The diffusion of scientific terms – tracing individuals’ influence in the history of science for E nglish (2021)

Abstract: Tracing the influence of individuals or groups in social networks is an increasingly popular task in sociolinguistic studies. While methods to determine someone’s influence in shortterm contexts (e.g., social media, on-line political debates) are widespread, influence in longterm contexts is less investigated and may be harder to capture. We study the diffusion of scientific terms in an English diachronic scientific corpus, applying Hawkes Processes to capture the role of individual scientists as “influencers” or “influencees” in the diffusion of new concepts. Our findings on two major scientific discoveries in chemistry and astronomy of the 18th century reveal that modelling both the introduction and diffusion of scientific terms in a historical corpus as Hawkes Processes allows detecting patterns of influence between authors on a long-term scale.

## introduction the detection and definition of influence in social contexts is becoming increasingly popular in computational sociolinguistics and related disciplines @xcite @xcite , mainly due to the availability of data from large-scale social media that allow us to study an unprecedented amount of exchanges, but recently also in diachronic settings as shown by @xcite on lexical semantic change. as the diffusion of new concepts and ideas is inherent to scientific writing, one can assume many cases of terminological influence between authors. also, since scientific communities act as social and collaborative networks @xcite , the diffusion of new concepts in the history of science might behave similarly to that of recently formed communities such as social media networks. scientific findings that either introduce new concepts or redefine the understanding of known phenomena are bound to either encourage the acquisition of new words and expressions or to promote existing terminology that gets endowed with novel importance. we present a pilot application of hawkes processes, usually used to trace short-term influences between cascades of events, modeling long-term influences between authors of the philosophical transactions and proceedings of the royal society of london, two of the longest-running scientific journals in english. from today's perspective, the 18th century royal society network represented a rather narrow circle of professional and private relations @xcite . in the publications of this "scientific club", we assume a reflection of social and thematic networks. central members may have had a particular influence by crossing disciplinary boundaries that were not yet well established. relying on previous findings on innovative uses of words in the late modern period of the rsc @xcite , we select in a data-driven fashion using kullback-leibler divergence sets of words distinctively used around that period and involved in terminology formation. these sets of words are used to select texts to be fed into the modelling of hawkes processes. we present the results of influences between individuals for two specific "revolutionary" periods in the history of science: (1) the discovery of oxygen, leading to the chemical revolution in the mid-18th century, and (2) the rapid expansion of knowledge on the composition of structures in the universe (the planetary nebula) through more powerful telescopes around the end of the 18th century. ## related work large diachronic scientific corpora are rare and valuable, since they allow us to study the development of a rather big but specialized community throughout historical time spans. one of the largest curated corpora of this kind to date is the royal society corpus (rsc; see @xcite ; fischer et al. (2020) for corpus creation @xcite for metadata curation). the material of the royal society has been used in various diachronic studies to explore the development of english scientific writing and aspects such as the evolution of peer review and community-based editorial processes of scholarly journals (e.g., @xcite ; @xcite ; fyfe et al. (2020); bizzoni et al. (2020) ). considering work on tracing influences, hawkes processes (hp) @xcite , originally designed to model waves of earthquakes' aftershocks @xcite , have gained popularity in sociolinguistics. they have been recently used as powerful means to study influence relationships between authors on a text-based level @xcite as well as words' spreading and turn taking in conversations @xcite @xcite and social media @xcite @xcite . the main advantage of using hps has been found in their ability to model a wide range of different relationships between events through a transfer function @xcite . also, their flexibility in accommodating auxiliary features @xcite has made them increasingly popular in fields like criminology @xcite , economy @xcite , and epidemiology @xcite . their flexibility has also made hps particularly apt to finance and market modelling @xcite . naturally, with the growth of social media a number of studies have found hps suitable to model the spread of information through communication networks @xcite @xcite . all in all, hps are a relatively simple and robust method to detect influence from incomplete and noisy data @xcite . we adapt hps to model long-term influences between scientific authors focusing on the use of newly established terminology. ## discussion and future work this pilot study aimed to trace influences on the diffusion of terms in the history of science. we model long-term influences with hawkes processes, usually applied to short-time studies, on the diachronic royal society corpus. we focus on two cases in the late modern period: (a) the diffusion of oxygen terminology, when the competing concept of phlogiston was losing momentum, and (b) the diffusion of specific astronomical terms centered around the discovery of new nebulae. for both, the model detects realistic influences between authors which correspond to qualitative observations of the scientific fields involved. the relationships between influencers and influencees can be quite diverse and contribute differently to the diffusion of innovative knowledge. for example, for the oxygen theory, while priestley is the innovator, pearson, the early adopter, is the one influencing a large number of peers. for the planetary nebulae discovery, instead, caroline herschel acts as a wide-spreading influencer among other influencers, while her brother william is a strong adopter with no major influencer role. being supported by empirical observations, these results also validate hps as a possible tool to study long-term influence between authors. in future works, a deeper qualitative analysis will allow us to detect more reliably possible benefits and drawbacks of the approach. for example, informing our data-driven approach with knowledge of historians of science, as we have simplistically shown for caroline herschel, would be beneficial, and investigating more deeply connections detected by our model will show whether we are able to find latent patterns of influence or detect false positives. to further evaluate the appropriateness of the approach, we might attempt to reproduce the phenomena we model in synthetic data that mimic types of lexical diffusion over longer periods. thus, we would have an even clearer idea of what types of scientific influence hps can capture best. while we here consider the lexical level, we are especially interested in tracing the diffusion of syntactic and/or stylistic patterns shaping the scientific register. the language of science has been shown to increasingly use conventionalized ways of expression to level out the high degree of informativity rendered @xcite @xcite . however, influencers originating from minority groups, such as caroline herschel, might have had to oblige not only to conventions related to the language of science but also to socio-cultural conventions possibly reflected in their use of language. according to @xcite , e.g., caroline's language is modest, self-effacing and polite highlighting her awareness of the proper codes of conduct for women, but also succinct and rigorous on the accounts of her observations, conclusions and defence of their credibility adhering to the expectations of the scientific community. also, her use of language does not claim priority as her bother's, but focuses on sharing information. thus, detecting influencer belonging to particular socio-cultural groups and analyzing their use of language across linguistic levels might help us to better understand the complexity of the diffusion of knowledge and the different possible stages and relationships of influencers and influencees considering social roles.