東華大學圖書館 |

語系: 繁體中文

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

Visual Persuasion in Mass Media: A C...

Joo, Jungseock.

FindBook

Google Book

Amazon

博客來

Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication./
作者:	Joo, Jungseock.
面頁冊數:	115 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-02(E), Section: B.
Contained By:	Dissertation Abstracts International77-02B(E).
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3725041
ISBN:	9781339089270

Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication.
Joo, Jungseock.

Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication. - 115 p.

Source: Dissertation Abstracts International, Volume: 77-02(E), Section: B.

Thesis (Ph.D.)--University of California, Los Angeles, 2015.

This item is not available from ProQuest Dissertations & Theses.

Visuals play a vital role in human communication in the modern media landscape, but there have been little progress on a systematic analysis on massive visual data. In this dissertation, I introduce a novel computational paradigm that brings advanced techniques in computer vision and machine learning to bear on research questions in media studies and social science.

ISBN: 9781339089270Subjects--Topical Terms:

523869
Computer science.

Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication.
LDR:02562nmm a2200325 4500 001 2074643
005 20160930093717.5
008 170521s2015 ||||||||||||||||| ||eng d
020 $a 9781339089270
035 $a (MiAaPQ)AAI3725041
035 $a AAI3725041
040 $a MiAaPQ $c MiAaPQ
100 1 $a Joo, Jungseock. $3 3189976
245 1 0 $a Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication.
300 $a 115 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-02(E), Section: B.
500 $a Adviser: Song-Chun Zhu.
502 $a Thesis (Ph.D.)--University of California, Los Angeles, 2015.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a Visuals play a vital role in human communication in the modern media landscape, but there have been little progress on a systematic analysis on massive visual data. In this dissertation, I introduce a novel computational paradigm that brings advanced techniques in computer vision and machine learning to bear on research questions in media studies and social science.
520 $a I first examine how the news media leverage photographs to visually persuade their audiences. I developed a computational model that can predict the viewers' emotional perceptions from politicians' photographs in the mass media---by inferring hidden messages and communicative intents embodied in images. I applied the model to track the visual favorability of the U.S. President in the mass media, revealing strong correlations between the visuals from the mass media and the public opinion. Secondly, I investigate the role of facial appearance in social perception and trait inference and its impacts to real-world social events such as elections. The result shows that the automated trait recognition from the facial appearance of politicians predicts the major election outcomes in the U.S. up to 70% accuracy.
520 $a These approaches extend existing theories and behavioral studies to large-scale analysis, demonstrate the utility of computer vision and machine learning as novel research tools in computational communication science, and suggest a new area of research for computer vision, which goes beyond traditional syntactical scene understanding.
590 $a School code: 0031.
650 4 $a Computer science. $3 523869
650 4 $a Statistics. $3 517247
650 4 $a Mass communication. $3 2144804
690 $a 0984
690 $a 0463
690 $a 0708
710 2 $a University of California, Los Angeles. $b Computer Science 0201. $3 2049859
773 0 $t Dissertation Abstracts International $g 77-02B(E).
790 $a 0031
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3725041