國立虎尾科技大學 |

A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election./
作者:	Kearney, Michael W.
面頁冊數:	1 online resource (106 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-04(E), Section: A.
Contained By:	Dissertation Abstracts International79-04A(E).
標題:	Mass communication. -
電子資源:	click for full text (PQDT)
ISBN:	9780355342895

A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.
Kearney, Michael W.

A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election. - 1 online resource (106 pages)

Source: Dissertation Abstracts International, Volume: 79-04(E), Section: A.

Thesis (Ph.D.)

Includes bibliographical references

Communication and media research lacks an accessible and systematic approach to measuring political partisanship in decentralized media environments. In this dissertation, a network-based measurement of partisanship is proposed and then used to analyze social media users during a highly contentious general election. Study I (Chapter 2) introduces rtweet, a newly developed open-source software package designed to collect Twitter data. Study II (Chapter 3) then uses rtweet to gather publicly available Twitter data and demonstrate a network-based approach to estimating partisanship. Finally, Study 3 (Chapter 4) extends this network-based approach to analyze change over time in network polarization among partisan and non-partisan users during the 2016 general election. Results showcase the range and validity of network-based estimates of partisanship and provide clear evidence of partisan selective exposure and network polarization on Twitter as proximity to the election increases.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355342895Subjects--Topical Terms:

1179310
Mass communication.
Index Terms--Genre/Form:

554714
Electronic books.

A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.
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520 $a Communication and media research lacks an accessible and systematic approach to measuring political partisanship in decentralized media environments. In this dissertation, a network-based measurement of partisanship is proposed and then used to analyze social media users during a highly contentious general election. Study I (Chapter 2) introduces rtweet, a newly developed open-source software package designed to collect Twitter data. Study II (Chapter 3) then uses rtweet to gather publicly available Twitter data and demonstrate a network-based approach to estimating partisanship. Finally, Study 3 (Chapter 4) extends this network-based approach to analyze change over time in network polarization among partisan and non-partisan users during the 2016 general election. Results showcase the range and validity of network-based estimates of partisanship and provide clear evidence of partisan selective exposure and network polarization on Twitter as proximity to the election increases.
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