Difference between revisions of "Milestone 3 TuringMachine DarkHorseIdea: Social Network for Crowdsourcing"

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(Created page with "==Background and Motivation == Class")
 
 
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==Author ==
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Neil Gaikwad
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=Leaderboard, social Network for crowdsourcing =
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'''Leveraging social network community structure for ensuring Reward, Respect, and Recognition . '''
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==Background and Motivation ==
 
==Background and Motivation ==
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Based on brainstorming and analysis of various missing components in the existing crowdsourcing system, we draw our design from the social network theory. We propose a crowdsourcing system architecture surrounded by Artificial Intelligence and Machine Learning algorithms. Below diagram gives abstract overview of interactions between various human-human, machine-machine, and human-machine workflows. Furthermore, we zoom into a dark horse  specific component of the system i.e . Leaderboard.
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[[File:Process.png|900px|center|Class]]   
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[[File:Crowdgaikwad.png|1002px|center|Class]]
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[http://crowdresearch.stanford.edu/w/img_auth.php/7/7f/The_future_of_crowd_work_%28private%29.pdf The Future of Work, Kittur etal 2013] and [http://sloanreview.mit.edu/article/the-collective-intelligence-genome/ Genomes of Collective Intelligence Framework, Malone etal 2010] have shown that Reputation, Incentives, and Motivation play a big role in developing sustainable crowd sourcing communities. However, the question remains how do we motivate people for a long period of time and how do we build the trust? HCI research provides guidelines for developing sustainable online communities. In [http://www.cs.cmu.edu/~ylataus/files/TausczikDabbishKraut2014.pdf Building Successful Online Communities: Evidence-Based Social Design, Tausczik, Dabbish, and Kraut 2012] discuss the Identity and bond Based attachments.
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[[File:Incentives.png|432px|center|Class]]     
 
   
 
   
  
[[File:Crowdgaikwad.png|902px|center|Class]]
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<u>'''Leaderboard profile for Requestors (individual profile as well as group ranking)'''</u>
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* How might we increase the '''reputation of requestors'''?
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* Motivate Requestors to be transparent and attract quality workers.
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* Workers can vote for top requestors who are providing clear instructions about the tasks and fairness. Borda Count Voting algorithm can be implanted to design the system; see [http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch23.pdf Networks, Crowds, and Markets: Reasoning about a Highly Connected World, Kleinberg]
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* Create Requestors' profile highlighting their track-records. Make an announcement of top performers.
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[[File:Brodacount.png|400px|center|Top]]
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* Workers can trust the requestors who are high ranked and provide good value for their time
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* Requestors' reputation will help them attract new talent for accomplishing complex tasks
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* Requestors' reputation will them earn reward from the crowdsourcing system administrators
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[[File:Req.png|400px|center|Top]]
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*How might we increase the '''reputation of workers'''? 
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* Motivate workers by being recognized in the community
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* Provide incentive to reach to top using hierarchy
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[[File:Top.png|400px|center|Top]]
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* Provide value to their commitment and ability to get things done
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* Requestors can trust the worker's profile based on making payments or recruiting them
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[[File:Imp.png|600px|center|Top]]

Latest revision as of 06:37, 12 July 2015

Author

Neil Gaikwad

Leaderboard, social Network for crowdsourcing

Leveraging social network community structure for ensuring Reward, Respect, and Recognition .

Background and Motivation

Based on brainstorming and analysis of various missing components in the existing crowdsourcing system, we draw our design from the social network theory. We propose a crowdsourcing system architecture surrounded by Artificial Intelligence and Machine Learning algorithms. Below diagram gives abstract overview of interactions between various human-human, machine-machine, and human-machine workflows. Furthermore, we zoom into a dark horse specific component of the system i.e . Leaderboard.

Class
Class

The Future of Work, Kittur etal 2013 and Genomes of Collective Intelligence Framework, Malone etal 2010 have shown that Reputation, Incentives, and Motivation play a big role in developing sustainable crowd sourcing communities. However, the question remains how do we motivate people for a long period of time and how do we build the trust? HCI research provides guidelines for developing sustainable online communities. In Building Successful Online Communities: Evidence-Based Social Design, Tausczik, Dabbish, and Kraut 2012 discuss the Identity and bond Based attachments.

Class


Leaderboard profile for Requestors (individual profile as well as group ranking)

  • How might we increase the reputation of requestors?
  • Motivate Requestors to be transparent and attract quality workers.
  • Workers can vote for top requestors who are providing clear instructions about the tasks and fairness. Borda Count Voting algorithm can be implanted to design the system; see Networks, Crowds, and Markets: Reasoning about a Highly Connected World, Kleinberg
  • Create Requestors' profile highlighting their track-records. Make an announcement of top performers.
Top
  • Workers can trust the requestors who are high ranked and provide good value for their time
  • Requestors' reputation will help them attract new talent for accomplishing complex tasks
  • Requestors' reputation will them earn reward from the crowdsourcing system administrators
Top
  • How might we increase the reputation of workers?
  • Motivate workers by being recognized in the community
  • Provide incentive to reach to top using hierarchy


Top
  • Provide value to their commitment and ability to get things done
  • Requestors can trust the worker's profile based on making payments or recruiting them
Top