Data used in Chapter 3 (compromise experiments) from the 2018 UML YouGov survey.

All figures, unless otherwise stated, are from YouGov Plc. Total sample size was 2035 adults. Fieldwork was undertaken between 14th - 22nd May 2020. The survey was carried out online. The figures have been weighted and are representative of all Scotland adults (aged 18+).

The EUI-YouGov dataset on European solidarity is built on a large survey designed by the EUI 'Solidarity in Europe' research team and implemented by YouGov. The data aims to empirically assess public opinion on the willingness to redistribute resources within the EU and to examine political attitudes that might explain these preferences. The survey design covers a number of issues, particularly concerning attitudes towards European solidarity; policy preferences; satisfaction and trust in national and European institutions; attitudes towards European integration, identity, value of democracy, world politics, security and defence, Russia, NATO and a European army; preferences concerning taxes and other (social) policy priorities; the relative salience of different issues and threats facing individuals, countries and the EU; political ideology, religion and voting preferences; as well as other individual attributes such as gender and age. The survey inquired 11.288 adults over 11 EU countries (including, then, the UK) from 18 to 30 April 2018. YouGov implemented the survey online using a randomised panel sampling mechanism to ensure it is nationally representative concerning age, gender, social class, region, level of education, voting preference and level of political interest.

Data and do files are provided for the models that use this data in Chapters 3, 4 and 6.

Data and do files are provided for the models that use these data in Chapter 6.

This data was generated in conjunction with a UK study of public perceptions to different tree-breeding solutions to ash dieback. This study was a component of a wider BBSRC-funded research project that aims to develop new approaches for identifying genes conferring tolerance to Chalara.

The data was generated from a questionnaire survey adminstered by YouGov in March 2016. A second data set available on ORA relates to a similar survey of UK publics attending countryside events.

These data are being released as a preliminary version to facilitate early access to the study for research purposes. This collection has not been fully processed by ICPSR at this time, and data are released in the format provided by the principal investigators. As the study is processed and given enhanced features by ICPSR in the future, users will be able to download the updated versions of the study. Please report any data errors or problems to user support, and we will work with you to resolve any data-related issues. The American National Election Study (ANES): 2016 Pilot Study sought to test new instrumentation under consideration for potential inclusion in the ANES 2016 Time Series Study, as well as future ANES studies. Much of the content is based on proposals from the ANES user community submitted through the Online Commons page, found on the ANES home page. The survey included questions about preferences in the presidential primary, stereotyping, the economy, discrimination, race and racial consciousness, police use of force, and numerous policy issues, such as immigration law, health insurance, and federal spending. It was conducted on the Internet using the YouGov panel, an international market research firm that administers polls that collect information about politics, public affairs, products, brands, as well as other topics of general interest.

All figures, unless otherwise stated, are from YouGov Plc. Total sample size was 2035 adults. Fieldwork was undertaken between 14th - 22nd May 2020. The survey was carried out online. The figures have been weighted and are representative of all Scotland adults (aged 18+).

2 data files; 1 codebook The EUI-YouGov survey on Solidarity in Europe (2020) is a dataset containing the answers to a survey of a representative sample of more than 20,000 adults from 13 European countries and the UK. The survey has been implemented by YouGov in collaboration with the EUI. The over 70 questions cover a number of topics focused on: the concept of solidarity among EU states and beyond; response to different crises through various instruments, including the recent Covid-19 outbreak; satisfaction and trust towards governments, the EU and international actors; strength of national and European identities; value of democracy; importance and salience of various issues and threats; intention in a EU-membership referendum and other EU-related indicators including differentiated integration; world politics; left-right self-placement; gender, religion and age group; vote record in past national elections.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

YouGov (YOU) Stock Forecast: Polling the Market for Growth Potential

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Underlying data from annex B for the report that uses data from the YouGov DebtTrack surveys to update trend information about credit use and the extent of consumer indebtedness in Britain. The analysis suggests a continued decrease in the proportion of households using unsecured credit, but little change in the average amount of unsecured debt among credit users. The data also indicated a decline in the incidence of financial difficulty.

Data and replication code for the 2022 YouGov Survey and 2023 YouGov survey. For each do file, the recode file must be run before the analysis do file.

American favorability for Tesla falls to a nine-year low, despite uptick in conservative support. Sales decline in key markets, revealing challenges for Tesla.

This statistic shows the ways in which adults were introduced to the character Batman in the United States as of March 2019. Around 25 percent of respondents stated that they were first introduced to the character Batman through a live-action television series.

