Robyn Naisbitt

We have recently made a dataset on Airbnb rentals and reviews across London and Leeds available via our safeguarded service.  The dataset, which is supplied by AirDNA LLC, contains 125 data points for over 200,000 Airbnb rentals across London and Leeds to provide unique insights into the performance of each property and host.

The dataset includes:

• Total historical data (monthly and daily listing performance) for London and Leeds
• Total host data for London and Leeds
• Property data for London and Leeds
• Total review data for London and Leeds

Further information, including detail on the quality and temporal extent, is available in the data profile.

Applying to access

These data are classified as Safeguarded and are available via application only.  You can find out more about the application process or make an initial application on the CDRC website.

About AirDNA

AirDNA provides data and analytics to vacation rental entrepreneurs and investors.  By tracking the daily performance of over 4.5 million listings across 60,000 markets worldwide, AirDNA presents market reports and other data products that feature occupancy rates, seasonal demand, and revenue generated by short-term rentals.

The Consumer Data Research Centre (CDRC) are delighted to announce that our student, Alyson Lloyd, passed her PhD viva!

Dr Lloyd’s thesis – “The Applications of Loyalty Card Data for Social Science” – looked at the applications of loyalty card data in population research and the extent to which insights can be inferred about people and places from consumer activity patterns.

Examiners Prof Alex Singleton (University of Liverpool) and Dr Adam Dennett (University College London) were hugely impressed by the amount of data processing and analytical work that went into Alyson’s thesis, whose research has already had a big impact on the way the CDRC deploy consumer data in research.

Alyson is also in high demand in the retail industry, where she now works as an analyst for the fashion retailer, ASOS.

Congratulations to Dr Lloyd!

CDRC’s Map of the Month for July 2018 is a map of Consumer Vulnerability, showing a geodemographic classification developed by CDRC in Leeds.

Some consumers are more vulnerable to marketing practices due to their personal traits such as age, health or household makeup. This vulnerability varies by product and industry. Consumer vulnerability here is defined as the risk that a consumer’s mental, physical or financial welfare may be damaged when engaging in a market interaction.

While consumer vulnerability has been discussed at length in academic literature and regulatory guidelines, there has not been a comprehensive geographical assessment of consumer vulnerability in the United Kingdom. This study creates a geodemographic classification of consumer vulnerability at output area level.

The interactive map is available to browse here.

Further details about the work, including the methodology and the data itself, is available here.  This work was completed by Michael Adcock, alongside Nik Lomax and Stephen Clark, as part of his internship at Leeds Institute for Data Analytics.

Download these data.

CDRC Director Professor Paul Longley represented the ESRC Consumer Data Research Centre (CDRC) when delivering a keynote at the XVIII Congreso Nacional de Tecnologías de la Información Geográfica, Valencia, Spain, 20-22 June 2018.

His talk addressed aspects of consumer data analytics and was received extremely well by the delegates. It is hoped that further collaborations with Spanish researchers will develop in the future.

During the keynote, Paul discussed the newly published CDRC book, ‘Consumer Data Research’, and ways in which it seeks to provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors. The book can also be accessed as a free open access eBook at www.cdrc.ac.uk/book.

Further information about the conference is available here.

The open access Geospatial Analysis free web resource and online ebook, www.spatialanalysisonline.com (6^th edition, authored by Mike de Smith, Prof Paul Longley, Prof Mike Goodchild and colleagues) has been completely re-built and updated, with new material and up-to-date interactive links. An online web-based resource, it provides a comprehensive guide to concepts, methods and tools, with many examples being provided using a variety of popular software tools such as ArcGIS, Idrisi, Grass, Surfer and others.

This is the first update since 2015, with the latest version featuring significant inputs from the Consumer Data Research Centre (CDRC); these include an extended chapter on Big Data and Geospatial Analysis, primarily authored by CDRC Researcher Guy Lansley, as well as links to key CDRC resources, including our popular Online Tutorials and the CDRC book ‘Consumer Data Research‘.

A 60 page extract of the special PDF version can be obtained here.

Course tutors can request a free copy of the material in electronic format (printable) for offline use by emailing [email protected].

In addition to the online version, there are special printable and non-printable PDF offline versions and a printed version (colour cover, mono interior, 618pp) has been made available via Amazon’s KDP service.

We are pleased to announce the release of our book entitled ‘Consumer Data Research’.

