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Follow on Google News | New Model for Better Predicting Presidential Election Outcomes Based on Single-Show TV ViewershipIn the article entitled "Predicting Presidential Election Outcomes from What People Watch? (http://online.liebertpub.com/ Arash Barfar, PhD, University of Nevada, Reno, and Balaji Padmanabhan, PhD, University of South Florida, Tampa, explore the use of predictive models built on Nielsen national watch data for both partisan and non-partisan television shows. They analyzed the model using data from the 2012 presidential election and then applied it to viewership information gathered during the 2016 presidential primaries. The researchers discuss the practical implications of their findings for campaigns and the media, and how political parties might be able to use this model to target certain shows with specific messaging. "Bias in polling data can be difficult to detect in cases of highly infrequent outcomes such as a presidential election (http://www.marketwatch.com/ About the Journal Big Data (http://www.liebertpub.com/ About the Publisher Mary Ann Liebert, Inc., publishers (http://www.liebertpub.com/) for establishing authoritative medical and biomedical peer-reviewed journals, including OMICS: A Journal of Integrative Biology, Journal of Computational Biology, New Space, and 3D Printing and Additive Manufacturing. Its biotechnology trade magazine, GEN (Genetic Engineering & Biotechnology News), was the first in its field and is today the industry's most widely read publication worldwide. A complete list of the firm's more than 80 journals, newsmagazines, and books is available on the Mary Ann Liebert, Inc., publishers (http://www.liebertpub.com/) End
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