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
Python for graph and network analysis
~
Al-Taie, Mohammed Zuhair.
FindBook
Google Book
Amazon
博客來
Python for graph and network analysis
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Python for graph and network analysis/ by Mohammed Zuhair Al-Taie, Seifedine Kadry.
作者:
Al-Taie, Mohammed Zuhair.
其他作者:
Kadry, Seifedine.
出版者:
Cham :Springer International Publishing : : 2017.,
面頁冊數:
xiii, 203 p. :ill., digital ;24 cm.
內容註:
Theoretical Concepts of Network Analysis -- Network Basics -- Graph Theory -- Social Networks -- Node-Level Analysis -- Group-Level Analysis -- Network-Level Analysis -- Information Diffusion in Social Networks -- Appendix A: Python Tutorial -- Appendix B: NetworkX Tutorial.
Contained By:
Springer eBooks
標題:
Python (Computer program language) -
電子資源:
http://dx.doi.org/10.1007/978-3-319-53004-8
ISBN:
9783319530048
Python for graph and network analysis
Al-Taie, Mohammed Zuhair.
Python for graph and network analysis
[electronic resource] /by Mohammed Zuhair Al-Taie, Seifedine Kadry. - Cham :Springer International Publishing :2017. - xiii, 203 p. :ill., digital ;24 cm. - Advanced information and knowledge processing,1610-3947. - Advanced information and knowledge processing..
Theoretical Concepts of Network Analysis -- Network Basics -- Graph Theory -- Social Networks -- Node-Level Analysis -- Group-Level Analysis -- Network-Level Analysis -- Information Diffusion in Social Networks -- Appendix A: Python Tutorial -- Appendix B: NetworkX Tutorial.
This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications.
ISBN: 9783319530048
Standard No.: 10.1007/978-3-319-53004-8doiSubjects--Topical Terms:
729789
Python (Computer program language)
LC Class. No.: QA76.73.P98
Dewey Class. No.: 005.133
Python for graph and network analysis
LDR
:02572nmm a2200325 a 4500
001
2092572
003
DE-He213
005
20170320102207.0
006
m d
007
cr nn 008maaau
008
171117s2017 gw s 0 eng d
020
$a
9783319530048
$q
(electronic bk.)
020
$a
9783319530031
$q
(paper)
024
7
$a
10.1007/978-3-319-53004-8
$2
doi
035
$a
978-3-319-53004-8
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.73.P98
072
7
$a
UYD
$2
bicssc
072
7
$a
COM074000
$2
bisacsh
082
0 4
$a
005.133
$2
23
090
$a
QA76.73.P98
$b
A316 2017
100
1
$a
Al-Taie, Mohammed Zuhair.
$3
3226541
245
1 0
$a
Python for graph and network analysis
$h
[electronic resource] /
$c
by Mohammed Zuhair Al-Taie, Seifedine Kadry.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2017.
300
$a
xiii, 203 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Advanced information and knowledge processing,
$x
1610-3947
505
0
$a
Theoretical Concepts of Network Analysis -- Network Basics -- Graph Theory -- Social Networks -- Node-Level Analysis -- Group-Level Analysis -- Network-Level Analysis -- Information Diffusion in Social Networks -- Appendix A: Python Tutorial -- Appendix B: NetworkX Tutorial.
520
$a
This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications.
650
0
$a
Python (Computer program language)
$3
729789
650
0
$a
Graph theory
$x
Data processing.
$3
655277
650
0
$a
Quantitative research.
$3
919734
650
0
$a
Online social networks
$x
Data processing.
$3
3226542
650
1 4
$a
Computer Science.
$3
626642
650
2 4
$a
System Performance and Evaluation.
$3
891353
650
2 4
$a
Computer Appl. in Social and Behavioral Sciences.
$3
892702
650
2 4
$a
Information Systems Applications (incl. Internet)
$3
1565452
650
2 4
$a
Python.
$3
3201289
700
1
$a
Kadry, Seifedine.
$3
2132942
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Advanced information and knowledge processing.
$3
1568369
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-53004-8
950
$a
Computer Science (Springer-11645)
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
W9316946
電子資源
11.線上閱覽_V
電子書
EB QA76.73.P98
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