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Permanent URI for this collectionhttps://www.weizenbaum-library.de/handle/id/977

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    Reproduction Material for: Whose ideas are worth spreading? The representation of women and ethnic groups in TED talks
    (Harvard Dataverse, 2019-07-12) Schwemmer, Carsten
    This repository contains replication data for "Whose ideas are worth spreading? The representation of women and ethnic groups in TED talks". (2009-07-12)
    #### Readme The R code for all analysis is included in the file "ted_talks_analysis_replication.Rmd". An html version of the analysis including output is available in file "ted_talks_analysis_replication.html" The remaining files are either figures, UTF-8 encoded and tab-delimited datasets (original format .tsv, dataverse format .tab), or R objects (ending with .RData). Please consider that data for TED talks is licensed under a Creative Commons License by TED. The Python code for collecting the data from TED and the image recognition service is not included in this repository. Unfortunately the TED website already changed since the time of data collection, and the code therefore does not work anymore. In case you have any questions about the replication material, feel free to contact me at c.schwem2er@gmail.com
    #### File list - readme.txt - ted_main_dataset.tsv - ted_ready_for_analysis.RData - ted_talks_analysis_replication.html - ted_talks_analysis_replication.Rmd - ted_talks_validation.tsv - ted_yt-comments_sentiment.tsv - ted_yt-comments.tsv - figures/figure2.pdf - figures/figure2.png - figures/figure3.pdf - figures/figure3.png - figures/figure4.pdf - figures/figure4.png - figures/supporting_information_figure1.png - figures/supporting_information_figure2.png - figures/supporting_information_figure3.png - figures/supporting_information_figure4.png - figures/supporting_information_figure5.png
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    Supplemental material: “Whose ideas are worth spreading? The representation of women and ethnic groups in TED talks”
    (2019) Schwemmer, Carsten; Jungkunz, Sebastian
    S1 Image recognition algorithm S2 Topic modeling S3 Regressions References