Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model

Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic the...
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Autor*in:	Li, Deng [verfasserIn] Chen, Zhujun [verfasserIn] Liu, Jiaqi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Social network Altruism Cooperation Parallel processing

Übergeordnetes Werk:	Enthalten in: International journal of parallel programming - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1972, 47(2018), 4 vom: 16. Feb., Seite 686-708
Übergeordnetes Werk:	volume:47 ; year:2018 ; number:4 ; day:16 ; month:02 ; pages:686-708

Links:	Volltext

DOI / URN:	10.1007/s10766-018-0559-9

Katalog-ID:	SPR013126687

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520			\|a Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing.
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author_variant	d l dl z c zc j l jl
matchkey_str	article:15737640:2018----::nlssobhvoaeooisnoilewrsnlrimaed
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allfields	10.1007/s10766-018-0559-9 doi (DE-627)SPR013126687 (SPR)s10766-018-0559-9-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.25 bkl Li, Deng verfasserin aut Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing. Social network (dpeaa)DE-He213 Altruism (dpeaa)DE-He213 Cooperation (dpeaa)DE-He213 Parallel processing (dpeaa)DE-He213 Chen, Zhujun verfasserin aut Liu, Jiaqi verfasserin aut Enthalten in International journal of parallel programming Dordrecht [u.a.] : Springer Science + Business Media B.V., 1972 47(2018), 4 vom: 16. Feb., Seite 686-708 (DE-627)319583945 (DE-600)2006577-2 1573-7640 nnns volume:47 year:2018 number:4 day:16 month:02 pages:686-708 https://dx.doi.org/10.1007/s10766-018-0559-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.25 ASE AR 47 2018 4 16 02 686-708
spelling	10.1007/s10766-018-0559-9 doi (DE-627)SPR013126687 (SPR)s10766-018-0559-9-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.25 bkl Li, Deng verfasserin aut Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing. Social network (dpeaa)DE-He213 Altruism (dpeaa)DE-He213 Cooperation (dpeaa)DE-He213 Parallel processing (dpeaa)DE-He213 Chen, Zhujun verfasserin aut Liu, Jiaqi verfasserin aut Enthalten in International journal of parallel programming Dordrecht [u.a.] : Springer Science + Business Media B.V., 1972 47(2018), 4 vom: 16. Feb., Seite 686-708 (DE-627)319583945 (DE-600)2006577-2 1573-7640 nnns volume:47 year:2018 number:4 day:16 month:02 pages:686-708 https://dx.doi.org/10.1007/s10766-018-0559-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.25 ASE AR 47 2018 4 16 02 686-708
allfields_unstemmed	10.1007/s10766-018-0559-9 doi (DE-627)SPR013126687 (SPR)s10766-018-0559-9-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.25 bkl Li, Deng verfasserin aut Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing. Social network (dpeaa)DE-He213 Altruism (dpeaa)DE-He213 Cooperation (dpeaa)DE-He213 Parallel processing (dpeaa)DE-He213 Chen, Zhujun verfasserin aut Liu, Jiaqi verfasserin aut Enthalten in International journal of parallel programming Dordrecht [u.a.] : Springer Science + Business Media B.V., 1972 47(2018), 4 vom: 16. Feb., Seite 686-708 (DE-627)319583945 (DE-600)2006577-2 1573-7640 nnns volume:47 year:2018 number:4 day:16 month:02 pages:686-708 https://dx.doi.org/10.1007/s10766-018-0559-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.25 ASE AR 47 2018 4 16 02 686-708
allfieldsGer	10.1007/s10766-018-0559-9 doi (DE-627)SPR013126687 (SPR)s10766-018-0559-9-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.25 bkl Li, Deng verfasserin aut Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing. Social network (dpeaa)DE-He213 Altruism (dpeaa)DE-He213 Cooperation (dpeaa)DE-He213 Parallel processing (dpeaa)DE-He213 Chen, Zhujun verfasserin aut Liu, Jiaqi verfasserin aut Enthalten in International journal of parallel programming Dordrecht [u.a.] : Springer Science + Business Media B.V., 1972 47(2018), 4 vom: 16. Feb., Seite 686-708 (DE-627)319583945 (DE-600)2006577-2 1573-7640 nnns volume:47 year:2018 number:4 day:16 month:02 pages:686-708 https://dx.doi.org/10.1007/s10766-018-0559-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.25 ASE AR 47 2018 4 16 02 686-708
