| 000 -LEADER |
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| fixed length control field |
nam a22 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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231129b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783030002282 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.312 |
| Item number |
TAG |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Tagarelli, Andrea |
| 245 ## - TITLE STATEMENT |
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| Title |
Mining lurkers in online social networks : principles, models, and computational methods |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2018 |
| Place of publication, distribution, etc |
Cham : |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
vi, 93 p. ; |
| Other physical details |
ill., |
| Dimensions |
23 cm |
| 365 ## - TRADE PRICE |
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| Price amount |
49.99 |
| Price type code |
EUR |
| Unit of pricing |
91.70 |
| 490 ## - SERIES STATEMENT |
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| Series statement |
SpringerBriefs in computer science |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
This SpringerBrief brings order to the wealth of research studies that contribute to shape our understanding of on-line social networks (OSNs) lurking phenomena. This brief also drives the development of computational approaches that can be effectively applied to answer questions related to lurking behaviors, as well as to the engagement of lurkers in OSNs. All large-scale online social networks (OSNs) are characterized by a participation inequality principle, i.e., the crowd of an OSN does not actively contribute, rather it takes on a silent role. Silent users are also referred to as lurkers, since they gain benefit from others' information without significantly giving back to the community. Nevertheless, lurkers acquire knowledge from the OSN, therefore a major goal is to encourage them to more actively participate. Lurking behavior analysis has been long studied in social science and human-computer interaction fields, but it has also matured over the last few years in social network analysis and mining. While the main target audience corresponds to computer, network, and web data scientists, this brief might also help increase the visibility of the topic by bridging different closely related research fields. Practitioners, researchers and students interested in social networks, web search, data mining, computational social science and human-computer interaction will also find this brief useful research material. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Evolutionary game theory |
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| Topical term or geographic name as entry element |
Influence propagation |
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| Topical term or geographic name as entry element |
Information diffusion |
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| Topical term or geographic name as entry element |
User engagement |
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| Topical term or geographic name as entry element |
Vicarious learning |
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| Topical term or geographic name as entry element |
Passive users |
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| Topical term or geographic name as entry element |
Silent users |
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| Topical term or geographic name as entry element |
Influence propagation |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Interdonato, Roberto |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
|
| Item type |
Books |