Information and influence propagation in social networks:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
[San Rafael]
Morgan & Claypool
2014
|
| Schriftenreihe: | Synthesis lectures on data management
37 |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027023649&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Printed version of a work that appears in the "Synthesis Digital Library of Engineering and Computer Science" |
| Umfang: | XV, 161 S. graph. Darst. |
| ISBN: | 9781627051156 |
Internformat
MARC
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| 245 | 1 | 0 | |a Information and influence propagation in social networks |c Wei Chen ; Laks V. S. Lakshmanan ; Carlos Castillo |
| 264 | 1 | |a [San Rafael] |b Morgan & Claypool |c 2014 | |
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| 500 | |a Printed version of a work that appears in the "Synthesis Digital Library of Engineering and Computer Science" | ||
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Datensatz im Suchindex
| _version_ | 1820960122689552384 |
|---|---|
| adam_text |
Xl
Contents
:
:· :
:
Acknowledgments
.xv
1
Introduction
.1
1.1
Social Networks and Social Influence
.1
1.1.1
Examples of Social Networks
.1
1.1.2
Examples
ofinformation
Propagation
.2
1.2
Social Influence Examples
.2
1.3
Social Influence Analysis Applications
.4
1.4
The Flip Side
.5
1.5
Outline of This Book
.6
2
Stochastic Diffusion Models
.9
2.1
Main Progressive Models
.10
2.1.1
Independent Cascade Model
.10
2.1.2
Linear Threshold Model
.15
2.1.3
Submodularity and
Monotonicity
of Influence Spread Function
.19
2.1.4
General Threshold Model and General Cascade Model
.20
2.2
Other Related Models
.25
2.2.1
Epidemic Models
.25
2.2.2
Voter Model
.29
2.2.3
Markov Random Field Model
.30
2.2.4
Percolation Theory
.32
3
Influence Maximization
.35
3.1
Complexity of Influence Maximization
.36
3.2
Greedy Approach to Influence Maximization
.38
3.2.1
Greedy Algorithm for Influence Maximization
.39
3.2.2
Empirical Evaluation of (G,k)
.44
3.3
Scalable Influence Maximization
.48
3.3.1
Reducing the Number of Influence Spread Evaluations
.48
3.3.2
Speeding Up Influence Computation
.51
3.3.3
Other Scalable Influence Maximization Schemes
.65
Xli
4
Extensions
to
Diffusion
Modeling and Influence Maximization
.67
4.1
A Data-Based Approach to Influence Maximization
.6'
4.2
Competitive Influence Modeling and Maximization
.71
4.2.1
Model Extensions for Competitive Influence Diffusion
.72
4.2.2
Maximization Problems for Competitive Influence Diffusion
.75
4.2.3
Endogenous Competition
.
°°
4.2.4
A New Frontier
-
The Host Perspective
.88
4.3
Influence, Adoption, and Profit
.94
4.3.1
Influence vs. Adoption
.95
4.3.2
Influence vs. Profit
.97
4.4
Other Extensions
.
Ю1
5
Learning Propagation Models
.105
5.1
Basic Models
.105
5.2 1С
Model
.106
5.3
Threshold Models
.109
5.3.1
Static Models
.
Ill
5.3.2
Does Influence Remain Static?
.113
5.3.3
Continuous Time Models
.114
5.3.4
Discrete Time Models
.115
5.3.5
Are All Objects Equally Influence Prone?
.116
5.3.6
Algorithms
.117
5.3.7
Experimental Validation
.
Ц9
5.3.8
Discussion
.120
6
Data and Software for Information/Influence: Propagation Research
.123
6.1
Types of
Datasets
.123
6.2
Propagation
ofinformation
"Mêmes".
124
6.2.1
Microblogging
.124
6.2.2
Newspapers/blogs/etc
.125
6.3
Propagation of Other Actions
.126
6.3.1
Consumption/Appraisal Platforms
.126
6.3.2
User-Generated Content Sharing/Voting
.127
6.3.3
Community Membership as Action
.127
6.3.4
Cross-Provider Data
.128
6.3.5
Phone Logs
. 128
6.4
Network-Only
Datasets
. 128
xiii
6.4.1
Citation Networks
.129
6.4.2
Other
Networks
.129
6.5
Other
Off-Line
Datasets
.129
6.6 Publishing
Your Own
Datasets.
