{"title":"Social Network Analysis and Kinship in the Old Babylonian Diyala. Fathers and Sons in the Archive of Nūr-Šamaš","authors":"Carlos Gonçalves","doi":"10.21814/h2d.3470","DOIUrl":null,"url":null,"abstract":"The object of the analysis carried out here is the Old Babylonian archive of Nūr-Šamaš, provenient from the Diyala region, formed by 116 loan contracts conceded by Nūr-Šamaš, and involving some 400 people as debtors and witnesses. Data obtained from the documents of the archive will be used to generate a graph modelling the relations of the attested persons. The graph will then be split into classes maximizing modularity, that is to say, into clusters optimally composed by personal identifications that statistically tend to connect more inside each cluster than with personal identifications of other clusters. Finally, this will be used to raise or lower the probability of stating that pairs of identifications of the type 'ZZZ, son of YYY' and 'YYY' may correspond respectively to a son and his father.","PeriodicalId":365381,"journal":{"name":"H2D|Revista de Humanidades Digitais","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"H2D|Revista de Humanidades Digitais","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21814/h2d.3470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The object of the analysis carried out here is the Old Babylonian archive of Nūr-Šamaš, provenient from the Diyala region, formed by 116 loan contracts conceded by Nūr-Šamaš, and involving some 400 people as debtors and witnesses. Data obtained from the documents of the archive will be used to generate a graph modelling the relations of the attested persons. The graph will then be split into classes maximizing modularity, that is to say, into clusters optimally composed by personal identifications that statistically tend to connect more inside each cluster than with personal identifications of other clusters. Finally, this will be used to raise or lower the probability of stating that pairs of identifications of the type 'ZZZ, son of YYY' and 'YYY' may correspond respectively to a son and his father.