Jsilver Reputation ideas

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Revision as of 23:01, 3 August 2015 by Jsilver (Talk | contribs) (End-of-task Itemized Rating (Applicable to worker and client))

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Reputation Ideas by Jsilver

I will post a collection of reputation ideas (among other ideas) that have been scattered in my mind and notes since January 2015 and even much prior, based on my experience (as a worker, team manager, client) particularly in oDesk since 2012. I've shared them countless times here on Slack (publicly and privately), Meteor, and Wikis.

Acronyms used:

RS= Reputation system

End-of-task Itemized Rating (Applicable to worker and client)

  • A client would rate a worker based on skills used in a particular task and based on other criteria (domains quality of work; communication/responsiveness; cooperation and work ethics/professionalism, deadline/turnaround; efficiency (like cost and time); and accuracy/consistency). This RS is not perfect but would reflect a rating for each skill used in a task or project, rather than the typical "limited-view" 5-star rating. This is essential so that future clients would not bet blind on such a worker; If done in conjunction with interviewing the worker and checking the worker's job history, the client would have a very good idea of the worker's skills and experiences.

On the other hand, a worker could rate a client based on that 6-domain criteria above plus another criteria: knowledge of task. (criteria mentioned here may not be accurate nor final)

As the platform evolves, it would have a substantial collection of rating data from workers and clients. By then, each worker would have worked with many clients and vice versa. If necessary, the platform would be able to put more weight on ratings given by skilled clients/workers (those who are able to rate workers/clients more accurately/honestly than others).

Implicit signals (Applicable to worker and client)

  • Rating is done during job application evaluation phase. This is a great way of providing reputation coverage throughout the worker (and client) population. I believe this could be implemented much easier than other reputation systems. See [1]