Dataset Card for Russia Ukraine Conflict

  Dataset Summary

Context

On 24 February 2022, Russia invaded Ukraine in a major escalation of the Russo-Ukrainian War that began in 2014. The invasion caused Europe's largest refugee crisis since World War II, with more than 6.3 million Ukrainians fleeing the country and a third of the population displaced (Source: Wikipedia).

Content

This dataset is a collection of 407 news articles from NYT and Guardians related to ongoing… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/russia-ukraine-conflict-articles.

The face-to-face survey was conducted by the Ilko Kucheriv Democratic Initiatives Foundation in cooperation with the Centre for Political Sociology from 5 to 15 June 2023.

A total of 2,001 respondents aged 18 or older took part in the survey in Vinnytsia, Volyn, Dnipropetrovsk, Zhytomyr, Zakarpattia, Zaporizhzhia, Ivano-Frankivsk, Kyiv, Kirovohrad, Lviv, Mykolaiiv, Odesa, Poltava, Rivne, Sumy, Ternopil, Kharkiv, Kherson, Khmelnytskyi, Cherkasy, Chernihiv, and Chernivtsi regions, and the city of Kyiv (in Zaporizhzhia, Kharkiv, and Kherson regions – only in the territories controlled by Ukraine and not affected by hostilities).

The sampling technique used in the survey is multi-stage, with a random selection of localities in the first stage and a quota-based selection of respondents in the final stage. The random selection is representative of the demographic structure of the adult population in the areas covered by the survey at the beginning of 2022.

The maximum sampling error shall not exceed 2.3%. At the same time, it is necessary to take into account systematic deviations in the sample caused by the forced migration of millions of citizens due to the Russian-Ukrainian war.

COMPOSITION OF MACRO-REGIONS: West – Volyn, Zakarpattia, Ivano-Frankivsk, Lviv, Rivne, Ternopil, and Chernivtsi regions; Center – Vinnytsia, Zhytomyr, Kyiv, Kirovohrad, Poltava, Sumy, Khmelnytskyi, Cherkasy, and Chernihiv regions, and the city of Kyiv; South – Zaporizhzhia, Mykolaiiv, Kherson, and Odesa regions; East – Dnipropetrovsk and Kharkiv regions.

This dataset contains the original survey data. The SPSS file (.sav) is the original file. It has been exported to an Excel file. The content of the corresponding XLSX file should be identical to the original SAV file. The SAV file contains the questions and answer options of the original questionnaire in Ukrainian. The original questionnaire and an English translation have also been included in this data collection as separate PDF files.

In addition, the dataset includes a file of "selected findings", which documents some of the key findings of the survey in the form of analytical summaries and descriptive statistics. The report was prepared by the civil society organisation OPORA.

This dataset contains data from the experiment and python code for the project titled “Love or politics? Political views regarding the war in Ukraine in an online dating experiment”.

Paper abstract: Political views affect various behaviors, including relationship formation. This study conducts a field experiment on a large Russian dating site and gathers data from over 3,000 profile evaluations. The findings reveal significant penalties for those who express pro-war or anti-war positions on their dating profiles. Age emerges as the most polarizing factor: younger individuals are less likely to approach pro-war profiles but not anti-war ones, whereas older individuals are less likely to respond positively to profiles indicating anti-war views but not pro-war ones. The results align with survey evidence of a positive relationship between respondents' age and expressed support for the war in Russia, although the experiment indicates a higher degree of polarization. Overall, the experimental findings demonstrate that survey data can reveal trends and relationships between individuals' characteristics and their opinions, but may overstate the levels of support for government agendas in non-democratic states.

The experiment was conducted in October - November, 2022, on a large online dating site in Russia in three Russian regions: Moscow, Saint Petersburg, and Sverdlovskaya oblast. There are three separate data files, one for each region. Each file contains information on dating site users that have been liked by and/or have viewed the experimental profiles.

