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 conflict between Russia and Ukraine. The publishing date of articles ranges from Feb 1st, 2022 to Jul 31st, 2022.

What you can do?

Here are some ideas to explore:

• Discourse analysis of Russia-Ukraine conflict (How the war has evolved over months?)
• Identify most talked about issues (refugees, food, weapons, fuel, etc.)
• Extract sentiment of articles for both Russia and Ukraine
• Which world leaders have tried to become mediators?
• Number of supporting countries for both Russia and Ukraine
• Map how NATO alliance has been affected by the war

I am looking forward to see your work and ideas and will keep adding more ideas to explore.

Russia launched its armed aggression against Ukraine in February 2014, seizing Crimea and subsequently occupying parts of the Donetsk and Luhansk oblasts of Ukraine. On February 24, 2022, Russia started a large-scale invasion of Ukraine on multiple fronts, deploying troops and shelling Ukrainian cities and infrastructure. As of the end of 2023 the war against Ukraine is still ongoing and its outcome is unknown. At different stages of the war, KIIS has studied the public opinion of the Ukrainian population regarding Russian aggression. It included surveys on people's attitudes towards the annexation of Crimea, and Ukraine's countermeasures in Eastern Ukraine (Anti-Terrorist Operation, ATO) covering the period from 2014 to 2018. Since 2022, public opinion polls have asked questions regarding people's feelings and opinions about the ongoing war between Ukraine and Russia, perceptions of the government's actions, readiness for concessions / compromises to end the war, etc. Data from individual surveys for the period 2014-2023 (14 in total) were combined into a merged dataset. Each of these polls is representative of the Ukraine's adult population (aged 18 and older), and typically includes about 2,000 respondents. The background information includes respondents' socio-demographic profiles (gender, age, education, nationality, occupation, self-assessment of financial situation) and place of residence (oblast, type of settlement). These data provide a snapshot of public opinion of the Ukrainian population on some aspects of the Russian-Ukrainian war. Some questions are repeated, which makes it possible to track changes in opinions over time.

Why I made this dataset

On the 24th of February Russia has invaded Ukraine.

Despite the fact that there were lots of speculations about the probable invasion in the press, it came as a complete shock for me as for many other Russians. It is so disgusting to start a full-scale war in the 21 century, so it was just unimaginable, no one talked about it seriously at that time. Many of us have friends and family members in Ukraine, others just want to be a part of the civil cosmopolitan world. How could our government so gruesomely attack Ukraine, destroying the lives in both countries?

But maybe it wasn't? I want to see the evolution of the discussion around Ukraine and Russia. So I parsed quite a big number of tweets. Maybe some of you will find it useful as well.

How did I collect the data.

• max 5000 for the day
• I used these words for the search ['ukraine war', 'ukraine troops', 'ukraine border', 'ukraine NATO', 'StandwithUkraine', 'russian troops', 'russian border ukraine', 'russia invade' ]
• for each search, I created the separate CSV
• dates: from 2022 - 01 - 01 to 2022 - 03 -06

Format

The dataset is available as separate CSVs files.

License

As this data was collected from Twitter, its use must abide by the Twitter Developer Agreement. Most notably, the display of individual tweets should satisfy requirements.

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 dataset is about the Ukraine-Russia war. I can be used to analyze sentiment. The next step in recognizing emotion and personality is to manually classify them.

Content

https://static4.libertatea.ro/wp-content/uploads/2022/03/slava-ukraini.jpg">

News & Events Surrounding Russia's Invasion of Ukraine from r/UkrainianConflict subreddit. Posts and comments are collected from this subrredit.

Data source and collection

Data source is: https://www.reddit.com/r/UkrainianConflict/
Data collected using praw Python package
Data is collected and merged daily

Acknowledgments

The data content is created by the Reddit contributors in this subrredit.

Inspiration

Use this data to understand the daily events of Russian invasion of Ukraine. Perform sentiment analysis for the posts and comments of this dataset. Extract the topics (using topic modelling) in the posts and comments.

Since the early 1990s, KIIS has systematically polled the question "How would you like to see Ukraine's relations with Russia?" to estimate Ukrainian preferences regarding these relations. The answer options provided to respondents were: "They should be the same as with other states - with closed borders, visas, customs"; "Ukraine and Russia should be independent but friendly states - with open borders, no visas, and no customs"; "Ukraine and Russia should unite into one state." Each survey wave was carried out on a sample representative of the Ukraine's adult population (aged 18 and older), with an average sample size of about 2,000 respondents. To facilitate analysis, the results of the individual survey waves from 1993 to 2023 were merged into a single dataset, including 82 polls with a total of 166,314 respondents. The background information includes respondents' socio-demographic profiles (gender, age, education, nationality, occupation, self-assessment of financial situation) and place of residence (oblast, type of settlement). These data enable tracking Ukrainian public opinion on what the relationship between the Ukraine and Russia should be like, from Ukraine's independence to the 2023, both among the population as a whole and among its different subpopulations.

