語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Practical Social Network Analysis wi...
~
Mohan, Ankith.
Practical Social Network Analysis with Python
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Practical Social Network Analysis with Python/ by Krishna Raj P.M., Ankith Mohan, K.G. Srinivasa.
作者:
Raj P.M., Krishna.
其他作者:
Mohan, Ankith.
面頁冊數:
XXXI, 329 p. 186 illus., 73 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Computer communication systems. -
電子資源:
https://doi.org/10.1007/978-3-319-96746-2
ISBN:
9783319967462
Practical Social Network Analysis with Python
Raj P.M., Krishna.
Practical Social Network Analysis with Python
[electronic resource] /by Krishna Raj P.M., Ankith Mohan, K.G. Srinivasa. - 1st ed. 2018. - XXXI, 329 p. 186 illus., 73 illus. in color.online resource. - Computer Communications and Networks,1617-7975. - Computer Communications and Networks,.
Chapter 1. Basics of Graph Theory -- Chapter 2. Graph Structure of the Web -- Chapter 3. Random Graph Models -- Chapter 4. Small World Phenomena -- Chapter 5. Graph Structure of Facebook -- Chapter 6. Peer-To-Peer Networks -- Chapter 7. Signed Networks -- Chapter 8. Cascading in Social Networks -- Chapter 9. Influence Maximisation -- Chapter 10. Outbreak Detection -- Chapter 11. Power Law -- Chapter 12. Kronecker Graphs -- Chapter 13. Link Analysis -- Chapter 14. Community Detection -- Chapter 15. Representation Learning on Graph.
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
ISBN: 9783319967462
Standard No.: 10.1007/978-3-319-96746-2doiSubjects--Topical Terms:
1115394
Computer communication systems.
LC Class. No.: TK5105.5-5105.9
Dewey Class. No.: 004.6
Practical Social Network Analysis with Python
LDR
:03339nam a22004095i 4500
001
991311
003
DE-He213
005
20200701213605.0
007
cr nn 008mamaa
008
201225s2018 gw | s |||| 0|eng d
020
$a
9783319967462
$9
978-3-319-96746-2
024
7
$a
10.1007/978-3-319-96746-2
$2
doi
035
$a
978-3-319-96746-2
050
4
$a
TK5105.5-5105.9
072
7
$a
UKN
$2
bicssc
072
7
$a
COM075000
$2
bisacsh
072
7
$a
UKN
$2
thema
082
0 4
$a
004.6
$2
23
100
1
$a
Raj P.M., Krishna.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1282966
245
1 0
$a
Practical Social Network Analysis with Python
$h
[electronic resource] /
$c
by Krishna Raj P.M., Ankith Mohan, K.G. Srinivasa.
250
$a
1st ed. 2018.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
XXXI, 329 p. 186 illus., 73 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Computer Communications and Networks,
$x
1617-7975
505
0
$a
Chapter 1. Basics of Graph Theory -- Chapter 2. Graph Structure of the Web -- Chapter 3. Random Graph Models -- Chapter 4. Small World Phenomena -- Chapter 5. Graph Structure of Facebook -- Chapter 6. Peer-To-Peer Networks -- Chapter 7. Signed Networks -- Chapter 8. Cascading in Social Networks -- Chapter 9. Influence Maximisation -- Chapter 10. Outbreak Detection -- Chapter 11. Power Law -- Chapter 12. Kronecker Graphs -- Chapter 13. Link Analysis -- Chapter 14. Community Detection -- Chapter 15. Representation Learning on Graph.
520
$a
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
650
0
$a
Computer communication systems.
$3
1115394
650
0
$a
Python (Computer program language).
$3
1127623
650
1 4
$a
Computer Communication Networks.
$3
669310
650
2 4
$a
Python.
$3
1115944
700
1
$a
Mohan, Ankith.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1208246
700
1
$a
Srinivasa, K.G.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1066320
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783319967455
776
0 8
$i
Printed edition:
$z
9783319967479
776
0 8
$i
Printed edition:
$z
9783030072414
830
0
$a
Computer Communications and Networks,
$x
1617-7975
$3
1255420
856
4 0
$u
https://doi.org/10.1007/978-3-319-96746-2
912
$a
ZDB-2-SCS
912
$a
ZDB-2-SXCS
950
$a
Computer Science (SpringerNature-11645)
950
$a
Computer Science (R0) (SpringerNature-43710)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入