Semantic map: the case of Ústí nad Orlicí

Abstract

The paper presents a method of creating a semantic map which follows up the tradition of mental mapping. The first step in the construction of a semantic map is a spatial definition of the shared image of a place/town. The second step is selection of the words and phrases that fit the shared meaning of a place/town. The third step then is their localization in the “underlying map”. The size of individual expressions indicates the frequency with which the place was named so or to what extent the designation was shared among the respondents. Then the final step is “regionalization” of the space based on semantic proximity of the words used to describe individual locations. The semantic map method is presented using the example of the town of Ústí nad Orlicí. The empirical material is based on 21 interviews conducted in the town of Ústí nad Orlicí between January and September 2013.

To fear or not to fear? Exploring the temporality of topophobia in urban environments

“…According to Frantál et al (2017, p. 238) "mental mapping is a valuable tool for understanding how humans perceive and reflect their environment". The convenience of the mental mapping application in data collection from urban space research has been demonstrated in case studies from all over the world, regardless of the type of research: it can be a systematic way to study the meanings of places (Osman, 2016); an expansion of creative industry in a city (Brennan-Horley, 2010); a contribution from its inhabitants to a city's development (Ghioca, 2014); or the identification of places identified as causing fear (Curtis, 2012).…”

Mapping topo-ambivalent places for the purposes of strategic planning of urban space. The case of Šternberk, the Czech Republic

“…Such a way of visualising a map reflects the characteristics of a socially constructed space through the interconnection of mental mapping and the linguistic meaning of the respondents' verbal declarations. Thus, it is possible to analyse the meanings with which specific places are associated and to produce semantic places based on their semantic proximity (Osman, 2016). The semantic map of the town of Šternberk contains nine semantically ambivalent places (see Main Map), which are based on the identified topo-ambivalent places (Table 2).…”