3.11.3 Current and Future Trends of Linguistic Research
3.11.3.1 Review of Research Work
This article reviews recent works of applying GIS in linguistic studies. Over the last two decades, linguistic research made an important innovation technologically and such innovation is to import the GIS tools that allowed them to manage and display language data. This type of tools has become more and more popular among linguistic researchers. Having GIS tools, linguistic researches are now capable of doing quantitative research using linguistic data that were difficult in the past. In the meantime, the GIS tool allowed linguistic data to be stored and managed together with the data from other disciplines using the same framework. This greatly enhanced linguistic research by enriching the nature and comprehensiveness of the science of linguistics. In addition, GIS’s function for visualizing geographical data enabled linguistic data to be displayed vividly, which substantially increases the acceptance and the level of comprehension of linguistic researches by the general public. Because it is now relatively easy to implement data storage, data management, and visualization in GIS tools, such implementations are now the most applied research methods in linguistic studies.
Since early applications of GIS in linguistic studies, scholars had realized the great potential of using GIS in linguistics. Especially, spatial analytics in GIS made it possible for innovation, theory reconstruction, formulating new research hypotheses, and data visualization in linguistic studies. Still, there existed only a limited number of research that adopted GIS tools and spatial analytics in working with linguistic data. They should definitely be promoted to encourage more uses in linguistic studies. With the advent of information era, informatization will become an important direction for the development of different disciplines. GISystem and GIScience will be an excellent platform for the informatization in linguistic studies. Researchers can utilize GIS as the interface to work with other new informational technologies so that they can formulate a new breakthrough on the framework of linguistic studies and, at the same time, make linguistic studies to be better understood by the general public.
In summary, GIS enabled linguistic studies to be more quantitative, vivid, and scientific. With GIS, linguistic scholars have also made a substantial achievement in linguistics. With the improvement of technology, better understanding of spatial concepts for the researchers, and influence of the background of information age, more potentials could be seen in the future of linguistic studies.
3.11.3.2 Trends of Applying GIS in Linguistic Studies
Currently, most applications of GIS in linguistic studies are still in the primitive form, which included introducing the GIS software into linguistic studies and demonstrating that such software could be used with great potentials. Most of those works pertained to data storage, data management, mapping of simple distributions, and visualizing linguistic data of multiple formats with only a few examples of using simple spatial analyses. Few linguistic scholars pursued reasons behind changes in the spatial patterns and processes as shown by linguistic data. Moreover, traditional linguistic studies typically lack the adoption of spatial concepts. In order to understand an emerging regional phenomenon, one has to realize the importance of concepts of space and distance as well as the relationship between them and other social, political, and/or environmental factors. These factors often play the essential roles in revealing the process of language development. Therefore, next agenda for linguistic researchers would be to improve the understanding of spatial patterns and processes exhibited in linguistic data. Based on that, linguistic scholars can then carry out in-depth studies using GIS to reason the spatial distribution and process of changes in languages such as the interaction between society and history, migration, natural environment, communication and transportation, and other factors.
Furthermore, with the improvement of technology and the advent of information era, more software related to data storage, data management, and visualization in linguistic research emerged (Luebbering et al., 2013). For example, GPS, web-based mapping of data uncertainty, data visualization, and spatiotemporal analysis will provide linguistic scholars an enhanced armory for working with linguist data. Because GIS itself can be seen as the platform for managing comprehensive data and it is also the open architecture that can be used for further development, GIS are really suitable for linguistic scholars to work with a wide variety of other computer software. Such benefits should provide linguistic studies with more accurate, more comprehensive, and more practical research outcomes.
3.11.3.3 Simulations of Linguistic Features for
In GIS, tools have been developed in association with computational simulations to help better understand how certain geographical phenomena change in space and over time. For example, how urban areas expanded in space and over time had been studied by applying cellular automation (CA) with raster-based land use data that typically come from remotely sensed data. CA is a rule-based simulation approach. It assumes that the study area is divided into a fine rectangular grid of square cells. CA first defines each cell and its “state” and then proceeds to simulate how cells in the grid will change their states based on a set of predefined rules. Such simulations allow analysts to observe the overall patterns of how spatial clusters of cells with similar or distinct states evolve over time.
In a similar fashion, agent-based models (ABMs) can be constructed to simulate how elements in a system change and interact among one another. For example, ABMs have been applied to study how certain disease diffuse in space and over time. In a complex system, elements change their states and how they interact with one another according to a set of rules that are defined for their behavioral patterns. These changes are often interactive and dynamic, which are not possible for the conventional regression models to describe. In an ABM, each element is an agent. Each agent is given a set of rules that define how the agent is to change its status and how it affects other agents in different circumstances. By allowing all agents to be active simultaneously, the ABM simulates the entire system so that the overall patterns and trends can be observed.
Using computer simulations to study linguistic features and trends started approximately in early 2000s. For example, computer simulation was used to model spatial diffusion of linguistic features and the adaptive aspect of complex systems in speech and culture (Wolfram, 2002; Gilbert and Troitzsch, 2005; Miller and Page, 2007; Gilbert, 2008). In particular, linguistic researchers have built simulations to address language, such as Baxter et al. (2009), Stanford and Kenny (2013), Blythe and Croft (2009), Ellis and Larsen-Freeman (2009), and Kretzschmar and Juuso (2014).
These articles adapted methods from computer science by attempting to model language as the selection of a particular variant as part of a grammar. Although grammar is not the direct output of the complex linguistic systems, these simulations skipped to rule-based regularity in grammatical constructions at the level of the entire language. Both ABM and CA have been used in simulations of linguistic data. As a result, computer-assisted research in linguistic advanced beyond the traditional analysis by drawing isoglosses to visualize spatial features of linguistic data or by applying statistical summaries of linguistic data for digesting linguistic trends. Linguistic research, with computer simulations, enables us to visualize spatial patterns of languages and to understand how languages evolve in different environments and at different time.
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