancouver, British Columbia, Canada, 2009.
5.
ShahCPomerantzJ.Evaluating and predicting answer quality in community QA. In: Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval, Geneva, Switzerland, 2010, pp. 411–418.
6.
AgichteinELiuYBianJ.Modeling information-seeker satisfaction in community question answering. Journal of ACM Transactions on Knowledge Discovery from Data2009; 3(2): 10.
7.
MaiJ-E.The quality and qualities of information. Journal of the Association for Information Science and Technology (JASIST)2013, 64(4): 675–688.
8.
HarperFM.RabanDRafaeliSKonstanJA.Predictors of answer quality in online Q&A sites. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Florence, Italy, 2008, pp. 865–874.
9.
ChoiEKitzieVShahC.Developing a Typology of Online Q&A Models and Recommending the Right Model for Each Question Type. In: Proceedings of the Association for Information Science and Technology (ASIST), Baltimore, MD, USA, 2012, pp. 1–4.
10.
AdamicLAZhangJBakshyEAckermanMS.Knowledge sharing and Yahoo Answers: Everyone knows something. In: Proceedings of the 17th International World Wide Web Conference, Beijing, China, 2008, pp. 665–674.
11.
ShahCOhSOhJS.Research agenda for social Q&A. Library & Information Science Research2009; 31(4): 205–209.
BernhardDGurevychI.Answering Learners’ Questions by Retrieving Question Paraphrases from Social Q&A Sites. In: Proceedings of the 3rd Workshop on Innovative Use of NLP for Building Educational Applications in conjunction with ACL, Columbus, OH, USA, 2008, pp. 44–52.
14.
ChenYHoTKimY.Knowledge Market Design: A field Experiment at Google Answers. Journal of Public Economics Theory2008; 12(4): 641–664.
15.
PomerantzJNicholsonSBelangerYLankesRD.The Current State of Digital Reference. Information Processing and Management2004; 40(2): 347–363.
16.
HorowitzDKamwarS.The Anatomy of a Large-Scale Social Search Engine. In: Proceedings of the 17th International World Wide Web Conference, Geneva, Switzerland, 2010, pp. 431–440.
17.
PaulSAHongLChiEH.Is Twitter a Good Place for Asking Questions? A Characterization Study. In: Proceedings of Fifth International AAAI Conference on Weblogs and Social Media, Barcelona, Spain, 2011.
18.
HoneycuttCHerringS.Beyond Microblogging: Conversation and Collaboration in Twitter. In: Proceedings of 42nd Hawaii International Conference on System Sciences, Waikoloa, HI, USA, 2009, pp. 1–10.
19.
MorrisMRTeevanJPanovichK.What do people ask their social networks, and why?: a survey study of status message q&a behavior. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Atlanta, GA, 2010, pp. 1739–174.
20.
CampbellJDunnetteMLawlerEWeickK.Managerial Behavior, Performance, and Effectiveness. New York: McGraw-Hill, 1970.
21.
FeatherNT.Expectancy-value approaches: Present status and future directions. In: FeatherNT (ed.) Expectations and actions: Expectancy-value models in psychology. Hillsdale, NJ: Erlbaum, 1982, pp. 395–420.
22.
TaylorRS.Question-negotiation and information seeking in libraries. College and Research Libraries1968; 29(3): 178–194.
23.
BarryCL.User-defined relevance criteria: An exploratory study. Journal of the American Society for Information Science and Technology (JASIST)1994; 45(3): 149–159.
24.
BatemanJ.Modeling the importance of end-user relevance criteria. In: Proceedings of the 62nd ASIS Annual Meeting, Washington DC, MA, USA, 1999, pp. 396–406.
25.
RiehSY.Judgment of information quality and cognitive authority in the Web. Journal of the American Society for Information Science and Technology (JASIST)2002; 53(2): 145–161.
26.
JanesJHillCRolfeA. (2001). Ask-an-expert services analysis. Journal of the American Society for Information Science and Technology (JASIST)2001; 52(13): 1106–1121.
27.
