Editing Building Successful Online Communities (Fall 2016) (section)

=== December 5: Crowdsourcing ===

<!-- '''Resources:'''

* [https://canvas.uw.edu/files/33600343/download?download_frd=1 Week 8 Reading Note] (Requires UW Access)
* [https://canvas.uw.edu/courses/987817/files/33628104/download?wrap=1 Lecture Slides] (Requires UW Access)
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Our guest lecturer will be [http://www.andresmh.com/ Andrés Monroy-Hernández].

'''Required Readings:'''

* Howe, J. (2006). [https://www.wired.com/2006/06/crowds/ The rise of crowdsourcing]. Wired Magazine, 14(6), 1–4.
* [Case] [https://docs.aws.amazon.com/AWSMechTurk/latest/RequesterUI/Introduction.html Amazon Mechanical Turk Requester UI Guide] ''[Skim, but make sure you're ready to submit tasks.]''
* [Case] [https://mturkpublic.s3.amazonaws.com/docs/MTURK_BP.pdf Amazon Mechanical Turk Best Practices Guide]. ''[Skim, but make sure you're ready to submit tasks.]''

'''Optional Readings:'''

Our guest speaker will be talking about these three papers. It might be good to look these over before class:

* Cranshaw, J., Monroy-Hernández, A., & Needham, S. A. (2016). [https://doi.org/10.1145/2858036.2858573 Journeys & Notes: Designing Social Computing for Non-Places]. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 4722–4733). New York, NY, USA: ACM. [Available through UW libraries]
* Agapie, E., & Monroy-Hernández, A. (2015). [http://arxiv.org/abs/1507.01300 Eventful: Crowdsourcing Local News Reporting]. arXiv:1507.01300 [Cs].
* Kim, J., & Monroy-Hernandez, A. (2016). [https://doi.org/10.1145/2818048.2820072 Storia: Summarizing Social Media Content Based on Narrative Theory Using Crowdsourcing]. In ''Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing'' (pp. 1018–1027). New York, NY, USA: ACM. [Available through UW libraries]

'''Assignment ''before'' class:'''

* [https://www.mturk.com/mturk/welcome mTurk] - Find and complete at least 2 "hits" as a worker on [http://mturk.com Amazon Mechnical Turk]. Note that to do this you will need to create a ''worker'' account on Mturk. 
** Record (write down) details and notes about your tasks: What did you do? Who was the requester? What could you was the purpose of the task (as best you could tell)? What was the experience like? What research applications can you (not) imagine for this kind of system? 
** If you're not a US citizen, creating an requester account is much more complicated because it involves getting paid and ensuring that you have authorization to work. ''Please just skip this part.''
* [https://www.mturk.com/mturk/welcome mTurk] Create a "requester" account. Doing so may require up top 48 hours to be approved so please do that ''immediately'' so you have it ready to go in class.
* [https://www.zooniverse.org/ Zooniverse] - Complete at least 1-2 tasks in two different projects of your choice on Zooniverse. Come to class ready to talk about it. 

'''In class exercise:'''

* Design and deploy a small-scale research task on Mturk. Note that to do this, you will need to create a ''requester'' account on Mturk. Be sure to allow some time to get the task design the way you want it! Some ideas for study designs you might do:
** A small survey. 
** Classification of texts or images (e.g., label tweets, pictures, or comments from a discussion thread).
** A small experiment (e.g., you can do a survey where you insert ''different'' images and ask the same set of questions. Check out the [https://requester.mturk.com/help/getting_started.html Mturk requester getting started guide]
* Prepare to share details of your small-scale research task in class, including results (they will come fast).

''Note:'' In terms of running your task, it will cost real money and you have to put money on your Amazon account yourself. Each group will have a $3 budget. Please use your credit card to put $3 on your account right away. You should be able to do this in class. I will pay each of you $3 in cash next week to reimburse you for the cost of running the experiment.