Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/311045 
Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Annals of Operations Research [ISSN:] 1572-9338 [Volume:] 338 [Issue:] 2 [Publisher:] Springer US [Place:] New York, NY [Year:] 2023 [Pages:] 1083-1100
Verlag: 
Springer US, New York, NY
Zusammenfassung: 
Power in human societies is a central phenomenon. Even though, it took ages to understand it and – even more – to measure it. Only in the last decades attempts were made to model power relations and to assign respective power indices to actors in a network. The present work goes a step further. It measures power of actors and groups of actors in networks by means of conditional relations. In a probabilistic framework, such relations are specified as conditionals: Which actor receives power given that the adjacent actor has it, and which actor looses power given that the neighbour dominates. This pattern of power relations allows for an exact calculation of an actor's and groups of actors' power index. The new decision analytics tool for this is maximizing entropy for the whole net and evaluating each actor's influence therein. The new concept is applied to a middle size Kronecker net of clans and subclans operating in a today's society.
Schlagwörter: 
Network analytics
Entropy
Power networks
Power support
Power suppression
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