allfieldsSound	10.1007/s10766-018-0559-9 doi (DE-627)SPR013126687 (SPR)s10766-018-0559-9-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.25 bkl Li, Deng verfasserin aut Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing. Social network (dpeaa)DE-He213 Altruism (dpeaa)DE-He213 Cooperation (dpeaa)DE-He213 Parallel processing (dpeaa)DE-He213 Chen, Zhujun verfasserin aut Liu, Jiaqi verfasserin aut Enthalten in International journal of parallel programming Dordrecht [u.a.] : Springer Science + Business Media B.V., 1972 47(2018), 4 vom: 16. Feb., Seite 686-708 (DE-627)319583945 (DE-600)2006577-2 1573-7640 nnns volume:47 year:2018 number:4 day:16 month:02 pages:686-708 https://dx.doi.org/10.1007/s10766-018-0559-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.25 ASE AR 47 2018 4 16 02 686-708
language	English
source	Enthalten in International journal of parallel programming 47(2018), 4 vom: 16. Feb., Seite 686-708 volume:47 year:2018 number:4 day:16 month:02 pages:686-708
sourceStr	Enthalten in International journal of parallel programming 47(2018), 4 vom: 16. Feb., Seite 686-708 volume:47 year:2018 number:4 day:16 month:02 pages:686-708
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Social network Altruism Cooperation Parallel processing
dewey-raw	070
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container_title	International journal of parallel programming
authorswithroles_txt_mv	Li, Deng @@aut@@ Chen, Zhujun @@aut@@ Liu, Jiaqi @@aut@@
publishDateDaySort_date	2018-02-16T00:00:00Z
hierarchy_top_id	319583945
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id	SPR013126687
language_de	englisch
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Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). 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author	Li, Deng
spellingShingle	Li, Deng ddc 070 bkl 54.25 misc Social network misc Altruism misc Cooperation misc Parallel processing Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model
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topic_title	070 004 ASE 54.25 bkl Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model Social network (dpeaa)DE-He213 Altruism (dpeaa)DE-He213 Cooperation (dpeaa)DE-He213 Parallel processing (dpeaa)DE-He213
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title	Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model
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title_full	Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model
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title_sort	analysis for behavioral economics in social networks: an altruism-based dynamic cooperation model
title_auth	Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model
abstract	Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing.
abstractGer	Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing.
abstract_unstemmed	Abstract Aiming at uncooperative behaviors such as free-riding, white-washing and sybil attacks, and the lack of rationality hypothesis in the traditional economic models, the paper presents an Altruism-Based Dynamic Model (ABDM) in social networks by introducing views from reciprocal altruistic theory. Considering the initiative of nodes behind reciprocal altruistic behaviors, the ABDM improves the cooperation rate of the network and promotes the propagation of cooperative behavior by using the nodes’ inherent ability of reciprocal altruism. Furthermore, based on nodes’ bounded rationality, ABDM also perfects models of traditional economic theories. The simulation results show that compared with the traditional model, the proposed ABDM has the higher level of cooperation, the stronger scalability and the better robustness. On this basis, the paper analyzes the ABDM at different scenarios: varying group sizes and population; behavior selection under varying parameter settings (cost-to-benefit ratios of the psychological payoff and etc.). With the more efficient interactions among the nodes, the ABDM model can improve the efficiency of parallel processing.
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container_issue	4
title_short	Analysis for Behavioral Economics in Social Networks: An Altruism-Based Dynamic Cooperation Model
url	https://dx.doi.org/10.1007/s10766-018-0559-9
remote_bool	true
author2	Chen, Zhujun Liu, Jiaqi
author2Str	Chen, Zhujun Liu, Jiaqi
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doi_str	10.1007/s10766-018-0559-9
up_date	2024-07-03T17:38:37.459Z
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