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

Deriving age and gender from forenames for consumer analytics

This paper explores the age and gender distributions of the bearers of British forenames and identifies key trends in British naming conventions. Age and gender characteristics are known to greatly influence consumption behaviour, and so extracting and using names to indicate these characteristics from consumer datasets is of clear value to the retail and marketing industries. Data representing over 17 million individuals sourced from birth certificates and market data have been modelled to estimate the total age and gender distributions of 32,000 unique forenames in Britain. When aggregated into five year age bands for each gender, the data reveal distinctive age profiles for different names, which are largely a product of the rise and decline in popularity of different baby names over the past 90 years. The names database produced can be used to infer the expected age and gender structures of many consumer datasets, as well as to anticipate key characteristics of consumers at the level of the individual

Representing Population Dynamics from Administrative and Consumer Registers

This research attempts to derive representative metrics of household dynamics and migration by analysing changes between two annual composite registers of the UK population. Through appropriate data cleaning and linkage techniques, it is possible to match addresses and record changes in their size and composition over a two year period. The paper also demonstrates that it is feasible to approximate migration trends by filtering and matching records of household units and individuals whom are not recorded at the same address in both datasets

Using linked consumer registers to estimate residential moves in the United Kingdom

This paper argues that frequently updated data on the nature of residential moves and the circumstances of movers in the United Kingdom are insufficient for many research purposes. Accordingly, we develop previous research reported in this Journal to re-purpose consumer and administrative data in order to develop annual estimates of residential mobility between all UK neighbourhoods. We use a unique digital corpus of linked individual and household-level consumer registers compiled by the UK Consumer Data Research Centre, comprising over 143 million unique address records pertaining to the entire UK adult population over the period 1997–2016. We describe how records pertaining to individuals vacating a property can be assigned to their most probable residential destination, based on novel methods of matching names, assessing household composition, and using information on the date and probable distance of residential moves. We believe that the results of this analysis contribute highly granular, frequently updated estimates of residential moves that can be used to chart population-wide outcomes of residential mobility and migration behaviour, as well as the socio-spatial characteristics of the sedentary population

Using linked consumer and administrative data to model demographic changes in London’s city fringe

This unique book demonstrates the utility of big data approaches in human geography and planning. Offering a carefully curated selection of case studies, it reveals how researchers are accessing big data, what this data looks like and how such data can offer new and important insights and knowledge

Food and nutrition security in the Barotse floodplain system

The CGIAR Research Program on Aquatic Agricultural Systems (AAS) is being implemented in ten communities in the Barotse floodplain of Zambia’s Western Province. With a focus on the rural poor and vulnerable, the AAS program aims to reduce poverty and improve food security by harnessing the development potential, productivity and diversity of aquatic and agricultural systems. The development challenge in the Barotse floodplain, as identified by relevant stakeholders, is to make effective use of seasonal flooding patterns and natural resources through more productive and diversified aquatic agricultural management practices that improve the lives and livelihoods of the poor and vulnerable. Food and nutrition are essential to support the overall AAS program objective and overcome the specific development challenge of the Barotse floodplain. Zambia has very high malnutrition rates, particularly for stunting in children under five. Poor nutritional status, especially of women and children, inhibits individual growth and development, and negatively impacts the overall health, productivity and economic potential of a community. The purpose of this report is to analyze the food and nutrition security situation within the Barotse floodplain. It explores multiple sectors, including nutrition, agriculture, health, and gender, at the national, provincial and community level to provide a comprehensive understanding of food and nutrition in the ten AAS communities in relation to the country as a whole. The analysis will provide informative inputs to the AAS Barotse hub design process to develop an appropriate food and nutrition research-in-development agenda

Deduction with XOR Constraints in Security API Modelling

We introduce XOR constraints, and show how they enable a theorem prover to reason effectively about security critical subsystems which employ bitwise XOR. Our primary case study is the API of the IBM 4758 hardware security module. We also show how our technique can be applied to standard security protocols