UNDERSTANDING MOBILE Q&A USAGE: AN EXPLORATORY STUDY
UICHIN LEE, HYANGHONG KANG, EUNHEE YI MUN Y. YI, JUSSI KANTOLA
KNOWLEDGE SERVICE ENGINEERING DEPART-MENT
KOREA ADVANCED INSTITUTE OF SCIENCE & TECH-NOLOGY
(KAIST), SOUTH KOREA
KNOWLEDGE SERVICE ENGINEERING @ KAIST
KNOWLEDGE CON-VERGENCE
Mobile Social Q&A
• Social Q&A: – Facilitating “knowledge sharing” by leveraging the wisdom of crowds– Support flexible question formulation and customized answer delivery
• Mobile Social Q&A:– Key difference: short text messaging with mobile phones for Q&A– Chacha > 4bil; Naver Mobile Q&A (2010) > 3.8 mil
ONLINE CROWDSSMS OR APP
What’s the name of an exercise device that looks
like a jump rope….Y-Band?
How about Cooking?
Good homemade and/or useful mother’s day gift
Ideas?
Mobile Social Q&A
• Social Q&A: – Facilitating “knowledge sharing” by leveraging the wisdom of crowds– Support flexible question formulation and customized answer delivery
• Mobile Social Q&A:– Key difference: mobile phone based interactions (mainly via SMS) – Chacha (est. 2006) > 4bil; Naver Mobile Q&A (est. 2010): > 3.8 mil
ONLINE CROWDSSMS OR APP
What’s the name of an exercise device that looks
like a jump rope….Y-Band?I suggest…
Good homemade and/or useful mothers day gift
Ideas?
Mobile Q&A’s Key Distinctions: Mobile phone: Small screen & restricted keyboard Text messaging: Q&A length typically limited to 150 letters No Q&A editing, best answer selection
Motivation• Existing research mainly focused on characterizing conventional
social Q&A usage (Yahoo! Answer, Naver KiN)– Question types and topics [Kim 08, Harper 08, Rodrigues 09]– Response rate/time [Hsieh 09] Microsoft Live Q&A: 80%/2:53 – Answerer’s motivation (e.g., altruism, learning) [Raban 08, Nam 10]– Asker/answerer social network (power law) [Adamic 08]
• Mobile Q&A: accessing wisdom of crowds via mobile phones
• Usage contexts and interaction patterns would be very different from conventional social Q&A
• But so far little is known about usage patterns of mobile social Q&A
Research Questions and Contributions
• Goal: characterizing mobile Q&A usage– What are key drivers of mobile Q&A usage?– What types of questions are asked over mobile Q&A? – How do users interact with mobile Q&A to meet their
information needs?
• Our contributions: – Identified unique usage patterns of mobile Q&A
• Usage contexts: deeply wired into everyday life activities• Key factors: accessibility, convenience, promptness, satisficing behavior• Unique coping strategies (e.g., repeating/refining)
– Our findings offer practical system design implications
Research Methods
• Corroborative approach: real Q&A data + email survey
• Crawled dataset from Naver Mobile Q&A – Dataset period: June 1, 2010–July 31, 2011– # questions: ~2.4mil, # answers: ~3.1mil
• Email survey of Naver Mobile Q&A users– Survey questionnaire design:
• Part 1: Asked overall usage patterns of mobile Q&A • Part 2: Asked detailed situations/reasons about the questions that participants
asked in July 2011 (up to 5 questions)– # survey participants: 555
• 73.9%: teenagers, 15%: 20s, 5.1%: >= 30s• 49.5%: male users, 70.5%: smartphone users
Research Questions
RQ #1: What are the key drivers of mobile Q&A usage?
RQ #2: What types of questions are asked over mobile Q&A?
RQ #3: How do users interact with mobile Q&A to meet their information needs?
Key Drivers of Mobile Q&A Usage(1) Why Social Q&A is preferred to Web Search?
0 10 20 30 40 50 60 70
Save timeMore convenient
Less satisfactory web searchCustomized answersNot to be distracted
Not good at web search
46.5%
36.9%
34.2%
27.6%
25.2%
1.6%
(2) Why Mobile Social Q&A is preferred to Social Q&A/Web Search?Asking questions anytime, anywhere
Getting fast responsesMore convenient than web search
More convenient than existing Q&A Not to be distracted
Giving more satisfactory answers0 10 20 30 40 50 60 70
63.2%
46.5%
36.9%
27.6%
19.1%
7.0%
Key drivers : accessibility, convenience, promptness
Contexts of Mobile Q&A Usage• Everyday life information seeking [Savolainen 08]
– Dealing with everyday life projects, ranging from generic and routine (e.g., household care) to specific projects (e.g., hobbies)
What’s the name of an exercise device that looks like a jump rope, but you can hold your foot on it and pull it?
