Difference between revisions of "WinterMilestone 3 BPHC ReputationIdea : Referral Network for Workers"

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(Created page with " == Referral Network for Workers == The ideas you brainstormed, (at least 10 ideas for trust, and at least 10 ideas for power). Provide them in whatever format you want - di...")
 
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One of the major needs identified in existing platforms for crowd-sourcing is the ability of the platform to effectively match capable workers with suitable jobs or HITs (Human Intelligence Tasks). The Stanford Crowd Research Team has thus far developed their Daemo Platform, which makes a significant step in meeting this requirement through the Boomerang Ranking System.
  
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We propose a referral based system that deals with the following reputation and relevant work issues:
  
== Referral Network for Workers ==
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* A problem with a system that prefers assigning tasks to workers with high reputation is that new workers may find it difficult to find good HITs. Requesters would tend to allot jobs to the same set of highly rated users. Similarly, existing workers would tend to take up HITs from the same set of requesters with high ratings.
  
The ideas you brainstormed, (at least 10 ideas for trust, and at least 10 ideas for power). Provide them in whatever format you want - diagrams, sketches, descriptions, or a combination (the wiki supports images, [http://www.mediawiki.org/wiki/Help:Images see here] for instructions on uploading them).
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* Workers rely on external forums (TurkerNation, Reddit etc) to find good HITs from reliable requesters. Clearly any future crowdsourcing platform should reduce this burden on the worker by allowing dedicated workers to easily share good HITs and help fellow workers to find relevant work .
  
=== Introduction ===
 
  
=== Implementation of a Referral Network for Crowdsourcing ===
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== Referral Network for Workers ==
  
=== Benefits of Referral Network ===
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=== Introduction ===
  
For each of the 4 ideas (2 for trust, 2 for power), describe (using diagrams, sketches, storyboards, text, or some combination) the ideas in further detail.
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The employee referral network in the corporate world is known to be a cost and time effective method of recruitment that produces high quality candidates. 92% of the participants in the Global Employee Referral Index 2013 Survey stated that referrals were a top source of recruitment. We thought about adapting the referral system to our crowd sourcing platform design. This would enable workers to recommend or “refer” other workers (existing or new) for good HITs.
  
Please <strong>create a separate wiki page for each of your ideas</strong>, so we can link to them individually. The title of the wiki page should be Milestone 3 followed by your team name and a description of the idea itself (ex: [[Milestone 3 YourTeamName TrustIdea 1: Automatic Pricing for Tasks based on Average Completion Time]]). Once done, post a link to each of your trust-related ideas to http://crowdresearch.meteor.com/category/milestone-3-trust-ideas and a link to each of your power-related ideas to http://crowdresearch.meteor.com/category/milestone-3-power-ideas when done, following the instructions at http://crowdresearch.meteor.com/posts/bXSNbqihjajASBQEL
 
  
=== Trust-related Ideas ===
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=== Implementation of a Referral Network for Crowdsourcing ===
  
* [[Milestone 3 YourTeamName TrustIdea 1: Description of some trust-related idea]] - http://crowdresearch.meteor.com/posts/TaNbEkmeoSSiv5vDB
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We illustrate the use of the referral system through the following example.
* [[Milestone 3 YourTeamName TrustIdea 2: Description of another trust-related idea]] - http://crowdresearch.meteor.com/posts/ShEsGS3tx2Gdq9noJ
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=== Power-related Ideas ===
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Requester R has a HIT to post on the crowdsourcing platform. R can view highly rated workers using Boomerang and make the HIT visible to them (or post the HIT publicly for all to see).
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Worker W notices the HIT posted by R and has the following options:
  
* [[Milestone 3 YourTeamName PowerIdea 1: Description of some power-related idea]] - http://crowdresearch.meteor.com/posts/HEiG2GyJWLFPzThYc
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Accept the HIT
* [[Milestone 3 YourTeamName PowerIdea 2: Description of another power-related idea]] - http://crowdresearch.meteor.com/posts/qsv2bcRNjSL3PC8sC
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Share the HIT with fellow workers. In the referral based scheme, this can be done in the following ways:
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W refers workers he or she knows to R.
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W can publicly offer to refer anyone who is interested in HIT. This is similar to how referrals are shared across social networks like Facebook, Twitter. This referral sharing network can be integrated into the crowdsourcing platform, removing the need for multiple external forums.
  