Russia - Ukraine War Tweets

Tweets about ongoing Russia - Ukraine war

By [source]

About this dataset

This dataset consists of tweets relating to the Russian invasion of Ukraine that were scraped for this study. Only tweets of which user features were available are included in the dataset. The tweets and corresponding user features can be rehydrated using the Twitter API. However, it could be that some tweets or users might be deleted or put on private and are therefore no longer available. Moreover, user and tweet features might change over time

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

The dataset consists of tweets relating to the Russian invasion of Ukraine that were scraped for this study. Only tweets of which user features were available are included in the dataset. The tweets and corresponding user features can be rehydrated using the Twitter API. However, it could be that some tweets or users might be deleted or put on private and are therefore no longer available. Moreover, user and tweet features might change over time This dataset can be used to study the change in sentiment, and topics over time as the war continues

Research Ideas

• Find out which tweets are most popular among people interested in the Russian invasion of Ukraine
• Identify which user attributes are associated with tweets about the Russian invasion of Ukraine
• Study the change in sentiment and public opinion on the war as events unfold.

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: after_invasion_tweetids.csv | Column name | Description | |:--------------|:-----------------------| | id | The tweet id. (String) |

File: before_invasion_tweetids.csv | Column name | Description | |:--------------|:-----------------------| | id | The tweet id. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Since 2008, KIIS has been tracking public opinion in Ukraine regarding Russia by asking the question 'What is your general attitude towards Russia now?' with a 4-point scale from 'very good' to 'very bad.' To gain a deeper understanding of the situation, every few years the surveys also included additional questions about attitudes towards Russians (residents of Russia) and the Russian leadership. Each survey wave in Ukraine was carried out on a sample representative of Ukraine's adult population (aged 18 and older), with an average sample size of about 2,000 respondents. The merged dataset contains data from 49 waves of the survey conducted in Ukraine from 2008 to 2022 with a total of 98,575 respondents. The background information includes respondents' socio-demographic profiles (gender, age, education, nationality, occupation, self-assessment of financial situation) and place of residence (oblast, type of settlement). These data enable tracking Ukrainian public opinion regarding Russia for the period of 14 years, from 2008 to 2022, both among the population as a whole and among its different subpopulations. This monitoring of public opinion in Ukraine on Russia is a part of a joint project with the Levada Center, which simultaneously tracked public opinion in Russia on Ukraine, using the same question wording. However, only the data from the polls conducted in Ukraine are presented in this data collection.

Today is the 19th day of war between Russia and Ukraine. Many countries are supporting Ukraine by introducing economic sanctions on Russia. There are a lot of tweets about the Ukraine and Russia war where people tend to update about the ground truths, what they feel about it, and who they are supporting. So if you want to analyze the sentiments of people over the Ukraine and Russian War, this article is for you. In this article, I will take you through the task of Ukraine and Russia war Twitter Sentiment Analysis using Python.

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.

In December 2021 and early February 2022, KIIS included the following question in its public opinion polls with the aim of assessing the population's readiness to resist a potential Russian invasion: 'In the event of an armed intervention by Russia in your city or village, would you take any action, and if so, which ones?' The response options included: 'Resist with arms,' 'Resist by participating in civil resistance actions such as demonstrations, protests, marches, boycotts, strikes, civil disobedience,' 'Move to a safer region of Ukraine,' 'Move abroad,' and 'Do nothing.' Each of these two polls was conducted with a sample that is representative of the adult population (aged 18 and older) of Ukraine, comprising approximately 2000 respondents. The background information includes respondents' socio-demographic profiles (gender, age, education, nationality, occupation, self-assessment of financial situation) and place of residence (oblast, type of settlement). These data enable the assessment of Ukrainians' willingness to resist Russian intervention on the eve of a full-scale invasion. Consistency in methodology and question wording across the surveys allows to track the dynamics of attitudes from the end of 2021 to just before the invasion in February 2022.

KIIS monitors the geopolitical preferences of the Ukrainian population by asking respondents about their readiness to act in a certain way (vote for, against, or not to participate in the vote) in a hypothetical situation, namely, if a referendum on Ukraine's accession to the European Union, NATO, the Union with Russia and Belarus, or the Customs Union (with Russia, Belarus, Kazakhstan) were held now. In addition to these questions, some polls also ask respondents which direction of foreign policy they consider more preferable, with the options "accession to the European Union", "accession to the Customs Union of Russia, Belarus, Kazakhstan, Kyrgyzstan" and "not joining either the European Union or the Customs Union". This wording of the question enables evaluating the broader attitudes of the population regarding the geopolitical direction without requiring a definitive choice (such as voting for or against a specific option). Each survey wave was carried out on a sample representative of Ukraine's adult population (aged 18 and older), with an average sample size of about 2,000 respondents. In order to facilitate the analysis, the data collected for the period 2005-2022 was combined into one data set, including 31 polls with a total of 62,911 respondents. The background information includes respondents' socio-demographic profiles (gender, age, education, nationality, occupation, self-assessment of financial situation) and place of residence (oblast, type of settlement). These data enable tracking Ukrainian public opinion on the desired course of the Ukraine's foreign policy for the period of 17 years, from 2005 to 2022, both among the population as a whole and among its different subpopulations.

