Aidan Pine and Mark Turin
The world is home to an extraordinary level of linguistic diversity, with roughly 7,000 languages currently spoken and signed. Yet this diversity is highly unstable and is being rapidly eroded through a series of complex and interrelated processes that result in or lead to language loss. The combination of monolingualism and networks of global trade languages that are increasingly technologized have led to over half of the world’s population speaking one of only 13 languages. Such linguistic homogenization leaves in its wake a linguistic landscape that is increasingly endangered.
A wide range of factors contribute to language loss and attrition. While some—such as natural disasters—are unique to particular language communities and specific geographical regions, many have similar origins and are common across endangered language communities around the globe. The harmful legacy of colonization and the enduring impact of disenfranchising policies relating to Indigenous and minority languages are at the heart of language attrition from New Zealand to Hawai’i, and from Canada to Nepal.
Language loss does not occur in isolation, nor is it inevitable or in any way “natural.” The process also has wide-ranging social and economic repercussions for the language communities in question. Language is so heavily intertwined with cultural knowledge and political identity that speech forms often serve as meaningful indicators of a community’s vitality and social well-being. More than ever before, there are vigorous and collaborative efforts underway to reverse the trend of language loss and to reclaim and revitalize endangered languages. Such approaches vary significantly, from making use of digital technologies in order to engage individual and younger learners to community-oriented language nests and immersion programs. Drawing on diverse techniques and communities, the question of measuring the success of language revitalization programs has driven research forward in the areas of statistical assessments of linguistic diversity, endangerment, and vulnerability. Current efforts are re-evaluating the established triad of documentation-conservation-revitalization in favor of more unified, holistic, and community-led approaches.
Klaus Beyer and Henning Schreiber
The Social Network Analysis approach (SNA), also known as sociometrics or actor-network analysis, investigates social structure on the basis of empirically recorded social ties between actors. It thereby aims to explain e.g. the processes of flow of information, spreading of innovations, or even pathogens throughout the network by actor roles and their relative positions in the network based on quantitative and qualitative analyses. While the approach has a strong mathematical and statistical component, the identification of pertinent social ties also requires a strong ethnographic background. With regard to social categorization, SNA is well suited as a bootstrapping technique for highly dynamic communities and under-documented contexts. Currently, SNA is widely applied in various academic fields. For sociolinguists, it offers a framework for explaining the patterning of linguistic variation and mechanisms of language change in a given speech community.
The social tie perspective developed around 1940, in the field of sociology and social anthropology based on the ideas of Simmel, and was applied later in fields such as innovation theory. In sociolinguistics, it is strongly connected to the seminal work of Lesley and James Milroy and their Belfast studies (1978, 1985). These authors demonstrate that synchronic speaker variation is not only governed by broad societal categories but is also a function of communicative interaction between speakers. They argue that the high level of resistance against linguistic change in the studied community is a result of strong and multiplex ties between the actors. Their approach has been followed by various authors, including Gal, Lippi-Green, and Labov, and discussed for a variety of settings; most of them, however, are located in the Western world.
The methodological advantages could make SNA the preferred framework for variation studies in Africa due to the prevailing dynamic multilingual conditions, often on the backdrop of less standardized languages. However, rather few studies using SNA as a framework have yet been conducted. This is possibly due to the quite demanding methodological requirements, the overall effort, and the often highly complex linguistic backgrounds. A further potential obstacle is the pace of theoretical development in SNA. Since its introduction to sociolinguistics, various new measures and statistical techniques have been developed by the fast growing SNA community. Receiving this vast amount of recent literature and testing new concepts is likewise a challenge for the application of SNA in sociolinguistics.
Nevertheless, the overall methodological effort of SNA has been much reduced by the advancements in recording technology, data processing, and the introduction of SNA software (UCINET) and packages for network statistics in R (‘sna’). In the field of African sociolinguistics, a more recent version of SNA has been implemented in a study on contact-induced variation and change in Pana and Samo, two speech communities in the Northwest of Burkina Faso. Moreover, further enhanced applications are on the way for Senegal and Cameroon, and even more applications in the field of African languages are to be expected.