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

Texts
Meta-documents
Project Overview
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 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 maps at three grain sizes: the whole corpus; posts organized into five tiers based on compensation level; specific productive terms. Findings identify coherent human aspects that collapse distinctions between bodily and intellectual capabilities, yet the separation between humans and non-humans is indistinct, because MTurk posts repeatedly redraw such boundaries, causing characteristic traits to be variably shared.
Drafts
Resources
Resource Collections
Single Resources
Image FCM unweighted
Image Unweighted FCM diagram for "readable" and its inflections
Image Weighted FCM diagram for "opinion" and its inflections
Image FCM weighted
Video Episode 1 (3-22-19)
Image Unweighted bigram network graph for "attitude" and its inflections
Image Bigram network graph unweighted
Video Episode 3 (6-18-19)
Video Episode 2 with Dr. Jeff Rice (5-14-19)
Image Weighted bigram network graph for "feel" and its inflections