| 000 | 03136nam a22005535i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-23105-1 | ||
| 003 | DE-He213 | ||
| 005 | 20200421112552.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150916s2015 gw | s |||| 0|eng d | ||
| 020 |
_a9783319231051 _9978-3-319-23105-1 |
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| 024 | 7 |
_a10.1007/978-3-319-23105-1 _2doi |
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| 050 | 4 | _aQ334-342 | |
| 050 | 4 | _aTJ210.2-211.495 | |
| 072 | 7 |
_aUYQ _2bicssc |
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| 072 | 7 |
_aTJFM1 _2bicssc |
|
| 072 | 7 |
_aCOM004000 _2bisacsh |
|
| 082 | 0 | 4 |
_a006.3 _223 |
| 100 | 1 |
_aShakarian, Paulo. _eauthor. |
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| 245 | 1 | 0 |
_aDiffusion in Social Networks _h[electronic resource] / _cby Paulo Shakarian, Abhivav Bhatnagar, Ashkan Aleali, Elham Shaabani, Ruocheng Guo. |
| 250 | _a1st ed. 2015. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015. |
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| 300 |
_aXI, 101 p. 28 illus., 24 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
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| 505 | 0 | _aIntroduction -- The SIR Model and Identification of Spreaders -- The Tipping Model and the Minimum Seed Problem -- The Independent Cascade and Linear Threshold Models -- Logic Programming Based Diffusion Models -- Evolutionary Graph Theory -- Examining Diffusion in the Real World -- Conclusion. | |
| 520 | _aThis book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), sociology (tipping models), physics (voter models), biology (evolutionary models), and epidemiology (SIR/SIS and related models). A variety of properties and problems related to these models are discussed including identifying seeds sets to initiate diffusion, game theoretic problems, predicting diffusion events, and more. The book explores numerous connections between social network diffusion research and artificial intelligence through topics such as agent-based modeling, logic programming, game theory, learning, and data mining. The book also surveys key empirical results in social network diffusion, and reviews the classic and cutting-edge research with a focus on open problems. | ||
| 650 | 0 | _aComputer science. | |
| 650 | 0 | _aData encryption (Computer science). | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 1 | 4 | _aComputer Science. |
| 650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
| 650 | 2 | 4 | _aData Encryption. |
| 700 | 1 |
_aBhatnagar, Abhivav. _eauthor. |
|
| 700 | 1 |
_aAleali, Ashkan. _eauthor. |
|
| 700 | 1 |
_aShaabani, Elham. _eauthor. |
|
| 700 | 1 |
_aGuo, Ruocheng. _eauthor. |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319231044 |
| 830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-23105-1 |
| 912 | _aZDB-2-SCS | ||
| 942 | _cEBK | ||
| 999 |
_c58940 _d58940 |
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