File ExperimentDataMainLikedUsers.csv contains data on the main sample of liked users. The hair color of these users was recorded from profile photos whenever possible. Weights have also been added to enable analysis with adjustment for differences in age distribution between dating site users and a subset of the Russian population that shares similar observable characteristics.

The folder also contains python code for data analysis.

The description of the study is available at https://mpra.ub.uni-muenchen.de/120731/

Russia is the largest natural gas supplier to the EU. The invasion of Ukraine was followed by a cut-off of gas supplies from Russia to many EU countries, and the EU is planning to ban or dramatically reduce its dependence from Russia. To quantify the magnitude of the Russian gas used for different countries and sectors and the potential solutions to the Russian gas gap, we provide two daily resolution datasets: 1) EU27&UK daily gas supply-consumption (EUGasSC), and 2) EU27&UK daily gas reduction potential (EUGasRP). EUGasSC (from 2016-2022) provides the country- and sector-specific natural gas supply-storage-consumption (including Russian Supply Share) in the EU27&UK at a daily resolution, which is aimed to quantify the shortfalls if Russian imports were to stop. EUGasRP (for 2021) shows the maximal daily gas conservation potentials estimated by reducing demand for heating and/or increasing power generation from other sources, i.e., coal, nuclear, and biomass. They can be used as either input or reference datasets for further research in various fields, such as gas/energy modeling, carbon emission, climate change, geopolitical policy discussions, and the international gas/energy market. The units of the two datasets are KWh.

Preprint of our paper: https://essd.copernicus.org/preprints/essd-2022-246/

Website of our datasets: https://eugas.herokuapp.com/

Github of our work: https://github.com/chuanlongZhou/russia_gas_essd.git

The EUGasSC dataset was developed with a gas network flow simulation based on flow mass balance by combining data from multiple datasets including ENTSO-G, ENTSO-E, and Eurostat energy balance (annual and monthly). The EUGasSC dataset was validated with BP Statistical Review of World Energy and multiple Eurostat datasets. The EUGasSC shows the share of gas supplied by Russia in each country to analyze the ‘gap’ that would result from a stop of all Russian exports to Europe.

The EUGasRP is developed for the potential solutions to fill the Russian gap in the EU27&UK. We analyze gas reductions for reducing demand for heating and increasing power generation from other sources, i.e., coal, nuclear, and biomass, that can substitute the gas.

For the heating sector, we analyze reduction scenarios for weekdays and weekends of household and public buildings. The reduction estimations are based on empirical temperature-gas-consumption (TGC) curves based on population-weighted air temperatures using the Eurostat population dataset and ERA5 daily 2-meters air temperature data. The values provided in EUGasRP assume the following reduction scenarios: 1) households on weekdays adopt a 2 °C lower critical temperature and follow the lower 20th percentile of TGC curves to define the slope, 2) households on weekends adopt a 2 °C lower critical temperature and the lower 40th percentile of TGC curves, and 3) public buildings adopt a 4 °C lower critical temperature and the lower 20th percentile of the TGS curve.

For the power sector, we assume that the electricity generated with gas can be substituted by boosting the hourly electricity generated with coal, nuclear, and biomass to certain observed higher levels. We estimate the observed higher levels by95% (as maximal gas reduction) of the maximum observed diurnal hourly capacities for coal, nuclear, and biomass for each country based on observed ENTSO-E electricity production data from 2019 to 2021.

We also provide further discussions in our paper for 1) uncertainties of the two datasets, 2) the moderate scenarios for gas reductions, 3) transferring gas savings from countries with surplus to those with deficits, and 4) increasing imports from other countries like Norway, the US, and Australia from either pipelines or LNG. Based on our analysis, we argue that with plausible demand reductions, shifts in power generation towards nuclear and coal, and intra-EU and international coordination, particularly with the UK, the US, Australia, and Norway, it should be possible for the EU to make up for the sudden loss of Russian gas.

