Finding Communities in Social Networks Using Graph Embeddings (Record no. 61155)
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| fixed length control field | 04407nam a22005535i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-60916-9 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251030112341.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240629s2024 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783031609169 |
| -- | 978-3-031-60916-9 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-031-60916-9 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | H61.3 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UF |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM005000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UXJ |
| Source | thema |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Alfaqeeh, Mosab. |
| Relator term | author. |
| Relator code | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 9 (RLIN) | 79615 |
| 245 10 - TITLE STATEMENT | |
| Title | Finding Communities in Social Networks Using Graph Embeddings |
| Medium | [electronic resource] / |
| Statement of responsibility, etc. | by Mosab Alfaqeeh, David B. Skillicorn. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cham : |
| Name of producer, publisher, distributor, manufacturer | Springer Nature Switzerland : |
| -- | Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | IX, 177 p. 90 illus., 34 illus. in color. |
| Other physical details | online resource. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Encoding format | |
| Source | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Social Networks, |
| International Standard Serial Number | 2190-5436 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Chapter 1: Introduction -- Chapter 2: Background -- Chapter 3: Building blocks -- Chapter 4: Social network data -- Chapter 5: Methodology -- Chapter 6: Results and validation -- Chapter 7: Conclusions. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Community detection in social networks is an important but challenging problem. This book develops a new technique for finding communities that uses both structural similarity and attribute similarity simultaneously, weighting them in a principled way. The results outperform existing techniques across a wide range of measures, and so advance the state of the art in community detection. Many existing community detection techniques base similarity on either the structural connections among social-network users, or on the overlap among the attributes of each user. Either way loses useful information. There have been some attempts to use both structure and attribute similarity but success has been limited. We first build a large real-world dataset by crawling Instagram, producing a large set of user profiles. We then compute the similarity between pairs of users based on four qualitatively different profile properties: similarity of language used in posts, similarity of hashtags used (which requires extraction of content from them), similarity of images displayed (which requires extraction of what each image is 'about'), and the explicit connections when one user follows another. These single modality similarities are converted into graphs. These graphs have a common node set (the users) but different sets a weighted edges. These graphs are then connected into a single larger graph by connecting the multiple nodes representing the same user by a clique, with edge weights derived from a lazy random walk view of the single graphs. This larger graph can then be embedded in a geometry using spectral techniques. In the embedding, distance corresponds to dissimilarity so geometric clustering techniques can be used to find communities. The resulting communities are evaluated using the entire range of current techniques, outperforming all of them. Topic modelling is also applied to clusters to show that they genuinely represent users with similar interests. This can form the basis for applications such as online marketing, or key influence selection. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| General subdivision | Data processing. |
| 9 (RLIN) | 65741 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 55059 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 65743 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 9 (RLIN) | 55059 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Skillicorn, David B. |
| Relator term | author. |
| Relator code | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 9 (RLIN) | 79616 |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031609152 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031609176 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783031609183 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Lecture Notes in Social Networks, |
| International Standard Serial Number | 2190-5436 |
| 9 (RLIN) | 79617 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-031-60916-9">https://doi.org/10.1007/978-3-031-60916-9</a> |
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