1 / 18

Understanding Mobile Q&A Usage: An Exploratory Study

Knowledge Convergence. Knowledge Service Engineering @ KAIST. Understanding Mobile Q&A Usage: An Exploratory Study.

lonna
Download Presentation

Understanding Mobile Q&A Usage: An Exploratory Study

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Knowledge Convergence Knowledge Service Engineering @ KAIST Understanding Mobile Q&A Usage: An Exploratory Study Uichin Lee, Hyanghong Kang, EunheeYi Mun Y. Yi, JussiKantolaKnowledge Service Engineering DepartmentKorea Advanced Institute of Science & Technology (KAIST), South Korea

  2. 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 What’s the name of an exercise device that looks like a jump rope…. How about Cooking? Good homemade and/or useful mother’s day gift Ideas? Online Crowds SMS or APP Y-Band?

  3. 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 • 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 What’s the name of an exercise device that looks like a jump rope…. I suggest… Good homemade and/or useful mothers day gift Ideas? Online Crowds SMS or APP Y-Band?

  4. Motivation • Existing research mainly focused on characterizing conventional social Q&A usage (Yahoo! Answer, NaverKiN) • 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 patternswould be very different from conventional social Q&A • But so far little is known about usage patterns of mobile social Q&A

  5. 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

  6. 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

  7. 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?

  8. Key Drivers of Mobile Q&A Usage (1) Why Social Q&A is preferred to Web Search? 46.5% Save time More convenient Less satisfactory web search Customized answers Not to be distracted Not good at web search 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 responses More convenient than web search More convenient than existing Q&A Not to be distracted Giving more satisfactory answers 63.2% 46.5% 36.9% 27.6% 19.1% 7.0% Key drivers : accessibility, convenience, promptness

  9. 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? • Activity Coding Results 12% watching other life 13% talking activities/misc (e.g., exercising) 10% studying 42% When I was watching a diet program on TV, I wanted to buy it but I had no idea about its name. 18% planning Coding results of context description of 206 questions participants asked

  10. 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 Browsing first few pages Answering page randomlyshows other old unanswered questions 3rd answer Current question 2nd answer Unanswered questions 1st answer Key drivers : accessibility, convenience, promptness

  11. 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

  12. 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?

  13. Questions in Mobile Q&A Question Type Examples Information Information “I’m at the Seoul station. Which bus goes to Sadang?” Opinion Mobile Social Q&A Social Q&A SNS-based Q&A Opinion “Who do you like most in Girl’s Generation?” Suggestion [Kim 08] Suggestion “Please recommend a good restaurant in Seoul” 35% [Morris 10] 17% Monologue Expressive Monologue “Too bad, Lee just missed a goal!!” 23.4% 23% 22% Requests “Please send me some interesting e-books!“ Requests 39% 29% 17.7% [Ervin-Tripp 64] Etc. 14% 4.1% 4% 2.7% [Kim 08] 14% 1% 3% 20% 40% 20% 40% 20% 40% 51.1% Prevalently used to meet “quick info needs” arising from daily activities

  14. 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?

  15. 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

  16. 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 0.30 1.0 ManualClassificationResults AutomaticClassificationResults 0.25 0.8 0.20 0.6 Similarity score Fraction of users 0.15 0.4 0.10 0.2 0.05 0.0 0.00 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Large fraction of users repeat/refine questions Repeating/Refining Questions OtherQuestions Frac. of repeated/refined questions

  17. 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)

  18. 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.)

More Related