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.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election./
Author:	Kearney, Michael W.
Description:	1 online resource (106 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-04(E), Section: A.
Contained By:	Dissertation Abstracts International79-04A(E).
Subject:	Mass communication. -
Online resource:	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.
LDR:02373ntm a2200373Ki 4500 001 909768
005 20180426091046.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355342895
035 $a (MiAaPQ)AAI10272822
035 $a (MiAaPQ)ku:15182
035 $a AAI10272822
040 $a MiAaPQ $b eng $c MiAaPQ
099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Kearney, Michael W. $3 1180711
245 1 2 $a A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.
264 0 $c 2017
300 $a 1 online resource (106 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-04(E), Section: A.
500 $a Advisers: Mary C. Banwart; Jeff A. Hall.
502 $a Thesis (Ph.D.) $c University of Kansas $d 2017.
504 $a Includes bibliographical references
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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mass communication. $3 1179310
650 4 $a Communication. $3 556422
650 4 $a Political science. $3 558774
650 4 $a Web studies. $3 1148502
655 7 $a Electronic books. $2 local $3 554714
690 $a 0708
690 $a 0459
690 $a 0615
690 $a 0646
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Kansas. $b Communication Studies. $3 1180712
773 0 $t Dissertation Abstracts International $g 79-04A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10272822 $z click for full text (PQDT)