ShahCKitzieV.Social Q&A and Virtual Reference – Comparing Apples and Oranges With the Help of Experts and Users. Journal of American Society of Information Science and Technology (JASIST)2012; 63(10): 2020–2036.
28.
WangPSoergelD.A cognitive model of document use during a research project. Study I. Document selection. Journal of the American Society for Information Science and Technology (JASIST)1998; 49(2): 115–133.
TashakkoriATeddlieC.Mixed methodology: Combining qualitative and quantitative approaches. Applied Social Research Methods Series, 46. Thousand Oaks, CA: Sage Publications, 1998.
31.
GayLRAirasianP.Educational research: Competencies for analysis and application. 6th ed.Upper Saddle River, NJ: Merrill, 2000.
32.
SieberSD.The integration of fieldwork and survey methods. American Journal of Sociology1973; 73(6): 1335–1359.
33.
CharlesCMMertlerCA.Introduction to educational research. 4th ed.Boston, MA: Allyn and Bacon, 2002.
34.
CreswellJW.Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River, NJ: Merrill/Pearson, 2002.
35.
BrewerNTHallmanWKFielderNKipenHM.Why do people report better health by phone than by mail?Medical Care2004; 42(9): 875–883.
36.
CrockettLJSchulenbergJEPetersenAC.Congruence between Objective and Self-Report Data in a Sample of Young Adolescents. Journal of Adolescent Research1987; 2(4): 383–392.
37.
ReisHT.Domains of experience: investigating relationship processes from three perspectives. In: ErberRGilmoreR (ed.) Theoretical Frameworks in Personal Relationships. Mahwah, NJ: Erlbaum, 1994, pp. 87–110.
38.
González-IbáñezRShahC.Coagmento: A system for supporting collaborative information seeking. In: Proceedings of the American Society for Information Science and Technology (ASIST), Baltimore, MA, USA, 2012.
39.
ShahC.Coagmento - A Collaborative Information Seeking, Synthesis, and Sense-making Framework. In: Proceedings of ACM Conference on Computer-Supported Cooperative Work and Social Computing, Savannah, Georgia, USA, 2010.
40.
HodgkinS.Telling it all: A story of women’s social capital using a mixed methods approach. Journal of Mixed Method Research2008; 2(4): 296–316.
41.
KvaleS.The qualitative research interview: A phenomenological and a hermeneutical mode of understanding. Journal of Phenomenological Psychology1983; 14(2): 171–196.
42.
ChoiEShahC.User motivation for asking a question in online Q&A services. Journal of the Association for Information Science and Technology (JASIST) (in press).
43.
ChoiEKitzieVShahC.10 points for the best answer!”– Baiting for Explicating Knowledge Contributions within Online Q&A. In: Proceedings of the Association for Information Science and Technology, Montreal, Quebec, Canada, 2013, pp. 1–4.
44.
FichmanP.A comparative assessment of answer quality on four question answering sites. Journal of Information Science2011; 37(5): 476–486.
45.
BloomaMJChuaAGohD.A Predictive Framework for Retrieving the Best Answer. In: Proceedings of the 23rd Annual ACM Symposium on Applied Computing, Fortaleza, Ceará, Brazil, 2008, pp. 1107–1111
46.
BloomaMJChuaAGohD.What makes a high quality user-generated answer?IEEE Internet Computing2011; 15(1): 66–71.
47.
ShachafP.The paradox of expertise: Is the Wikipedia Reference Desk as good as your library?Journal of Documentation2009; 65(6): 977–963.
48.
JeonGYJKimYMChenY.Re-examining price as a predictor of answer quality in an online Q&A site. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Atlanta, GA, USA, 2010, pp. 325–328.
49.
ShahCKitzieVChoiE.Modalities, motivations, and materials - investigating traditional and social online Q&A services.Journal of Information Science2014; 40(5): 669–687.
50.
MaiJE.The quality and qualities of information. Journal of the Association for Information Science and Technology (JASIST)2013; 64(4): 675–688.
51.
WorrallAOhS.The place of health information and socio-emotional support in social questioning and answering. Information Research2013; 18(3). Available at: http://www.informationr.net/ir/18–3/paper587.html
(accessed September 2013).
