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SUMMARY:Using Counter-Modellings analysing narratives about places of unsa
 fety in Recife\, Brazil - Dominik Kremer
DTSTART;TZID=Europe/Amsterdam:20240926T153000
DTEND;TZID=Europe/Amsterdam:20240926T160000
DTSTAMP:20261012T024013Z
UID:pretalx-spathum24-KU8GGA@pretalx.com
DESCRIPTION:In the context of crisis discourses\, corpus linguistic analys
 is of language use patterns are worthwhile in order to understand how cris
 es are linguistically bound (Bubenhofer\, 2009\; Kremer and Walker\, 2023)
 . This concerns acute crises such as diseases (Semino et al.\, 2004) or pa
 ndemics (Kremer and Felgenhauer\, 2022)\, but also everyday experiences of
  unsaftey in urban spaces (Moura de Souza et al.\, 2022). Metaphors of fig
 hting the crisis (Semino\, 2021) imply a search for places of the crisis (
 Brinks and Ibert\, 2020) in order to identify\, control and combat effects
  and causes (Chapman and Miller\, 2020). When it comes to the question of 
 experienced unsafety in everyday life\, it is known from conceptual social
  sciences that they are modelled best as fluid spaces (Redepenning et al.
 \, 2010)\, which reflect forms of mobility as well as constantly changing 
 situations (Moura de Souza et al.\, 2022). Even when the virus had already
  penetrated the population during the COVID-19 pandemic\, the question of 
 a spatial origin\, the "hotspots"\, still played a decisive role in the se
 arch for causes (Kremer and Felgenhauer\, 2022). Interestingly\, however\,
  media repertoires have developed in everyday discourses on unsafety that 
 address this need non-cartographically in a mixture of social media and cl
 assic unidirectional TV broadcasts (Moura de Souza et al.\, 2022) and thus
  may represent a more suitable data basis for the analysis of unsafety tha
 n their mere visualization bound to map-based data.\n\nIn the search for s
 hared "imaginaries" (Taylor\, 2004)\, the dominant guiding metaphors (Lako
 ff and Johnson\, 2003) and narratives (Viehöver\, 2001) of everyday place
 s\, focus in Digital Spatial Humanities is directed towards multimodal ana
 lysis of imagery (Rose\, 2001) and text data (Mayring\, 2016). Supported b
 y digital analysis methods\, certain structural findings are available for
  the first time (Jannidis et al.\, 2017\; Moretti\, 2013).  In the traditi
 on of critical data studies (Dalton and Thatcher\, 2014\; Kitchin and Laur
 iault\, 2014)\, however\, it has become established to interrogate such re
 search-based digital representations and data collections as apolitical sp
 aces (Iliadis and Russo\, 2016)\, to systematically scrutinize power\, sur
 veillance and control in the supposed decision support and\, if necessary
 \, to help underrepresented interests gain more visibility through counter
 -data (Dalton and Thatcher\, 2014) (Iliadis and Russo\, 2016). Dominant pe
 rspectives (Kitchin and Lauriault\, 2014)  manifest themselves - either un
 consciously through the organizational structure of the data or consciousl
 y as part of a previously developed information architecture of a project 
 - as data and information modelling. In analogy to _counter-data_\, we thu
 s see our approach of what we call concept space analysis as an opportunit
 y to systematically examine data modeling and its social production condit
 ions not only ex-post\, but complementarily in the sense of _counter-model
 ing_ (Kremer/Lang in print) even before their development at the beginning
  of projects in terms of texamining alternative explanatory approaches.\n
 \nWe illustrate our workflow using the example of a study on place-based n
 arratives about perceived safety in different stakeholder groups in the ci
 ty of Recife\, Brazil (Moura de Souza et al.\, 2022). A general **workflow
 ** can be derived (Kremer/Lang in print)\, which can be explored increment
 ally in order to obtain complementary answers to research questions:\n\n1 
 **Identify theoretical approach:** Which different theoretical approaches 
 can be applied to the research question in principle? Which spatial terms 
 are used to refer to the question from a technical point of view? What are
  the basic assumptions?\n\n2 **Analyze conceptual space:** Which spatial c
 oncepts should be used to make structures visible on the data in an explor
 ative manner ? \n\n3 **Develop appropriate data modelling:** In which data
  schemas should the spatial data be organized? Which explorative data anal
 yses can be applied to appropriately evaluate the validity of the investig
 ated spatial theory approaches with respect to the given research question
 ?
LOCATION:MG1 00.04 Hörsaal
URL:https://pretalx.com/spathum24/talk/KU8GGA/
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