Research findings for the 2013 stop and search review produced by YouGov on behalf of HMIC.

Methods The SOPHIE survey was a 14-country survey developed as part of the Seas, Oceans and Public Health in Europe (SOPHIE) project funded under the EU’s Horizon 2020 Framework Programme (https://sophie2020.eu/). A total of 14,157 individuals (Mage = 46, age range: 18-99 years, 6898 men and 7269 women) participated in the survey. Country selection was based on several criteria including a desire to have at least one country with a coastline on each of the European sea/ocean basins (i.e. Atlantic, Baltic, Black, Mediterranean, North, Arctic), one landlocked country with no coastline for comparison (i.e. Czech Republic), and countries with key maritime sectors (e.g. Norway). Accordingly, the 14 countries selected were: Belgium, Bulgaria, Czech Republic, France, Germany, Greece, Republic of Ireland, Italy, the Netherlands, Norway, Poland, Portugal, Spain and the United Kingdom (which at the time of the survey was still in the EU).

The survey was administered online in March and April 2019 by international market research company YouGov using established respondent panels. Eligible participants (aged 18 and above and registered as a resident in one of the 14 countries) were invited to complete the survey by YouGov. Samples of approximately 1,000 respondents per country were stratified to be nationally representative on age, gender, and region, as per previous studies in this field (e.g. Gelcich et al., 2014). Survey questions were translated into local languages were appropriate. Where possible, established scales and items from pre-existing surveys where used (e.g. the European Social Survey (ESS, 2018)) to ensure robustness and pre-translation. The data were provided to the research team for analysis already anonymised; and ethical approval for the research was provided by the University of Exeter Medical School Ethics Committee (reference number: Nov18/B/171).

The R script The script files contain the code used to create the models, tables and figures in the paper entitled "Public preferences for policy intervention to protect public health from maritime activities: A 14 European country study". The data needed for this analysis will be released at a later date.

This dataset contains the results for France of the cross-national survey "Conspiracy Theories" commissioned by the Conspiracy and Democracy Project (CRASSH, University of Cambridge) to YouGov and fielded in nine countries: Britain, France, Germany, Hungary, Italy, Poland, Portugal, Sweden, US.

The current dataset is a subset of a large data collection based on a purpose-built survey conducted in seven middle-income countries in the Global South: Chile, Colombia, India, Kenya, Nigeria, Tanzania, South Africa and Vietnam. The purpose of the collected variables in the present dataset aims to understanding public preferences as a critical way to any effort to reduce greenhouse gas emissions. There are many studies of public preferences regarding climate change in the Global North. However, survey work in low and middle-income countries is limited. Survey work facilitating cross-country comparisons not using the major omnibus surveys is relatively rare.
We designed the Environment for Development (EfD) Seven-country Global South Climate Survey (the EfD Survey) which collected information on respondents’ knowledge about climate change, the information sources that respondents rely on, and opinions on climate policy. The EfD survey contains a battery of well-known climate knowledge questions and questions concerning the attention to and degree of trust in various sources for climate information. Respondents faced several ranking tasks using a best-worst elicitation format. This approach offers greater robustness to cultural differences in how questions are answered than the Likert-scale questions commonly asked in omnibus surveys. We examine: (a) priorities for spending in thirteen policy areas including climate and COVID-19, (b) how respiratory diseases due to air pollution rank relative to six other health problems, (c) agreement with ten statements characterizing various aspects of climate policies, and (d) prioritization of uses for carbon tax revenue. The company YouGov collected data for the EfD Survey in 2023 from 8400 respondents, 1200 in each country. It supplements an earlier survey wave (administered a year earlier) that focused on COVID-19. Respondents were drawn from YouGov’s online panels. During the COVID-19 pandemic almost all surveys were conducted online. This has advantages and disadvantages. Online survey administration reduces costs and data collection times and allows for experimental designs assigning different survey stimuli. With substantial incentive payments, high response rates within the sampling frame are achievable and such incentivized respondents are hopefully motivated to carefully answer the questions posed. The main disadvantage is that the sampling frame is comprised of the internet-enabled portion of the population in each country (e.g., with computers, mobile phones, and tablets). This sample systematically underrepresents those with lower incomes and living in rural areas. This large segment of the population is, however, of considerable interest in its own right due to its exposure to online media and outsized influence on public opinion. The data includes respondents’ preferences for climate change mitigation policies and competing policy issues like health. The data also includes questions such as how respondents think revenues from carbon taxes should be used. The outcome provide important information for policymakers to understand, evaluate, and shape national climate policies. It is worth noting that the data from Tanzania is only present in Wave 1 and that the data from Chile is only present in Wave 2.

