ARL crowd sourcing

PROJECT

Url:N/A
Start date: 2011/09/01
End date: 2013/09/01
Infrastructure: Amazon mechanical turk

TEAM

Official team page:
Leader:




PROJECT DEFINITION

Subject

Engineering and technology > (other)

Description

Crowdsourcing is an increasingly popular technique used to complete complex tasks or collect large amounts of data. This report documents the effort to employ crowdsourcing using the Mechanical Turk service hosted by Amazon. The task was to collect labeling data on several thousands of short videos clips as such labels would be perceived by a human. The approach proved to be viable, collecting large amounts of data in a relatively short time frame, but required specific considerations for the population of workers and impersonal medium through which data were collected.

Purpose.

According to Pierce & Fung (2013), The goal of this project is to generate a large number of video vignettes meant to visually demonstrate specific verbs. The project called for 48 verbs to be demonstrated,each in 10 different exemplars. Each exemplar was filmed with 16 different setting variations, consisting of different backgrounds, camera angle, time of day,etc. This produces a total of 7680 vignettes. The vignettes are to be data points provided to system design teams as part of a larger research and development project This project included 6 variants (sub-projects) described in the Pierce & Fung, 2013 report.

Research question.

unknown

ABOUT PARTICIPANT TASKS

Tasks description.

Recognition Task: Crowdsourced Study subproject For each task, also known as a stimulus, a vignette was displayed along with a verb question (“Do you see [verb] ?”) and the verb definition. Workers responded to a single verb question with a present/absent judgment

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Grey typology Participation typology Contribution type:
Computing: NO Thinking: YES
Sensing: Somewhat Gaming: NO
Crowdsourcing ☑ Distributed intelligence ☐
Participatory science ☐ Extreme citizen science ☐
Science outreach ☐
Data collection ☑
Data analysis ☐
Data interpretation ☐--------
Gaming
Genre: Gaming elements: other
Interface
Data type to manipulate: pictures, text interface enjoyment: somewhat cool/attractive
Interface usability: rather easy to use		 Member profiles::N/A
Member profile elements:


ABOUT GUIDANCE AND FEEDBACK

Guidance Feedback on
Tutorial and documentation: SOMEWHAT
Training sequence: SOMEWHAT
Peer to peer guidance: SOMEWHAT
individual performance: Somewhat
collective performance: Somewhat
research progress: Somewhat

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COMMUNITY

Tools News & Events

Communication:
Social Network: N/A

Main news site:
Frequency of project news updates: N/A
Type of events:
Frequency of events :

Community description

Community size (volounteers based):
Role: Interaction form:
Has official community manager(s): N/A
 Has team work N/A

Other information about community:
Community led additions: 2013/09/01

OTHER PROJECT INFORMATION



No [[has completion level::Low]




No

Engineering and technology other [[Has project purpose::According to Pierce & Fung (2013), The goal of this project is to generate a large number of video vignettes meant to visually demonstrate specific verbs. The project called for 48 verbs to be demonstrated,each in 10 different exemplars. Each exemplar was filmed with 16 different setting variations, consisting of different backgrounds, camera angle, time of day,etc. This produces a total of 7680 vignettes. The vignettes are to be data points provided to system design teams as part of a larger research and development project

This project included 6 variants (sub-projects) described in the Pierce & Fung, 2013 report.]] unknown USA Crowd Sourcing Data Collection through Amazon Mechanical Turk [[Has participant task description::Recognition Task: Crowdsourced Study subproject

For each task, also known as a stimulus, a vignette was displayed along with a verb question (“Do you see [verb] ?”) and the verb definition. Workers responded to a single verb question with a present/absent judgment]] data collection Revenue crowdsourcing pictures, text, other: Thinking: yes Computing: no Sensing: somewhat Gaming: no other


somewhat cool/attractive rather easy to use N/A N/A N/A N/A N/A N/A

N/A

N/A

N/A



N/A


N/A


Low



BIBLIOGRAPHY


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