== Dark Horse idea ==
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The quality of referrals can be incentivized in a number of ways. A rudimentary way would be to include a measure of good referrals in the scores used to rank workers and requesters. A separate index could be used for referrals or requesters may reward good referrals with bonus payments.
  
Describe your dark horse idea (using diagrams, sketches, storyboards, text, or some combination).
 
  
Please <strong>create a separate wiki page for your dark horse idea</strong> so we can link to it individually. Post the link on http://crowdresearch.meteor.com/category/milestone-3-dark-horse-ideas when done
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=== Benefits of Referral Network ===
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A HIT initially becomes visible to highly rated workers who have worked with that particular requester in the past. The referral network enables sharing of HITs with other (existing and new) workers who would otherwise have been the last in line to see the HIT. This is especially useful when a requester posts a large number of HITs, which can be shared quickly among workers.
  
* [[Milestone 3 YourTeamName DarkHorseIdea: Description of some dark horse idea]] - http://crowdresearch.meteor.com/posts/3xiwnx7ir35hgW3PS
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== ==

Revision as of 08:45, 31 January 2016

One of the major needs identified in existing platforms for crowd-sourcing is the ability of the platform to effectively match capable workers with suitable jobs or HITs (Human Intelligence Tasks). The Stanford Crowd Research Team has thus far developed their Daemo Platform, which makes a significant step in meeting this requirement through the Boomerang Ranking System.

We propose a referral based system that deals with the following reputation and relevant work issues:

  • A problem with a system that prefers assigning tasks to workers with high reputation is that new workers may find it difficult to find good HITs. Requesters would tend to allot jobs to the same set of highly rated users. Similarly, existing workers would tend to take up HITs from the same set of requesters with high ratings.
  • Workers rely on external forums (TurkerNation, Reddit etc) to find good HITs from reliable requesters. Clearly any future crowdsourcing platform should reduce this burden on the worker by allowing dedicated workers to easily share good HITs and help fellow workers to find relevant work .


Referral Network for Workers

Introduction

The employee referral network in the corporate world is known to be a cost and time effective method of recruitment that produces high quality candidates. 92% of the participants in the Global Employee Referral Index 2013 Survey stated that referrals were a top source of recruitment. We thought about adapting the referral system to our crowd sourcing platform design. This would enable workers to recommend or “refer” other workers (existing or new) for good HITs.


Implementation of a Referral Network for Crowdsourcing

We illustrate the use of the referral system through the following example.

Requester R has a HIT to post on the crowdsourcing platform. R can view highly rated workers using Boomerang and make the HIT visible to them (or post the HIT publicly for all to see). Worker W notices the HIT posted by R and has the following options:

Accept the HIT Share the HIT with fellow workers. In the referral based scheme, this can be done in the following ways: W refers workers he or she knows to R. W can publicly offer to refer anyone who is interested in HIT. This is similar to how referrals are shared across social networks like Facebook, Twitter. This referral sharing network can be integrated into the crowdsourcing platform, removing the need for multiple external forums.

The quality of referrals can be incentivized in a number of ways. A rudimentary way would be to include a measure of good referrals in the scores used to rank workers and requesters. A separate index could be used for referrals or requesters may reward good referrals with bonus payments.


Benefits of Referral Network

A HIT initially becomes visible to highly rated workers who have worked with that particular requester in the past. The referral network enables sharing of HITs with other (existing and new) workers who would otherwise have been the last in line to see the HIT. This is especially useful when a requester posts a large number of HITs, which can be shared quickly among workers.