Modifying a Geodemographic Classification of the e-Society using public feedback

The e-Society geodemographic classification (Longley et al., 2008) categories neighbourhoods based on their engagement with new information communication technologies. This classification was launched online in 2006, and allowed users to both view and comment on the accuracy of their assigned neighbourhood Type. This paper utilises the user generated feedback on the accuracy of the e-Society classification and through external validation calculates their accuracy. The pilot methodology developed in this paper is scalable and could be repeated for any classification. We believe that this methodology gives the recipients of these classification procedures a voice that their concerns of classification accuracy can be heard

Creating Open Source Geodemographic Classifications for Higher Education Applications

This paper explores the use of geodemographic classifications to investigate the social, economic and spatial dimensions of participation in higher education. Education is a public service that confers very significant and tangible benefits upon receiving individuals: as such, we argue that understanding the geodemography of educational opportunity requires an application-specific classification, that exploits under-used educational data sources. We develop a classification for the UK higher education sector, and apply it to the Gospel Oak area of London. We discuss the wider merits of sector specific applications of geodemographics, with particular reference to issues of public service provision

The UK geography of the E-Society: a national classification

It is simplistic to think of the impacts of new information and communication technologies (ICTs) in terms of a single, or even small number of, 'digital divides'. As developments in what has been termed the ?e-society? reach wider and more generalisedaudiences, so it becomes appropriate to think of digital media as having wider-ranging but differentiated impacts upon consumer transactions, information gathering and citizen participation. This paper describes the development of a detailed, nationwide household classification based on levels of awareness of different ICTs; levels of use of ICTs; andtheir perceived impacts upon human capital formation and the quality of life. It discusses how geodemographic classification makes it possible to provide context for detailed case studies, and hence identify how policy might best improve both the quality and degree ofsociety?s access to ICTs. The primary focus of the paper is methodological, but it alsoillustrates how the classification may be used to investigate a range of regional and subregional policy issues. This paper illustrates the potential contribution of bespoke classifications to evidence-based policy, and the likely benefits of combining the most appropriate methods, techniques, datasets and practices that are used in the public and private sectors. It is simplistic to think of the impacts of new information and communication technologies (ICTs) in terms of a single, or even small number of, 'digital divides'. As developments in what has been termed the ?e-society? reach wider and more generalisedaudiences, so it becomes appropriate to think of digital media as having wider-rangingbut differentiated impacts upon consumer transactions, information gathering and citizen participation. This paper describes the development of a detailed, nationwide household classification based on levels of awareness of different ICTs; levels of use of ICTs; and their perceived impacts upon human capital formation and the quality of life. It discusses how geodemographic classification makes it possible to provide context for detailed case studies, and hence identify how policy might best improve both the quality and degree of society?s access to ICTs. The primary focus of the paper is methodological, but it also illustrates how the classification may be used to investigate a range of regional and subregional policy issues. This paper illustrates the potential contribution of bespoke classifications to evidence-based policy, and the likely benefits of combining the most appropriate methods, techniques, datasets and practices that are used in the public and private sectors

Family names as indicators of Britain’s changing regional geography

In recent years the geography of surnames has become increasingly researched in genetics, epidemiology, linguistics and geography. Surnames provide a useful data source for the analysis of population structure, migrations, genetic relationships and levels of cultural diffusion and interaction between communities. The Worldnames database (www.publicprofiler.org/worldnames) of 300 million people from 26 countries georeferenced in many cases to the equivalent of UK Postcode level provides a rich source of surname data. This work has focused on the UK component of this dataset, that is the 2001 Enhanced Electoral Role, georeferenced to Output Area level. Exploratory analysis of the distribution of surnames across the UK shows that clear regions exist, such as Cornwall, Central Wales and Scotland, in agreement with anecdotal evidence. This study is concerned with applying a wide range of methods to the UK dataset to test their sensitivity and consistency to surname regions. Methods used thus far are hierarchical and non-hierarchical clustering, barrier algorithms, such as the Monmonier Algorithm, and Multidimensional Scaling. These, to varying degrees, have highlighted the regionality of UK surnames and provide strong foundations to future work and refinement in the UK context. Establishing a firm methodology has enabled comparisons to be made with data from the Great British 1881 census, developing insights into population movements from within and outside Great Britain

