語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
A Network-Based Approach to Estimati...
~
Kearney, Michael W.
FindBook
Google Book
Amazon
博客來
A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.
紀錄類型:
書目-電子資源 : 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.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
106 p.
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:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10272822
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.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 106 p.
Source: Dissertation Abstracts International, Volume: 79-04(E), Section: A.
Thesis (Ph.D.)--University of Kansas, 2017.
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.
ISBN: 9780355342895Subjects--Topical Terms:
2144804
Mass communication.
A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.
LDR
:02036nmm a2200325 4500
001
2155407
005
20180426091046.5
008
190424s2017 ||||||||||||||||| ||eng d
020
$a
9780355342895
035
$a
(MiAaPQ)AAI10272822
035
$a
(MiAaPQ)ku:15182
035
$a
AAI10272822
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Kearney, Michael W.
$3
3343145
245
1 2
$a
A Network-Based Approach to Estimating Partisanship and Analyzing Change in Polarization During the 2016 General Election.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2017
300
$a
106 p.
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.)--University of Kansas, 2017.
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.
590
$a
School code: 0099.
650
4
$a
Mass communication.
$3
2144804
650
4
$a
Communication.
$3
524709
650
4
$a
Political science.
$3
528916
650
4
$a
Web studies.
$3
2122754
690
$a
0708
690
$a
0459
690
$a
0615
690
$a
0646
710
2
$a
University of Kansas.
$b
Communication Studies.
$3
1020359
773
0
$t
Dissertation Abstracts International
$g
79-04A(E).
790
$a
0099
791
$a
Ph.D.
792
$a
2017
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10272822
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9354954
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入