Making “fetch” happen: The influence of social and linguistic context on nonstandard word growth and decline

Abstract

In an online community, new words come and go: today's haha may be replaced by tomorrow's lol. Changes in online writing are usually studied as a social process, with innovations diffusing through a network of individuals in a speech community. But unlike other types of innovation, language change is shaped and constrained by the grammatical system in which it takes part. To investigate the role of social and structural factors in language change, we undertake a large-scale analysis of the frequencies of nonstandard words in Reddit. Dissemination across many linguistic contexts is a predictor of success: words that appear in more linguistic contexts grow faster and survive longer. Furthermore, social dissemination plays a less important role in explaining word growth and decline than previously hypothesized.

Predicting the Growth of Morphological Families from Social and Linguistic Factors

“…8 Furthermore, it is interesting to note that the frequency-based as well as the dissemination-based measures are considerably clumped together in feature importance space for absolute growth δ a , with the frequency-based predictors topping the dissemination-based ones. This is in line with recent work on the relative importance of frequency and social dissemination in lexical change (Stewart and Eisenstein, 2018). Higher values in these features correlate with a higher likelihood of growth, except for topicality: here, growth is more likely with lower topicality, which as discussed above indicates higher topical dissemination.…”

“…Generally, the more disseminated a word is, the more likely it is to grow. This holds for social dissemination across users and threads (Altmann et al, 2011) as well as linguistic dissemination across different lexical collocations (Stewart and Eisenstein, 2018).…”

“…Concretely, we draw upon the Baumgartner Reddit Corpus, a collection of (almost) all publicly available comments posted on Reddit since 2005. 4 A three-year slice of this corpus was used in a study on lexical change by Stewart and Eisenstein (2018). Gaffney and Matias (2018) show that the corpus's coverage of Reddit is not complete, but we do not expect this to affect our analysis.…”

“…Usage frequency is a well-known factor that influences the evolution of a word at historical time scales (Pagel et al, 2007). Studies on lexical change in online groups have shown that this is also true for shorter time scales (Altmann et al, 2011;Stewart and Eisenstein, 2018). Another main factor is the dissemination of a word, i.e., how widely a word is spread across different social and linguistic contexts.…”

Temporally-Informed Analysis of Named Entity Recognition

“…Language change is a popular topic of research in linguistics (Stephen, 1962). In natural language processing, using data from online platforms such as Twitter or discussion fora, language change and adoption have been studied at the community level (Danescu-Niculescu-Mizil et al, 2013;Eisenstein et al, 2014;Goel et al, 2016;Stewart and Eisenstein, 2018) and at the individual level (Zhang et al, 2019). In some cases, the senses of the same word are known to shift over time (Wijaya and Yeniterzi, 2011), and modeling such changes in word semantics has been explored using diachronic word embeddings (Kulkarni et al, 2015;Hamilton et al, 2016;Kutuzov et al, 2018).…”