130
6.7
Software Tools
.130
6.7.1
Graph Software Tools
.131
6.7.2
Propagation Software Tools
.131
6.7.3
Visualization
.132
6.8
Conclusions
.132
Conclusion and Challenges
.135
7.1
Application-Specific Challenges
.135
7.1.1
Prove Value for Advertising/Marketing
.135
7.1.2
Learn to Design for Virality
.136
7.1.3
Correct for Sampling Biases
.136
7.1.4
Contribute to Other Applications
.137
7.2
Technical Challenges
.137
7.3
Conclusions
.139
Notational Conventions
.141
Bibliography
.143
Authors' Biographies
. 157
Index
.159 |
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| building | Verbundindex |
| bvnumber | BV041578334 |
| ctrlnum | (OCoLC)847941526 (DE-599)BSZ396144365 |
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| id | DE-604.BV041578334 |
| illustrated | Illustrated |
| indexdate | 2025-01-11T13:41:39Z |
| institution | BVB |
| isbn | 9781627051156 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027023649 |
| oclc_num | 847941526 |
| open_access_boolean | |
| owner | DE-12 |
| owner_facet | DE-12 |
| physical | XV, 161 S. graph. Darst. |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Morgan & Claypool |
| record_format | marc |
| series | Synthesis lectures on data management |
| series2 | Synthesis lectures on data management |
| spelling | Chen, Wei Verfasser aut Information and influence propagation in social networks Wei Chen ; Laks V. S. Lakshmanan ; Carlos Castillo [San Rafael] Morgan & Claypool 2014 XV, 161 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Synthesis lectures on data management 37 Printed version of a work that appears in the "Synthesis Digital Library of Engineering and Computer Science" Einfluss (DE-588)4151276-5 gnd rswk-swf Soziales Netzwerk (DE-588)4055762-5 gnd rswk-swf Berechenbarkeit (DE-588)4138368-0 gnd rswk-swf Informationsfluss (DE-588)4161668-6 gnd rswk-swf Gesellschaft (DE-588)4020588-5 gnd rswk-swf Soziales Netzwerk (DE-588)4055762-5 s Informationsfluss (DE-588)4161668-6 s Gesellschaft (DE-588)4020588-5 s Einfluss (DE-588)4151276-5 s Berechenbarkeit (DE-588)4138368-0 s DE-604 Lakshmanan, Laks V. S. Verfasser aut Castillo, Carlos Verfasser aut Synthesis lectures on data management 37 (DE-604)BV036766043 37 Digitalisierung BSB Muenchen - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027023649&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Chen, Wei Lakshmanan, Laks V. S. Castillo, Carlos Information and influence propagation in social networks Synthesis lectures on data management Einfluss (DE-588)4151276-5 gnd Soziales Netzwerk (DE-588)4055762-5 gnd Berechenbarkeit (DE-588)4138368-0 gnd Informationsfluss (DE-588)4161668-6 gnd Gesellschaft (DE-588)4020588-5 gnd |
| subject_GND | (DE-588)4151276-5 (DE-588)4055762-5 (DE-588)4138368-0 (DE-588)4161668-6 (DE-588)4020588-5 |
| title | Information and influence propagation in social networks |
| title_auth | Information and influence propagation in social networks |
| title_exact_search | Information and influence propagation in social networks |
| title_full | Information and influence propagation in social networks Wei Chen ; Laks V. S. Lakshmanan ; Carlos Castillo |
| title_fullStr | Information and influence propagation in social networks Wei Chen ; Laks V. S. Lakshmanan ; Carlos Castillo |
| title_full_unstemmed | Information and influence propagation in social networks Wei Chen ; Laks V. S. Lakshmanan ; Carlos Castillo |
| title_short | Information and influence propagation in social networks |
| title_sort | information and influence propagation in social networks |
| topic | Einfluss (DE-588)4151276-5 gnd Soziales Netzwerk (DE-588)4055762-5 gnd Berechenbarkeit (DE-588)4138368-0 gnd Informationsfluss (DE-588)4161668-6 gnd Gesellschaft (DE-588)4020588-5 gnd |
| topic_facet | Einfluss Soziales Netzwerk Berechenbarkeit Informationsfluss Gesellschaft |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027023649&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV036766043 |
| work_keys_str_mv | AT chenwei informationandinfluencepropagationinsocialnetworks AT lakshmananlaksvs informationandinfluencepropagationinsocialnetworks AT castillocarlos informationandinfluencepropagationinsocialnetworks |