This merged dataset contains data on self-assessed happiness, collected through nationwide representative surveys conducted by the Kyiv International Institute of Sociology (KIIS) among the adult population of Ukraine in the period from 2001 to 2024. Happiness is measured using the question, "Do you consider yourself a happy person?" with five response options: "yes," "rather yes than no," "both yes and no," "rather no than yes," and "no." This question has been included in KIIS omnibus surveys since 2001, typically on an annual basis. However, in certain years (2003, 2004, 2019, and 2020), this question was not tracked, so data for those years are unavailable. The dataset combines data from 25 individual survey waves. All those surveys were carried out with samples representative of Ukraine's adult population (18 years and older), with an average sample size of around 2,000 respondents for each wave between 2001 and 2021, and approximately 1,000 respondents per wave between 2022 and 2024. In addition to the primary happiness data, the dataset includes socio-demographic variables such as gender, age, education, nationality, occupation, self-assessment of financial situation, and place of residence (oblast, type of settlement). These data allow for tracking changes in subjective well-being over time and exploring some of the factors that influence it, both at the national level and within different population groups. The data is available in an SAV format (Ukrainian, Russian, English) as well as a converted CSV format (with a codebook). The Data Documentation includes a short overview and discussion of survey results (with tables in Annex 1).

This data collection offers a representative omnibus survey of the Ukrainian population, living in territories controlled by the Ukrainian government without ongoing armed hostilities. The survey was conducted by the Ilko Kucheriv Democratic Initiatives Foundation together with the sociological service of the Razumkov Center from 09 to 15 August 2023. The survey was conducted using a stratified multi-stage sample. The structure of the sample reflects the demographic structure of the adult population of the surveyed territories as of the beginning of 2022 (by age, gender, type of settlement). 2019 respondents aged 18 and older were interviewed. The theoretical sampling error does not exceed 2.3%. At the same time, additional systematic sample deviations may be caused by the consequences of Russian aggression, in particular, the forced evacuation of millions of citizens. The survey covers five thematic fields: assessment of the current situation in the country, the Russian war of aggression, energy sector, corruption, volunteering. This data collection contains the original survey data. The SPSS file (.sav) is the original file provided by the Ilko Kucheriv Democratic Initiatives Foundation. It has been exported into an Excel file. The content of the respective xlsx-file should be identical with the original sav-file. The sav-file contains the questions and answer options of the original questionnaire in Ukrainian. The original questionnaire and an English translation are also included in this data collection as separate pdf-file. Additionally, the data collection contains three files with "selected results" which document some major results of the survey in the form of analytical summaries and descriptive statistics: two in English, covering assessment of the current situation in the country + the Russian war of aggression as well as volunteering; one in Ukrainian covering corruption. New in version 1.1: The numbering of questions in the separate questionnaire (file "DIF_CR_0823-questionnaire-revised.pdf") has been adjusted to the numbering in the original data file ("DIF_CR_0823.sav"). A third file with "selected results" has been added. New in version 1.2: An English translation of the questionnaire has been added under "files". Method(s) of data collection: Public Opinion PollMethod(s) of data analysis: Descriptive Statistics Published on Discuss Data, https://discuss-data.net/dataset/3f4a566d-8e85-4f7d-916a-99bd35896b57/

Opinion data from Hungary, Bulgaria and Latvia (including the Russian-speaking minority).

This survey focuses on relations with and attitudes towards Russia in three East European countries with a record of close ties with Russia – Latvia, Hungary, and Bulgaria. The survey was carried out against the backdrop of Russia´s annexation of Crimea and Eastern Ukraine. It may be the very first survey to tap East European reactions to Russia’s drastic attempt to redraw the map of post-war Eastern Europe. The 2015 Post-Crimea Survey asks many of the key questions in the Baltic Barometer questions about identity, democracy, and the European Union (Baltic Barometer 2014).

Representative samples of populations in Estonia, Latvia and Lithuania. This is our follow-up survey (from 2014) in the three Baltic countries but without additional sampling of their respective Russian speaking minorities. Special focus is on the handling of the covid pandemic in the Baltic countries, but the survey also covers attitudes towards the EU, migration, democracy, and Russia against the backdrop of its aggression in Ukraine.