According to a survey conducted in Britain in 2023, 49 percent of dating app users reported having a very or fairly good general user experience. Overall, 30 percent stated they had neither a good nor bad experience, and one in five users said they had a very or fairly bad general user experience.

This panel survey contains data from households located in large, coastal urban centers in the United States (Miami, Houston, and New Orleans greater areas), the Netherlands (Rotterdam greater area, Zeeland province), China (Shanghai greater area), and Indonesia (Jakarta greater area, other cities in Java). The last fifth wave of the SCALAR surveys has also covered an additional country: the United Kingdom (London, Norfolk/Suffolk coast, Somerset). China was omitted from the fifth survey wave due to the operational reasons. The surveys are focused on soliciting information on households' socio-economic background, perceptions, adaptive capacities, self-assessed resilience, place attachment, social influence, policy and other factors influencing individual climate change adaptation behavior (here contextualized to floods). The SCALAR project team has developed the questionnaires grounded in theories and best practices from the past survey literature. The surveys were conducted online by YouGov and the data presented are from identical, translated questions in the respective languages of each country. The first survey was launched in late March 2020, and a subsequent survey followed every six months for the following year and a half; in October 2020, April 2021, and November 2021. The spacing was specifically designed to allow sufficient time for the households to realize their adaptation intentions, yet still be in frequent enough intervals to encourage continued household participation. The fifth wave was conduced in July-August 2023. In this archive, you will find a subset of the data collected for each survey; 20 households in each country, for all five waves of responses.

Authors contributions: B.N., T.F. and A.N. designed the questionnaires for waves 1-4 of the survey. T.F. and T.W. designed the questionnaires for wave 5 of the survey. T.F. developed the goals of the surveys, its academic scope and format, and provided academic advice for B.N. and T.W. PhD theses. The development of the questionnaire and the analysis of the data for waves 1-4 constitute the core of the PhD project of B.N. The development of the questionnaire and the analysis of the data for wave 5 is part of the PhD project of T.W. The design, implementation and analysis of the survey was possible thanks to the ERC ‘SCALAR’ project developed and led by T.F. We are thankful to the funding from European Research Council project ‘SCALAR: Scaling up behavior and autonomous adaptation for macro models of climate change damage assessment’ (grant agreement no. 758014) under the European Union’s Horizon 2020 Research and Innovation Program.

Related publications: PhD Thesis of Dr. Brayton Noll (2023): https://repository.tudelft.nl/islandora/object/uuid%3A0d49cb3e-6dd8-4a9e-abc6-b847de938aea?collection=research

Noll, B., Filatova, T., Need, A, de Vries, P. (2023) ‘Uncertainty in individual risk judgments associates with vulnerability and curtailed climate adaptation’, Journal of Environmental Management, 325, 116462, https://pubmed.ncbi.nlm.nih.gov/36272292/

Noll, B., T.Filatova, A.Need (2022) ‘One and done? Exploring linkages between households’ intended adaptations to climate-induced floods’, Risk Analysis, 1-19, https://doi.org/10.1111/risa.13897

Noll B., Filatova, T., Need, A. & Taberna, A. (2021) ‘Contextualizing cross-national patterns in household climate change adaptation’, Nature Climate Change https://doi.org/10.1038/s41558-021-01222-3

This panel survey contains data from households located in large, coastal urban centers in the United States (Miami, Houston, and New Orleans greater areas), the Netherlands (Rotterdam greater area, Zeeland province), China (Shanghai greater area), and Indonesia (Jakarta greater area, other cities in Java). The last fifth wave of the SCALAR surveys has also covered an additional country: the United Kingdom (London, Norfolk/Suffolk coast, Somerset). China was omitted from the fifth survey wave due to the operational reasons. The surveys are focused on soliciting information on households' socio-economic background, perceptions, adaptive capacities, self-assessed resilience, place attachment, social influence, policy and other factors influencing individual climate change adaptation behavior (here contextualized to floods). The SCALAR project team has developed the questionnaires grounded in theories and best practices from the past survey literature. The surveys were conducted online by YouGov and the data presented are from identical, translated questions in the respective languages of each country. The first survey was launched in late March 2020, and a subsequent survey followed every six months for the following year and a half; in October 2020, April 2021, and November 2021. The spacing was specifically designed to allow sufficient time for the households to realize their adaptation intentions, yet still be in frequent enough intervals to...