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Friendsourcing,

Selfsourcing, and

Learnersourcing

Lecturer: Kenneth Huang

txh710@psu.edu

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Mar 19, 2020

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Changes!

  1. All the lectures during the remote period will be pre-recorded. The video will be available online to the students before each meeting time of the class.�
  2. My office hour at 11:30am on Tuesday and Thursday.�
  3. No quizzes during the remote period.

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We’re Going to Talk About…

  • Slow Search
  • Friendsourcing
  • Selfsourcing�
  • Learnersourcing

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Slides adopted from the following sources:�1. http://teevan.org/publications/talks/stanford16-slowsearch.pptx, by Jaime Teevan

2. https://groupsight.github.io/media/Morris_Keynote_GroupSight2017.pptx, by Meredith R. Morris

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Slow Movements

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Speed Focus in Search Reasonable

  • Focus on search speed has good motivation
    • Increased time has negative impact
    • Even positive changes negative�
  • Search engines make lots of compromises to speed things up

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Not All Searches Need to Be Fast

  • Long-term tasks
    • Long search sessions
    • Multi-session searches�
  • Social search
    • Question asking�
  • Technologically limited
    • Mobile devices
    • Limited connectivity
    • Search from space

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Making Use of Additional Time

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Searching v.s. Asking

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Searching v.s. Asking

  • Friends respond quickly
    • 58% of questions answered by the end of search
    • Almost all answered by the end of the day�
  • Some answers confirmed search findings�
  • But many provided new information
    • Information not available online
    • Information not actively sought
    • Social content

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Morris, M. R., Teevan, J., & Panovich, K. (2010, May). A comparison of information seeking using search engines and social networks. In Fourth International AAAI Conference on Weblogs and Social Media.

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Shaping the Replies from Friends

Teevan, J., Morris, M. R., & Panovich, K. (2011, July). Factors affecting response quantity, quality, and speed for questions asked via social network status messages. In Fifth International AAAI Conference on Weblogs and Social Media.

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Shaping the Replies from Friends

  • Larger networks provide better replies
  • Faster replies in the morning, more in the evening
  • Question phrasing important
    • Include question mark
    • Target the question at a group (even at anyone)
    • Be brief (although context changes nature of replies)
  • Early replies shape future replies
  • Opportunity for friends and algorithms to collaborate to find the best content

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Human Computation

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  • Low-cost
  • Always-available workers
  • Anonymous

Crowdsourcing

  • Free
  • High saturation [Pew 2012]
  • Personalized and trusted [Morris 2010]
  • Matches existing model [Kane 2009, Burton 2012]

Friendsourcing

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Human Computation for Image Labeling

VizWiz [Bigham et al., 2010]�VizWiz Social [Brady et al., 2013]

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✓ Free

✗ Answers may be slow

✓ Friends are trusted

✗ May bother friends

Crowdsourcing

Friendsourcing

Costs money✗

Extremely fast ✓

Workers are strangers ✗

No social costs ✓

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Social Microvolunteering

Brady, E., Morris, M. R., & Bigham, J. P. (2015, April). Gauging receptiveness to social microvolunteering. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 1055-1064). ACM.

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Visual Answers Pilot

  • Pilot study with 91 volunteers
    • Compensated half of them with $20 for participating
  • 64% had friends, family members with disability
  • Questions pre-selected from VizWiz archives
  • Visual Answers posted 1,130 questions
  • 42% of questions received at least 1 comment
  • 756 total comments (avg. 1.6 per answered post)
  • Examined response speed, quality, and feedback

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Response Speed

  • First comment average 50 minutes
  • Posted to 20 walls, first response in 156 seconds
    • 66 seconds if question is easy to answer

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Answer Quality

  • “Good faith” answers
    • Correct answer if question is answerable

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[“Which knob, is it the left or the right, is for temperature control?”] �Left one is for Temperature. It has three settings cold to the left, 21 Celsius/70 Farenheit in the center and warm to the right.

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[“What does this bottle say?”] �The flash on the camera seems to have caused the label to be too bright white to read. Also; the picture is not centered to see the full product. My guess is that it is window/glass cleaner.

  • “Good faith” answers
    • Explanation, feedback on how to retake if unanswerable

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Volunteer Responses

  • 95% felt positive about their use of Visual Answers
  • 83% said that they would want to use Facebook for social microvolunteering in the future

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We’re Going to Talk About…

  • Slow Search
  • Friendsourcing
  • Selfsourcing�
  • Learnersourcing

​

Slides adopted from the following sources:�1. http://teevan.org/publications/talks/stanford16-slowsearch.pptx, by Jaime Teevan

2. https://groupsight.github.io/media/Morris_Keynote_GroupSight2017.pptx, by Meredith R. Morris

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Hahn, N., Iqbal, S. T., & Teevan, J. (2019, May). Casual Microtasking: Embedding Microtasks in Facebook. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-9).

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We’re Going to Talk About…

  • Slow Search
  • Friendsourcing
  • Selfsourcing�
  • Learnersourcing

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Slides adopted from the following sources:�1. http://teevan.org/publications/talks/stanford16-slowsearch.pptx, by Jaime Teevan

2. https://groupsight.github.io/media/Morris_Keynote_GroupSight2017.pptx, by Meredith R. Morris

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Kim, J., Guo, P. J., Cai, C. J., Li, S. W., Gajos, K. Z., & Miller, R. C. (2014, October). Data-driven interaction techniques for improving navigation of educational videos. In Proceedings of the 27th annual ACM symposium on User interface software and technology (pp. 563-572).

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Weir, S., Kim, J., Gajos, K. Z., & Miller, R. C. (2015, February). Learnersourcing subgoal labels for how-to videos. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 405-416). ACM.

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Friendsourcing,

Selfsourcing, and

Learnersourcing

Lecturer: Kenneth Huang

txh710@psu.edu

​

Mar 19, 2020