Interpreting interpolation: the pattern of interpolation errors in digital surface models derived from laser scanning data

Errors within height models have, in the past, been communicated in terms of global measures ofaccuracy for the model. Such quantification ignores the spatial structure of errors across thesurface, hindering subsequent analysis. This paper demonstrates the importance ofunderstanding the spatial structure of error using, as an example, the creation of a DigitalSurface Model (DSM) from laser scanner data

The cultural, ethnic and linguistic classification of populations and neighbourhoods using personal names

There are growing needs to understand the nature and detailed composition of ethnicgroups in today?s increasingly multicultural societies. Ethnicity classifications areoften hotly contested, but still greater problems arise from the quality and availabilityof classifications, with knock on consequences for our ability meaningfully tosubdivide populations. Name analysis and classification has been proposed as oneefficient method of achieving such subdivisions in the absence of ethnicity data, andmay be especially pertinent to public health and demographic applications. However,previous approaches to name analysis have been designed to identify one or a smallnumber of ethnic minorities, and not complete populations.This working paper presents a new methodology to classify the UK population andneighbourhoods into groups of common origin using surnames and forenames. Itproposes a new ontology of ethnicity that combines some of its multidimensionalfacets; language, religion, geographical region, and culture. It uses data collected atvery fine temporal and spatial scales, and made available, subject to safeguards, at thelevel of the individual. Such individuals are classified into 185 independentlyassigned categories of Cultural Ethnic and Linguistic (CEL) groups, based on theprobable origins of names. We include a justification for the need of classifyingethnicity, a proposed CEL taxonomy, a description of how the CEL classification wasbuilt and applied, a preliminary external validation, and some examples of current andpotential applications

Providing clean water to rural villages

The paper is dedicated to investigate the results of a Third Party Validatioin TPV experience in Punjab. The Client, Punjab Saaf Pani Company, the State owned Authority, is allotted the task of providing fresh water to rural village

The geography of Twitter topics in London

Social media data are increasingly perceived as alternative sources to public attitude surveys because of the volume of available data that are time-stamped and (sometimes) precisely located. Such data can be mined to provide planners, marketers and researchers with useful information about activities and opinions across time and space. However, in their raw form, textual data are still difficult to analyse coherently and Twitter streams pose particular interpretive challenges because they are restricted to just 140 characters. This paper explores the use of an unsupervised learning algorithm to classify geo-tagged Tweets from Inner London recorded during typical weekdays throughout 2013 into a small number of groups, following extensive text cleaning techniques. Our classification identifies 20 distinctive and interpretive topic groupings, which represent key types of Tweets, from describing activities or informal conversations between users, to the use of check-in applets. Our motivation is to use the classification to demonstrate how the nature of the content posted on Twitter varies according to the characteristics of places and users. Topics and attitudes expressed through Tweets are found to vary substantially across Inner London, and by time of day. Some observed variations in behaviour on Twitter can be attributed to the inferred demographic and socio-economic characteristics of users, but place and local activities can also exert a considerable influence. Overall, the classification was found to provide a valuable framework for investigating the content and coverage of Twitter usage across Inner London

Un nuevo y prominente papel de los SIG y el Geomarketing en la provisión de servicios públicos

This editorial article describes how renewed and related academic interests in geodemographics, in quantitative urban analysis and in the geography of public finance are leading geographic information systems (GIS) to fulfil a central role in understanding the geographies of public service consumption. / En este artículo editorial nos gustaría ofrecer una revisión sobre la evolución de las técnicas de geomarketing en los últimos años, y describir cómo éstas, de la mano de la expansión de los sistemas de información geográfica (SIG), se han convertido en un elemento esencial para la comprensión de las geografías de consumo de los servicios públicos. Aunque este análisis se enfoca principalmente en el contexto del Reino Unido, consideramos que la mayor parte de los desarrollos, tendencias y retos que aquí se presentan, son también de central relevancia en los países de la audiencia de Geofocus