When I was watching a diet program on TV, I wanted to buy it but I had no
idea about its name.
watching
talking
studyingplanning
activities/miscother life
(e.g., exercising)
12%
13%
10%
18%
42%
Activity Coding Results
Coding results of context description of 206 questions
participants asked
Promptness of Mobile Social Q&A
• Response distribution: roughly power-law with exp cut-off• Avg: 15.5M & Median: 2.1M vs. MS Live Q&A: Avg 2H53M
0.99999 9.9999 99.999 999.99 9999.9 999990.00001
0.0001
0.001
0.01
0.1
1
3rd question2nd question1st question
Response time (seconds) Log scale
Frac
tion
of
inst
ance
s >
= t
(CC
DF,
log
scal
e)
1st answer
2nd answer3rd answer
Key drivers : accessibility, convenience, promptness
Answering page randomlyshows other old
unanswered questions
Browsing first few pages
Current question
Unanswered questions
Mobile Q&A Users’ Satisficing Behavior
• Satisficing behavior: good enough info satisfying the need although its quality is not the best (saving time and effort) [Prabha 07]
• Mobile Q&A users expect to trade quality for accessibility, convenience, promptness – Mobile Q&A provides “good enough” info although its
quality is inferior to other info sources • Mobile Q&A users tend to minimize “coping efforts”– Repeating (32.3%), rephrasing (36.8%) – Waiting (27.8%), or even stop seeking (39.8%)
Key drivers: accessibility, convenience, promptness, satisficing behavior
Research Questions
RQ #1: What are the key drivers of mobile Q&A usage?
RQ #2: What types of questions are asked over mobile Q&A?
RQ #3: How do users interact with mobile Q&A to meet their information needs?
17%
22%
29%
14%
4%
14%
20% 40%
SNS-based Q&A
[Morris 10]
Questions in Mobile Q&A
4.1%
2.7%
1%
InformationOpinion
SuggestionMonologue
RequestsEtc.
23.4%
17.7%
20% 40%
Mobile Social Q&A
51.1% 35%
23%
39%
3%
20%
Social Q&A
[Kim 08]
40%
Prevalently used to meet “quick info needs” arising from daily activities
InformationOpinion
Suggestion
“I’m at the Seoul station. Which bus goes to Sadang?”“Who do you like most in Girl’s Generation?”“Please recommend a good restaurant in Seoul”
Question Type Examples
[Kim 08]
Expressive MonologueRequests
“Too bad, Lee just missed a goal!!”“Please send me some interesting e-books!“ [Ervin-Tripp 64]
Research Questions
RQ #1: What are the key drivers of mobile Q&A usage?
RQ #2: What types of questions are asked over mobile Q&A?
RQ #3: How do users interact with mobile Q&A to meet their information needs?
Interaction Behavior: Repeating/Refining
• Repeating/refining as coping strategies of satisfying information needs
• Refining behavior example:– Question 1 (10:23AM): “How do I get to Sadang Station from
Seoul Station?”• Answer 1 (10:25AM): “Take a subway line number 4”• Answer 2 (10:27AM): “Just take a taxi”
– Question 2 (10:28AM) : “How long does it take and how much does it cost to go to Sadang Station from Seoul Station by taxi?• Answer 1 (10:30AM): “About 31 minutes, and 9,400 Won”
• Differences from “Query Refinement in web search”– # answers, predictability, delay scale
Interaction Behavior: Repeating/Refining
• How often repeating/refining behavior occurs?– Automatic classification: measuring cosine similarity of questions– Threshold value = 0.6 (set based on manual classification)
• Refining: similarity score = [0.6, 1), Repeating: similarity score = 1
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Frac
tion
of u
sers
0.10
0.20
0.30
0.05
0.15
0.25
0.00
Frac. of repeated/refined questions
AutomaticClassification
Results
Sim
ilarit
y sc
ore
Repeating/Refining Questions
OtherQuestions
ManualClassification
Results
0.2
1.0
0.4
0.8
0.0
0.6
Large fraction of users repeat/refine questions
Design Implications
• User interface design for askers: lowering cognitive burden of askers – Supporting popular coping strategies such as repeating, refining
• User interface design for answerers: improving answer speed and quality– Context sharing mechanism allowing answerers to know asker’s
interaction history – Automatic topic classification (focusing on specific topics)– Automatic suggestion of answers (if repeated questions are posted,
e.g., asking sports score)– Improving browsing capability of unanswered questions (delay
reduction)
Conclusion
• Mobile Q&A usage: deeply wired into daily life activities
• Prevalently used to meet “quick info needs” arising while performing daily activities
• Key factors of mobile Q&A usage: accessibility, convenience, promptness, satisficing behavior
• Coping strategies: repeating and refining questions
• System design implications (e.g., asker/answerer UI design, etc.)
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