Supplementary materials for: "Comparing Internet experiences and prosociality in Amazon Mechanical Turk and population-based survey samples"

  • Eszter Hargittai ((University of Zurich) (Creator)
  • Aaron Shaw ((Northwestern University) (Creator)
  • Aaron Shaw (Contributor)

Dataset

Description

Overview Supplementary materials for the paper "Comparing Internet experiences and prosociality in Amazon Mechanical Turk and population-based survey samples" by Eszter Hargittai and Aaron Shaw published in Socius in 2020 (https://doi.org/10.1177/2378023119889834). License The materials provided here are issued under the same (Creative Commons Attribution Non-Commercial 4.0) license as the paper. Details and a copy of the license are available at: http://creativecommons.org/licenses/by-nc/4.0/. Manifest The files included are: Hargittai-Shaw-AMT-NORC-2019.rds and Hargittai-Shaw-AMT-NORC-2019.tsv: Two (identical) versions the dataset used for the analysis. The tsv file is provided to facilitate import into software other than R. R analysis code files: 01-import.R - Imports dataset. Creates a mapping of dependent variables and variable names used elsewhere in the figure and analysis. 02-gen_figure.R - Generates Figure 1 in PDF and PNG formats and saves them in the "figures" directory. 03-gendescriptivestats.R - Generates results reported in Table 1. 04-gen_models.R - Fits models reported in Tables 2-4. 05-alternative_specifications.R - Fits models using log-transformed version of the income variable. Makefile: Executes all of the R files in sequence, produces corresponding .log files in the "log" directory that contain the full R session from each file as well as separate error log files (also in the "log" directory) that capture any error messages and warnings generated by R along the way. HargittaiShaw2019Socius-Instrument.pdf: The questions distributed to both the NORC and AMT survey participants used in the analysis reported in this paper. How to reproduce the analysis presented in the paper Depending on your computing environment, reproducing the analysis presented in the paper may be as easy as invoking "make all" or "make" in the directory containing this file on a system that has the appropriate software installed. Once compilation is complete, you can review the log files in a text editor. See below for more on software and dependencies. If calling the makefile fails, the individual R scripts can also be run interactively or in batch mode. Software and dependencies The R and compilation materials provided here were created and tested on a 64-bit laptop pc running Ubuntu 18.04.3 LTS, R version 3.6.1, ggplot2 version 3.2.1, reshape2 version 1.4.3, forcats version 0.4.0, pscl version 1.5.2, and stargazer version 5.2.2 (these last five are R packages called in specific .R files). As with all software, your mileage may vary and the authors provide no warranties. Codebook The dataset consists of 36 variables (columns) and 2,716 participants (rows). The variable names and brief descriptions follow below. Additional details of measurement are provided in the paper and survey instrument. All dichotomous indicators are coded 0/1 where 1 is the affirmative response implied by the variable name: id: Index to identify individual units (participants). svy_raked_wgt: Raked survey weights provided by NORC. amtsample: Data source coded 0 (NORC) or 1 (AMT). age: Participant age in years. female: Participant selected "female" gender. incomecont: Income in USD (continuous) coded from center-points of categories reported in the instruments. incomediv: Income in $1,000s USD (=incomecont/1000). incomesqrt: Square-root of incomecont. lincome: Natural logarithm of incomecont. rural: Participant resides in a rural area. employed: Participant is fully or partially employed. eduhsorless: Highest education level is high school or less. edusc: Highest education level is completed some college. edubaormore: Highest education level is BA or more. white: Race = white. black: Race = black. nativeam: Race = native american. hispanic: Ethnicity = hispanic. asian: Race = asian. raceother: Race = other. skillsmean: Internet use skills index (described in paper). accesssum: Internet use autonomy (described in paper). webweekhrs: Internet use frequency (described in paper). do_sum: Participatory online activities (described in paper). snssumcompare: Social network site activities (described in paper). altru_scale: Generous behaviors (described in paper). trust_scale: Trust scale score (described in paper). pts_give: Points donated in unilateral dictator game (described in paper). std_accesssum: Standardized (z-score) version of accesssum. std_webweekhrs: Standardized (z-score) version of webweekhrs. std_skillsmean: Standardized (z-score) version of skillsmean. std_do_sum: Standardized (z-score) version of do_sum. std_snssumcompare: Standardized (z-score) version of snssumcompare. std_trust_scale: Standardized (z-score) version of trust_scale. std_altru_scale: Standardized (z-score) version of altru_scale. std_pts_give: Standardized (z-score) version of pts_give.
Date made available2020
PublisherHarvard Dataverse

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