Network analysis of the social and demographic influences on name choice within the UK (1838-2016)

Abstract

Chosen names reflect a society’s changing values, aspirations and cultural diversity. Vogues in name usage can be easily shown on a case by case basis, by plotting the rise and fall in their popularity over time. However, individual name choices are not made in isolation and trends in naming are better understood as group-level phenomena. Here we use network analysis to examine onomastic (name) datasets in order to explore the influences on name choices within the UK over the last 170 years. Using a large representative sample of approximately 22 million chosen forenames from England and Wales given between 1838 and 2014, along with a complete population sample of births registered between 1996 and 2016, we demonstrate how trends in name usage can be visualised as network graphs.By exploring the structure of these graphs, various patterns of name use become readily apparent, which can be interpreted in the context of historic events, such as known waves of migration. In general, we show that the topology of network graphs can reveal naming vogues, and that naming vogues are a reflection of social and demographic changes.Many name choices are consistent with a self-correcting feedback loop, whereby rarer names become common because there are virtues perceived in their rarity, yet with these perceived virtues lost upon increasing commonality. Towards the present day, the comparatively greater range of media, freedom of movement, and ability to maintain globally-distributed social networks increases the number of possible names, but also ensures they may more quickly be perceived as commonplace. Consequently, contemporary naming vogues are relatively short-lived with many name choices appearing a balance struck between recognisability and rarity.The data are available via an easy-to-use web interface at http://demos.flourish.studio/namehistory.

Graphia: A platform for the graph-based visualisation and analysis of complex data

“…BioLayout has been used in the analysis of many large transcriptomic datasets from multiple species [39][40][41][42][43] . It has also been applied to datasets that were not envisaged at the time, for example the relationship between symptoms of altitude sickness 44 , the honey bee microbiome 45 , comparing morphometric measurements of dog brains 46 and even naming patterns in historical birth records 47 . The addition of new functionality to BioLayout was however constrained by inherent limitations in the code structure and programming language (Java).…”

Re-using the names of newborns: symbolic reincarnation in an age of infant mortality

“…These corrections are detailed alongside a corpus of names derived from the birth records, hosted via the University of Edinburgh DataShare portal (http://dx.doi.org/10.7488/ds/2294) and made available as part of a separate study applying network analysis methods to onomastic data (Bush, Powell-Smith, and Freeman 2018).…”

“…In total, 23,468,892 birth records, 18,864,672 marriage records and 13,379,636 death records were examined for this study (the number of records per region, and the years and regions covered, are detailed in (Bush, Powell-Smith, and Freeman 2018)). The available fields for each person's birth record were the first name, middle name(s) and surname, mother's maiden name (where applicable), year of birth, sub-district of the region in which the birth was registered, and identification number.…”