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Dialect atlases comprise considerable numbers of linguistic feature maps, i.e. dialect maps representing one linguistic feature each. Large amounts of data like these are often difficult to handle. This article presents a new quantitative method for the automatic analysis of such large corpora of linguistic feature maps. It makes use of geographical similarities between single maps to establish a system of criteria for structural relatedness. Furthermore, it employs statistical techniques to test whether given linguistic relations between the maps coincide significantly with structural relations. To achieve this, each underlying point-symbol map is converted into an area-class map (with all the original information still available). These area-class maps yield additional information regarding their structural composition. Cluster analysis is then employed to obtain groupings of similar maps. Such groupings facilitate the search for language-internal factors that influence the geographical distribution of linguistic variants, as the relevance of any given linguistic parameter for spatial patterns can be tested using statistical methods. Moreover, language-external factors, such as topographical conditions, can be tested in the same way. Thus, this new method allows for a profound and substantiated investigation of the regularities that can be found in the geographical distributions of linguistic variants.

Dialectometric intensity estimation as introduced in Rumpf et al. ) and Pickl and Rumpf (2011) is a method for the unsupervised generation of maps visualizing geolinguistic data on the level of linguistic variables. It also extracts spatial information for subsequent statistical analysis. However, as intensity estimation involves geographically conditioned smoothing, this method can lead to undesirable results. Geolinguistically relevant structures such as rivers, political borders or enclaves, for instance, are not taken into account and thus their manifestations in the distributions of linguistic variants are blurred. A possible solution to this problem, as suggested and put to the test in this paper, is to use linguistic distances rather than geographical (Euclidean) distances in the estimation. This methodological adjustment leads to maps which render geolinguistic distributions more faithfully, especially in areas that are deemed critical for the interpretation of the resulting maps and for subsequent statistical analyses of the results.

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The mass literacy drives of the 19 th century have proved to be a landmark in German language history, as for the first time the majority of the people in the German-speaking countries were able to participate in the culture of writing. The full impact of the spread of writing among the lower social classes on language variation and change has, however, not yet been recognised in language historiography. With examples from grammar and spelling in private emigrant letters, the present article strongly argues for an alternative approach to language historiography, using such texts as a starting-point for a 'language history from below'.

The present contribution addresses the phenomenon of grammatical change using a historical sociolinguistic approach, which is based on the principle that systematic language change can only be described and explained by accounting for sociopragmatic and variational factors of language use. The approach is illustrated by an empirical investigation of the change of selected morphological and syntactic features in (Middle) New High German, using Labov's distinction between 'language change from above' and 'language change from below' as a starting point of analysis. The aim of the paper is to demonstrate that the historical sociolinguistic approach not only complements other methods of historical linguistics, but may also lead to results and findings that could perhaps not be achieved by other methodological approaches. Moreover, it is considered central to the description and explanation of the development of language varieties in periods of language standardisation.

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