Replication Data for: Estimating the Ideology of YouTube Videos (doi:10.7910/DVN/WZZFTW)

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Document Description

Citation

Title:

Replication Data for: Estimating the Ideology of YouTube Videos

Identification Number:

doi:10.7910/DVN/WZZFTW

Distributor:

Harvard Dataverse

Date of Distribution:

2023-12-11

Version:

1

Bibliographic Citation:

Lai, Angela; Brown, Megan A.; Bisbee, James; Tucker, Joshua A.; Nagler, Jonathan; Bonneau, Richard, 2023, "Replication Data for: Estimating the Ideology of YouTube Videos", https://doi.org/10.7910/DVN/WZZFTW, Harvard Dataverse, V1

Study Description

Citation

Title:

Replication Data for: Estimating the Ideology of YouTube Videos

Identification Number:

doi:10.7910/DVN/WZZFTW

Authoring Entity:

Lai, Angela (New York University)

Brown, Megan A. (New York University)

Bisbee, James (New York University)

Tucker, Joshua A. (New York University)

Nagler, Jonathan (New York University)

Bonneau, Richard (New York University)

Producer:

<i>Political Analysis</i>

Distributor:

Harvard Dataverse

Access Authority:

Lai, Angela

Depositor:

Lai, Angela

Date of Deposit:

2023-03-02

Holdings Information:

https://doi.org/10.7910/DVN/WZZFTW

Study Scope

Keywords:

Social Sciences

Abstract:

Abstract: We present a method for estimating the ideology of political YouTube videos. The subfield of estimating ideology as a latent variable has often focused on traditional actors such as legislators while more recent work has used social media data to estimate the ideology of ordinary users, political elites, and media sources. We build on this work to estimate the ideology of a political YouTube video. First, we start with a matrix of political Reddit posts linking to YouTube videos and apply correspondence analysis to place those videos in an ideological space. Second, we train a language model with those estimated ideologies as training labels, enabling us to estimate the ideologies of videos not posted on Reddit. These predicted ideologies are then validated against human labels. We demonstrate the utility of this method by applying it to the watch histories of survey respondents to evaluate the prevalence of echo chambers on YouTube in addition to the association between video ideology and viewer engagement. Our approach gives video-level scores based only on supplied text metadata, is scalable, and can be easily adjusted to account for changes in the ideological landscape. Keywords: Ideology estimation, YouTube, latent variable This folder contains the replication materials for "Estimating the Ideology of Political YouTube Videos."

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Forthcoming, Political Analysis

Bibliographic Citation:

Forthcoming, Political Analysis

Other Study-Related Materials

Label:

youtube_ideology.tar.gz

Notes:

application/x-gzip

Other Study-Related Materials

Label:

YTI_ReadMe.pdf

Notes:

application/pdf