The fruitful collaboration among the KPAAM-CAM partners along with the results of our pilot project allowed us to apply for a new U.S. NSF grant in 2017 with a project entitled “Socio-spatial approaches to the analysis of multilingualism”. We received funding in 2018 (BCS#1761639) and this is what is currently allowing us to bring forward our research on multilingualism and space under KPAAM-CAM GEO.

Project team

  • PI’s: Jeff Good (Linguistics), Ling Bian (Geography), Jan Chomicki (Computer Science)
  • Coordinator: Pierpaolo Di Carlo
  • Steering Committee: Gratien Atindogbe (Linguistics),Gabriel Mba (Sociolinguistics), Florence Tabe (Linguistics), Mesmin Tchindjang (Geography), Lucas Wirba (Geography).
  • Students: currently being enrolled

Project summary

Language distributions represented on maps are typically quite simplified, assigning only one language to a given area. The reality is more complex. On the one hand, even in places where one language is dominant, there will often be groups who primarily use a different language in their daily lives, such as at home or in church. On the other hand, many people are able to speak more than one language, and simplified maps are incapable of representing this effectively. To achieve a more realistic sense of language distributions, it is necessary to explore linguistic knowledge and use at the level of the individual. In this multidisciplinary project, the investigators will use advances in the available tools for mapping complex social patterns for the spatial and linguistic dynamics of a rural region of Cameroon where the average adult speaks five different languages, many of which are endangered. The level of individual multilingualism found in this rural environment far exceeds what is typically found in the United States. The project will support the training of a graduate student and build future opportunities for international collaborative research. The resulting research on socio-spatial patterns and language use may be usable by the U.S. in the areas of public health, national security, and connections on the ground in Cameroon. The future adaptation of these methods will facilitate investigating the spatial patterns of other dimensions of social behavior, such as trade and marriage, or to compare the spread of linguistic features with the spread of diseases.

The investigators will utilize new ways of representing and analyzing language distributions using Geographic Information Systems (GIS) and individual-level data to understand the extent to which people tend to learn languages spoken by those that they live near and languages spoken by their friends and family members. These individual-level factors will be examined with regard to the dynamics and nature of the community in which these individuals live. A particular focus of the work is understanding the relationship between spatial, social, and cultural factors in accounting for an individual’s linguistic knowledge. High-resolution spatial data will be integrated with detailed descriptions of individual patterns of language use and analyzed from the perspective of spatial and social network analysis. Much of the data will be collected using smartphones, allowing information to be gathered at a scale that is unprecedented for linguistic research on endangered languages. The tools and methods to be developed will be general in nature and applicable to any part of the world and will be especially useful for the investigation of the language dynamics of rural areas with limited infrastructure. A better understanding of how and why people come to speak different languages will provide better information to policymakers in the domain of language planning. Spatial analysis of individual language use will augment psycholinguistic and other analyses of multilingualism to advance knowledge of human cognition and behavior in this domain.