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Understanding and Modeling User Beha...

Liu, Zhe.

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Understanding and Modeling User Behavior in Social Question and Answering.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Understanding and Modeling User Behavior in Social Question and Answering./
Author:	Liu, Zhe.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2015,
Description:	130 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
Contained By:	Dissertation Abstracts International78-10A(E).
Subject:	Information science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10609595
ISBN:	9781369828108

Understanding and Modeling User Behavior in Social Question and Answering.
Liu, Zhe.

Understanding and Modeling User Behavior in Social Question and Answering. - Ann Arbor : ProQuest Dissertations & Theses, 2015 - 130 p.

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.

Thesis (Ph.D.)--The Pennsylvania State University, 2015.

In this research, I focus on a specific type of information seeking on social networking sites (SNS), called social question and answering (social Q&A), in which people ask natural language questions to their networks via status updates. Compared with the traditional information seeking methods (e.g. search engines, online databases, etc.) and community question answering services (e.g. Yahoo! Answers, Quora, Answers.com, StackOverflow, etc.), social Q&A is considered to provide more trustworthy, contextualized, and interactive responses. Although there is an extensive amount of research and literature available on the topic of information seeking via the Internet, due to the distinct nature of social Q&A, still relatively little is known about how users behave in the process of information seeking and sharing under social context. To fill in this gap, in this study I examine three aspects of social Q&A.

ISBN: 9781369828108Subjects--Topical Terms:

554358
Information science.

Understanding and Modeling User Behavior in Social Question and Answering.
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100 1 $a Liu, Zhe. $3 1952384
245 1 0 $a Understanding and Modeling User Behavior in Social Question and Answering.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2015
300 $a 130 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
500 $a Adviser: Bernard J. Jansen.
502 $a Thesis (Ph.D.)--The Pennsylvania State University, 2015.
520 $a In this research, I focus on a specific type of information seeking on social networking sites (SNS), called social question and answering (social Q&A), in which people ask natural language questions to their networks via status updates. Compared with the traditional information seeking methods (e.g. search engines, online databases, etc.) and community question answering services (e.g. Yahoo! Answers, Quora, Answers.com, StackOverflow, etc.), social Q&A is considered to provide more trustworthy, contextualized, and interactive responses. Although there is an extensive amount of research and literature available on the topic of information seeking via the Internet, due to the distinct nature of social Q&A, still relatively little is known about how users behave in the process of information seeking and sharing under social context. To fill in this gap, in this study I examine three aspects of social Q&A.
520 $a First, in order to better understand the information needs of the questioners in a microblogging environment, I develop a taxonomy of question types in social Q&A, called ASK. This taxonomy allows us to differentiate questions according to their underlying intents, and then direct them to the most appropriate respondents for help. To apply the taxonomy to practical problems, I also present the implementation of an automatic classification method to categorize the social Q&A questions according to the ASK taxonomy.
520 $a Second, noticing the low response rate in social Q&A, I examine a set of factors that would affect the response probability of a question. Specifically, I limit the scope to extrinsic factors only, given the existence of literature focusing on factors from both social and cognitive perspectives in knowledge sharing. For the analysis, I collect over 20 thousand real-world questions posted on Weibo, which is the largest microblogging site in China.
520 $a Third, to validate the effectiveness of question routing systems in social Q&A, as well as to characterize the voluntary knowledge sharing behavior among individuals under social context, I analyze a collection of questions and answers posted during a 10-month period on Weiwen, a Chinese question routing services based on microblogging sites. I explore the patterns demonstrated by the knowledge contributors from three different perspectives: user behavior, user interest, and user connectedness. I also propose a predictive model on active contributors in social Q&A environment based on a number of non-Q&A features.
520 $a I believe this thesis is of interest as it very well addresses the research gaps concerning the understanding of information needs in social Q&A, and the effectiveness of SNS in handling question-answering. Findings from this research would be of practical value as well, as it could fulfill the need for technologies capable of performing question routing tasks to help people find what they need.
590 $a School code: 0176.
650 4 $a Information science. $3 554358
650 4 $a Web studies. $3 2122754
650 4 $a Technical communication. $3 3172863
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710 2 $a The Pennsylvania State University. $b Information Sciences and Technology. $3 2095842
773 0 $t Dissertation Abstracts International $g 78-10A(E).
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