Edited by CDRC Director Paul Longley and Deputy Directors’ James Cheshire and Alex Singleton, the book offers a unique and innovative series of case studies that demonstrate the enormous potential of consumer data research in the academic, commercial and government sectors. It also provides a timely snapshot of key research undertaken by the CDRC and features contributions that originate from CDRC led projects and data products.

Published by UCL Press, the full book is also available as a free open access edition online, accessible here.

‘Consumer Data Research’
Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. This book provides a first consolidated statement of the enormous potential of consumer data research and is a timely appraisal of the ways in which consumer data challenge scientific orthodoxies.

The Consumer Data Research Centre (CDRC) collaborated with GISRUK to host a data challenge.

Delegates were asked to develop a novel analysis or visualisation of CDRC and associated data in order to investigate the hypothesis set out in the Economist article “The immigration paradox Explaining the Brexit vote”, which argued the rate of change in number of migrants in an area rather than the total headcount influenced the Brexit vote.

We honed in on four finalists who presented their papers at GISRUK 2018 on 17 April and the winning paper announced on 19 April. A summary of the event – including reasons for selecting the winning paper – can be found here.

You can access each individual paper below:

Paper 1: Winning paper:
Title: SpaCular – Disclosure of spatial peculiarities of the Brexit
Authors: Joao Porto De Albuquerque (University of Warwick) , Konstantin Klemmer (University of Warwick) , Rene Weserholt (University of Heidelberg), Andra Sonea (University of Warwick)
Abstract: Immigration has consistently rated as the most important issue the UK faces, to a much higher degree than the average in the EU, despite UK not being among the EU countries with the highest share of foreign born or with the highest increase in foreign born population. Whilst the UK experienced, between 2002-2015, a 76% increase in immigration, at closer inspection data contradicts the stereotypical image of the immigrant so much misused during the Brexit vote: 47% of UK immigrants in the 15-64 age range have tertiary education, the highest proportion highly qualified immigrants by far among all EU countries. Additionally, non-European immigration consistently formed the majority of the immigration even after the A2 EU accession in 2007.

Paper 2:
Title: Tension Points: A Theory & Evidence on Migration in Brexit
Author: Levi John Wolf, University of Bristol
Abstract: The GISRUK Data Challenge asked: was Brexit primarily driven by the rate of change in migration, rather than the total headcount? To interrogate this, I used local regression methods, hierarchical models, migration data provided by the Office of National Statistics, and a novel method to extract population volatility from fine-grained Consumer Data Research Centre Data. Depending on the implicit hypothesis used to operationalize the contest question, I find Brexit voting at local authority level was driven in part by the rate of change in their population structure, but some types of change drove Leave voting and some drove Remain.

Paper 3:
Title: Rapid change in ethnic composition – part of a wider Brexit picture?
Authors: Edward Abel et al, University of Manchester
Abstract: Correlations have been reported by The Economist between a 13 year rate of change in the proportion of foreign born individuals in UK local areas and voting in the 2016 European referendum. Using regression and principal components analysis, we confirm the significance of rate of change in ethnic diversity, driven by a change in White British, White Other and Black populations. This varied by region, and the time window used for comparison also significantly impacts model results. Superficial correlations between change in Asian and Black populations and ‘leave’ voting were eliminated by including model variables linked to urban living. Age composition, turnout and population density all had smaller effect sizes than changes in ethnic composition.

Paper 4:
Title: Investigation of the impact of changes in ethnic mix on the EU referendum result
The authors have requested for the CDRC to not publish this paper in order for it to be progressed into a journal paper. 
Author: Aihua Zhang and Paul King, University of Leicester
Abstract: The Economist article “The immigration paradox Explaining the Brexit vote” (14 July 2016) argues that the rate of change in the number of migrants in an area, rather than the total headcount influenced the Brexit vote. This argument, however, was simply made by looking at the individual factor of ‘foreign-born’ (or ‘UK-born’) population in isolation, with no formal analysis. By contrast, in her recent research paper published in World Development (Volume 102, February 2018), Zhang applied two statistical analyses (Multivariate Regression and Logit Regression) to the actual referendum voting data obtained from the Electoral Commission and the UK’s latest census data. She found that the impact of the factor of ‘UK-born’ (and thus ‘foreign-born’) population proportions on the EU referendum results was insignificant, while other factors, such as, Higher Education, Turnout, Gender dominated the impacts on the outcome of the EU referendum. To address the question of ‘whether the rate of change in number of migrants in an area influenced the Brexit vote’, we apply the two aforementioned statistical approaches to the CDRC geographical dataset of 11 ethnicity categories that are mapped to the referendum results by Local Authority district or Council Area. Total headcount /level of immigration had no significant impact on the Brexit vote; the rate of change in ethnic mix had some minor impact on the referendum result;Areas in England and Wales with higher increase rates of British Chinese populations tended to vote Remain.

