CMU Crowdsourcing Lunch Seminar: Panos Ipeirotis


Title: Focused Crowdsourcing with a Billion (Potential) Customers

Speaker: Panos Ipeirotis, Professor in Division of Data, Operations,
and Administration Sciences at NYU Stern Faculty of Enterprise

Date: April 10, 2018

Time: 12:00-1:00pm

Room: Gates-Hillman Complicated 6501


We describe Quizz, a gamified crowdsourcing system that concurrently

assesses the data of customers and acquires new data from them.

Quizz operates by asking customers to finish brief quizzes on particular

subjects; as a person solutions the quiz questions, Quizz estimates the

person’s competence. To amass new data, Quizz additionally incorporates

questions for which we would not have a recognized reply; the solutions given

by competent customers present helpful indicators for choosing the proper

solutions for these questions. Quizz actively tries to establish

educated customers on the Web by working promoting campaigns,

successfully leveraging “without cost” the focusing on capabilities of

current, publicly accessible, advert placement providers. Quizz quantifies

the contributions of the customers utilizing data principle and sends

suggestions to the promoting system about every person. The suggestions

permits the advert focusing on mechanism to additional optimize advert placement.

Our experiments, which contain over ten thousand customers, verify that

we will crowdsource data curation for area of interest and specialised

subjects, because the promoting community can robotically establish customers

with the specified experience and curiosity within the given subject. We current

managed experiments that look at the impact of assorted incentive

mechanisms, highlighting the necessity for having short-term rewards as

objectives, which incentivize the customers to contribute. Lastly, our

cost-quality evaluation signifies that the price of our method is beneath

that of hiring employees by paid-crowdsourcing platforms, whereas

providing the extra benefit of giving entry to billions of

potential customers everywhere in the planet, and with the ability to attain customers

with specialised experience that isn’t sometimes accessible by

current labor marketplaces.


Panos Ipeirotis is a Professor and George A. Kellner School Fellow at

the Division of Data, Operations, and Administration Sciences at

Leonard N. Stern Faculty of Enterprise of New York College. He

acquired his Ph.D. diploma in Pc Science from Columbia College

in 2004. He has acquired 9 “Finest Paper” awards and nominations and

is the recipient of the 2015 Lagrange Prize, for his contributions within the

area of social media, user-generated content material, and crowdsourcing.

Discover out extra about Panos Ipeirotis at


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