Cable news channels' partisan ideology and market share growth as predictors of social distancing sentiment during the COVID-19 pandemic

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Original language	English
Title of host publication	Semantic Network Analysis in Social Sciences
Publisher	Taylor and Francis
Pages	72-93
Number of pages	22
ISBN (Electronic)	9781000471885
ISBN (Print)	9780367636524
DOIs	https://doi.org/10.4324/9781003120100-5
State	Published - Nov 30 2021

ASJC Scopus subject areas

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title = "Cable news channels' partisan ideology and market share growth as predictors of social distancing sentiment during the COVID-19 pandemic",

author = "Danowski, \{James A.\} and Bei Yan and Ken Riopelle",

year = "2021",

month = nov,

day = "30",

doi = "10.4324/9781003120100-5",

language = "English",

isbn = "9780367636524",

pages = "72--93",

booktitle = "Semantic Network Analysis in Social Sciences",

publisher = "Taylor and Francis",

}

TY - CHAP

T1 - Cable news channels' partisan ideology and market share growth as predictors of social distancing sentiment during the COVID-19 pandemic

AU - Danowski, James A.

AU - Yan, Bei

AU - Riopelle, Ken

PY - 2021/11/30

Y1 - 2021/11/30

UR - https://www.scopus.com/pages/publications/85126579316

UR - https://www.scopus.com/pages/publications/85126579316#tab=citedBy

U2 - 10.4324/9781003120100-5

DO - 10.4324/9781003120100-5

M3 - Chapter

SN - 9780367636524

SP - 72

EP - 93

BT - Semantic Network Analysis in Social Sciences

PB - Taylor and Francis

ER -