CDRC and LIDA Intern Natacha Chenevoy recently received an award from the International Association of Law Enforcement Intelligence Analysts (IALEIA) for her work with Lancashire Constabulary on identifying online hate crime.

The award recognises individuals for outstanding contributions as intelligence analysts, investigators, or prosecutors utilising intelligence products leading to the achievement of the organisation’s objectives’

Natacha’s projects, in collaboration with Lancashire Constabulary, explored the use of social media data to identify online hate crimes.  You can read more about each project below:

Project 1: Application of Natural Language Processing for identification of online hate on Twitter

Project 2: Analysis of police-recorded hate crime in Lancashire

Natacha collected her award at the IALEIA Annual Training Event in Los Angeles, which was attended by over 700 participants from across the globe.

We invited researchers intending to register as GISRUK 2018 conference delegates to develop a novel analysis or visualisation of CDRC and associated data, in order to investigate the hypothesis set out in the Economist article “The immigration paradox Explaining the Brexit vote” that argues that the rate of change in number of migrants in an area rather than the total headcount influenced the Brexit vote. The article can be viewed here.

Issues that we asked participants to potentially address included (but by no means were limited to):

• Whether Local Authority district is the most appropriate scale at which to ground analysis
• Whether country of birth or ethnicity as defined by CDRC is the best predictor of voting behaviour
• Whether the country of birth of recent immigrants plays any role in shaping voting intentions
• Whether enfranchised members of recently arrived ethnic minority groups are themselves likely to vote for Brexit
• Whether established party political affiliations affect the share of the Brexit vote
• Whether voting behaviour varies according to other local, Regional or national circumstances.

We provided two sets of data, to form the main sources of data for the challenge:

• CDRC small area predicted ethnicity data from 1998-2017.
• A copy of the Electoral Commission’s official results of the UK’s EU referendum results, by voting area (council areas in Scotland, constituencies in England and Wales, and a single result for Northern Ireland).

Judging the challenge
In second place, and highly commended by the judges, was “Tension Points: A Theory & Evidence on Migration in Brexit” by Levi John Wolf from the University of Bristol. The judges thought this was a good conceptual work using a variety of datasets including the CDRC’s. It demonstrated a new application of a method, and was clearly constructed, convincingly modelled, showing some interesting findings and a very clear style of presentation, with the technical elements explained well and an effective results dissemination.

However, the winner, by the narrowest of margins, was “SpaCular – Disclosure of spatial peculiarities of the Brexit”, authored by Joao Porto De Albuquerque, Konstantin Klemmer (who presented), Andra Sonea, from the University of Warwick, and Rene Weserholt from the University of Heidelberg. The judges thought this paper showed good conceptual work, new application of a method, was very analytical and made good use of the CDRC-specific data, particularly through exploration of its temporal variation. The delivery of the research was clear and effective.

On winning the prize, presenter Konstantin Klemmer stated “Thank you for the opportunity to participate in this fantastic challenge and, of course, for our award! As recent news regarding the “Windrush” generation show, immigration is one of the most important political issues in the UK. As such, the task set by the CDRC data challenge was particularly fascinating to our team. With backgrounds in geography, social science and computer science, we took an interdisciplinary approach to the challenge, focusing not only on the temporal aspects of immigration, but also the spatial dimension. Our findings not only support the initial hypothesis posed by “The Economist” that change in immigrant population drove the Brexit vote, but also that the spatial composition of immigration patterns is crucial! With information about spatial variation added, we can substantially enhance the initial temporal trend model. The CDRC challenge was an overall great experience for our team and has motivated us to explore our findings further and continue our studies. Thanks again to the whole CDRC team for hosting this brilliant challenge”.

The winning Warwick/Heidelberg team share a prize of £500 and a copy of the best-selling book “London: The Information Capital”, co-authored by CDRC co-investigator and UCL senior lecturer Dr James Cheshire.

The four short papers that were shortlisted for presentation, including the winning one, will be published on the CDRC website in due course.