東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Message Propagation and Social Influ...

Narayana, Vishali.

Linked to FindBook

Google Book

Amazon

博客來

Message Propagation and Social Influence in Twitter.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Message Propagation and Social Influence in Twitter./
Author:	Narayana, Vishali.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	104 p.
Notes:	Source: Masters Abstracts International, Volume: 79-12.
Contained By:	Masters Abstracts International79-12.
Subject:	Web Studies. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10608326
ISBN:	9780438044487

Message Propagation and Social Influence in Twitter.
Narayana, Vishali.

Message Propagation and Social Influence in Twitter. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 104 p.

Source: Masters Abstracts International, Volume: 79-12.

Thesis (M.S.)--Oklahoma State University, 2017.

This item must not be sold to any third party vendors.

Twitter data has potentially unlimited value and numerous applications and is known for its increase in users over time. Twitter facilitates information diffusion at an exponential rate and also the creation of networks of users with a common interest. People reacting to the spread of an epidemic or a natural disaster are greatly influenced by the information diffusion in social media. Twitter, being a popular micro-blogging network provides an effective way to measure diffusion in terms of speed and strength. Our research is based on previous work on models related to topic diffusion and user influence. A topic is defined by a set of keywords. This research concentrates on the implementation of algorithms for computation of diffusion of a topic in twitter. The degree of influence of the users who tweet on the topic is also addressed. We have presented two different approaches to compute user influence based on topic potential. We compare two diffusion models proposed in the literature, namely potentials and connections. For testing and empirical analyses we use tweets related to "flu", "food poisoning", and "politics".

ISBN: 9780438044487Subjects--Topical Terms:

1026830
Web Studies.

Message Propagation and Social Influence in Twitter.
LDR:02149nmm a2200325 4500 001 2206081
005 20190828133550.5
008 201008s2017 ||||||||||||||||| ||eng d
020 $a 9780438044487
035 $a (MiAaPQ)AAI10608326
035 $a (MiAaPQ)okstate:15368
035 $a AAI10608326
040 $a MiAaPQ $c MiAaPQ
100 1 $a Narayana, Vishali. $3 3432973
245 1 0 $a Message Propagation and Social Influence in Twitter.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 104 p.
500 $a Source: Masters Abstracts International, Volume: 79-12.
500 $a Publisher info.: Dissertation/Thesis.
500 $a M., George K.
502 $a Thesis (M.S.)--Oklahoma State University, 2017.
506 $a This item must not be sold to any third party vendors.
520 $a Twitter data has potentially unlimited value and numerous applications and is known for its increase in users over time. Twitter facilitates information diffusion at an exponential rate and also the creation of networks of users with a common interest. People reacting to the spread of an epidemic or a natural disaster are greatly influenced by the information diffusion in social media. Twitter, being a popular micro-blogging network provides an effective way to measure diffusion in terms of speed and strength. Our research is based on previous work on models related to topic diffusion and user influence. A topic is defined by a set of keywords. This research concentrates on the implementation of algorithms for computation of diffusion of a topic in twitter. The degree of influence of the users who tweet on the topic is also addressed. We have presented two different approaches to compute user influence based on topic potential. We compare two diffusion models proposed in the literature, namely potentials and connections. For testing and empirical analyses we use tweets related to "flu", "food poisoning", and "politics".
590 $a School code: 0664.
650 4 $a Web Studies. $3 1026830
650 4 $a Computer science. $3 523869
690 $a 0646
690 $a 0984
710 2 $a Oklahoma State University. $b Computer Science. $3 1018596
773 0 $t Masters Abstracts International $g 79-12.
790 $a 0664
791 $a M.S.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10608326