Following Mechanical Turks
Articulating the Human in "Human Intelligence Tasks"

Texts
Meta-documents
Project Overview
by Dr. Jeremy Tirrell, Dr. Nathaniel RiversProject Credits
by Dr. Jeremy Tirrell, Dr. Nathaniel Rivers
Research Products
Tracing the Human in Amazon Mechanical Turk through Rhetorical Text Mining
by Dr. Jeremy Tirrell, Dr. Nathaniel RiversThis study uses text mining to examine how the language of posts on Amazon’s Mechanical Turk (MTurk), an online global crowdsource marketplace, rhetorically articulates a model of the human that emerges from concrete labor acts rather than abstract moral or ethical capacities. The study analyzes 23,105 documents using multiple operations including weighted frequency counts, clusters and topic models, and frequency co-occurrence and n-gram diagrams at three grain sizes: the whole corpus, posts organized into five tiers based on compensation level, and specific term associations. Findings identify coherent human practices that collapse bodily and intellectual capabilities, but a uniform distinction between humans and non-humans is unresolved, because MTurk posts repeatedly redraw such boundaries, causing characteristic traits to be variably shared.
Drafts
Surveying Rhetorical Readability on Amazon Mechanical Turk
by Dr. Jeremy Tirrell, Dr. Nathaniel RiversThis is the working draft of the second research project
Resources
Resource Collections
Single Resources
Image A 1980s reconstruction of the original Mechanical Turk
Pdf A sample compensation keyness diagrams
Image Bigram network graph unweighted
Image Bigram network graph weighted
Video Computers and Composition Conference Talk (6-22-19)
Image Cookie Theft Picture
Video Dr. Casey Boyle on distinctions emerging from interactions
Video Dr. Casey Boyle on the name “Mechanical Turk”
Video Dr. Casey Boyle on the variable roles for humans and non-humans when producing readability
Video Dr. James. J. Brown, Jr. on labor realignments in MTurk