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Restoring Public Trust in Digital Platform Operations: Machine Learning Algorithmic Structuring of Social Media Content

Restoring Public Trust in Digital Platform Operations: Machine Learning Algorithmic Structuring... I develop a conceptual framework based on a systematic and comprehensive literature review on public trust in digital platform operations. Building my argument by drawing on data collected from Pew Research Center, I performed analyses and made estimates regarding machine learning algorithmic structuring of social media content. The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 4,700 respondents. Keywords: public trust; digital platform; machine learning; algorithm; social media http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Contemporary Philosophy Addleton Academic Publishers

Restoring Public Trust in Digital Platform Operations: Machine Learning Algorithmic Structuring of Social Media Content

Nela Mircică
Review of Contemporary Philosophy , Volume 19 (1): 7 – Jun 12, 2020
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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1841-5261
eISSN
2471-089X
Publisher site
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Abstract

I develop a conceptual framework based on a systematic and comprehensive literature review on public trust in digital platform operations. Building my argument by drawing on data collected from Pew Research Center, I performed analyses and made estimates regarding machine learning algorithmic structuring of social media content. The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 4,700 respondents. Keywords: public trust; digital platform; machine learning; algorithm; social media

Journal

Review of Contemporary Philosophy – Addleton Academic Publishers

Published: Jun 12, 2020

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