Geodemographic Segmentation

Troy, Austin

doi:10.1007/978-0-387-35973-1_456

Cited by 20 publications

(7 citation statements)

References 8 publications

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“…Of special interest here are geodemographic analyses (Troy, 2008) that draw upon a broad range of census or other kinds of profiling data to create sketches of people living in areas with particular ecological characteristics (Grove et al, 2006); as well as analyses of the wildland-urban interface and concurrent expansion of urban environments. These studies more closely correspond to the more magnified levels of ecological landtype and landtype phase in the ecological hierarchy on which this study is based-levels at which local conservation management and planning may be conducted and implemented (Radeloff et al, 2000(Radeloff et al, , 2001Jobin et al, 2003;Jackson et al, 2004).…”

Section: Resultsmentioning

confidence: 99%

“…This is a form of multivariate divisive partitioning that has been employed in geographic and geodemographic segmentation analyses (Troy, 2008). A robust data analysis tool for the classification of cases, CART utilizes hierarchical, treebuilding algorithms to successively partition a set of variables to be classified until a threshold of similarity in a focal or 'dependent' variable is reached.…”

Section: Identifying Prominent Social Attributes For Ecological Unitsmentioning

confidence: 99%

“…This research parallels studies that employ geodemographic segmentation, a multivariate statistical classification technique for discovering whether the individuals of a population fall into different groups by making quantitative comparisons of multiple characteristics (see, for example, Troy, 2008). Such studies thus examine population characteristics set within a spatial context by combining geographic and demographic variables.…”

Section: Introductionmentioning

confidence: 96%

See 2 more Smart Citations

Exploring linkages between people and rural landscapes at broad ecological scales

He¹,

Lewis²,

Baer³

et al. 2010

Landscape and Urban Planning

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Section: Resultsmentioning

confidence: 99%

Section: Identifying Prominent Social Attributes For Ecological Unitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

See 1 more Smart Citation

Exploring linkages between people and rural landscapes at broad ecological scales

He¹,

Lewis²,

Baer³

et al. 2010

Landscape and Urban Planning

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“…Various histories of geodemographics have been written, amongst them Birkin (1995), Sleight (2004), Harris et al (2005), Troy (2008), Singleton and Spielman (2014) and Leventhal (2016). Two origins commonly are identified.…”

Section: The Past and Present Of Geodemographicsmentioning

confidence: 99%

Putting the geography into geodemographics: Using multilevel modelling to improve neighbourhood targeting – a case study of Asian pupils in London

Harris

Feng

2016

J Market Anal

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Putting the geography into geodemographics: using multilevel modelling to improve neighbourhood targeting -a case study of Asian pupils in London. AbstractThis paper explores the use of multilevel modelling to provide a statistical framework for geodemographic analysis. It argues that combining a neighbourhood classification with a modelling approach to analysis allows the levels of the geodemographic hierarchy to be considered simultaneously, identifying those which are most appropriate to the analysis and allowing the apparent differences between neighbourhood types to be considered in regard to their statistical significance, and to the uncertainty of the estimates. The paper shows how the model can be extended to create a cross-classified multiscale model that makes better use of the locational information available and uses it to improve the efficiency of the neighbourhood targeting. The ideas are illustrated with a case study using a sample of data and the freely available London Output Area Classification to predict which neighbourhoods in London have the highest percentages of Asian school pupils. The multiscale model is shown to outperform the predictions made using geodemographics alone.

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“…These types of data sets are often used for marketing purposes (Troy, 2008). The United Kingdom's Office for National Statistics (ONS) 2 provides a range of data sets including the Output Area Classification (OAC) and Local Authority Classification (LAC) datasets.…”

Section: Data Sourcesmentioning

confidence: 99%

User profiling with geo-located posts and demographic data

Poulston

Stevenson

Bontcheva

2016

Proceedings of the First Workshop on NLP and Computational Social Science

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This paper presents a novel method for user profiling in social media that makes use of geo-location information associated with social media posts to avoid the need for selfreported data. These posts are combined with two publicly available sources of demographic information to automatically create data sets in which posts are labelled with socio-economic status. The data sets are linked by identifying each user's 'home location'. Analysis indicates that the nature of the demographic information is an important factor in performance of this approach.

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Geodemographic Segmentation

Cited by 20 publications

References 8 publications

Exploring linkages between people and rural landscapes at broad ecological scales

Exploring linkages between people and rural landscapes at broad ecological scales

Putting the geography into geodemographics: Using multilevel modelling to improve neighbourhood targeting – a case study of Asian pupils in London

User profiling with geo-located posts and demographic data

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