Conducting social science research during an active war raises distinct challenges. To investigate the relationship between both coverage and social desirability bias, we carry out a multi-mode study (web, telephone) with two independently drawn samples of the Ukrainian population during Russia's full-scale invasion of Ukraine in the summer of 2022. We employ identical demographic and behavioral questions in both surveys and pre-register a framing experiment to investigate reported differences in volunteering activities between modes. Observationally, we find that because web studies cannot reach the oldest and most rural Ukrainians, they likely contain much more significant coverage bias with respect to war-related demographic variables compared to the telephone sample. Experimentally, consistent with other studies that report greater social desirability bias in interviewer-mediated models, we find evidence of inflation in reporting volunteering activities only in the telephone survey. Our results demonstrate that, given modern survey techniques, wartime attitudes and behavior in Ukraine can be reliably measured, but there is a trade-off in survey modes between coverage bias and social desirability bias.

This dataset captures detailed geolocated conflict events inside Ukraine, from the beginning of the 2022 Russia–Ukraine war to early 2025. It includes battles, airstrikes, protests, shelling, and more — sourced from the respected ACLED project.

📌 What’s Inside? Event Date — Exact date of each incident.

Event Type — Battles, Explosions, Violence Against Civilians, etc.

Involved Parties — Ukrainian forces, Russian forces, and others.

Location Data — Province, District, Town, Latitude, Longitude.

Fatalities — Estimated deaths for each event.

Detailed Notes — Short summaries of every event.

🌍 Source Curated from ACLED (Armed Conflict Location & Event Data Project).

Data complies with public research usage under ACLED’s policies.

🔥 Potential Uses Conflict Timeline 📅

Predictive Modeling of War Escalation/De-escalation 🔮

Geospatial Analysis & Mapping 🗺️

Death Toll and Intensity Trend Studies 📊

Machine Learning: Severity and Impact Prediction 🧠

⚡ Latest Update: April 2025 Covers only events happening within Ukraine.

Updated for 2025 ongoing conflict events.

Fork it, analyze it, visualize it, and help the world understand this important situation!

This Flash Eurobarometer survey shows large consensus among EU citizens in all EU Member States in favour of the EU’s response to Russia’s invasion of Ukraine. The majority of Europeans think that since the war started, the EU has shown solidarity (79%) and has been united (63%) and fast (58%) in its reaction. Respondents are widely in favour of the unwavering support to Ukraine and its people. In particular, more than nine out of ten respondents (93%) approve providing humanitarian support to the people affected by the war. 88% of Europeans approve the idea of welcoming in the EU people fleeing the war. 80% approve the financial support provided to Ukraine. 66% agree that ‘Ukraine should join the EU when it is ready’, 71% believe that Ukraine is part of the European family and 89% feel sympathy towards Ukrainians.

Processed data

Processed data files for the Eurobarometer surveys are published in .xlsx format.

• Volume A "Countries/EU" The file contains frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of (weighted) replies for each country or territory and for (weighted) EU results.
• Volume AP "Trends" The file compares to previous poll in (weighted) frequencies and means (or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies); shifts for each country or territory foreseen in Volume A and for (weighted) results.
• Volume AA "Groups of countries" The file contains (labelled) frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of (weighted) replies for groups of countries specified by the managing unit on the part of the EC.
• Volume AAP "Trends of groups of countries" The file contains shifts compared to the previous poll in (weighted) frequencies and means (or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies); shifts for each groups of countries foreseen in Volume AA and for (weighted) results.
• Volume B "EU/socio-demographics" The file contains (labelled) frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies for the EU as a whole (weighted) and cross-tabulated by some 20 sociodemographic, socio-political or other variables, depending on the request from the managing unit on the part of the EC or the managing department of the other contracting authorities.
• Volume BP "Trends of EU/socio-demographics" The file contains shifts compared to the previous poll in (weighted) frequencies and means (or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies); shifts for each country or territory foreseen in Volume B above)and for (weighted) results.
• Volume C "Country/socio-demographics" The file contains (labelled) weighted frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies for each country or territory surveyed separately and cross-tabulated by some 20 socio-demographic, socio-political or other variables (including a regional breakdown).

For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer

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/

Euromaidan (or the Revolution of Dignity) is the name given to the protests of late November 2013 - February 2014 that began after the Ukrainian government announced that it was suspending its course towards European integration. KIIS, in collaboration with DIF and with funding from the International Renaissance Foundation, conducted three polls among participants of the Maidan protests in Kyiv: • The first poll of Maidan participants was held on weekdays, the 7th and 8th of December 2013. A total of 1037 respondents were interviewed using a method that provides a random sample of Maidan participants. • The second poll of Maidan, conducted when it had become a stationary camp (Maidan-camp), took place on December 20, 2013 (Friday). A total of 515 persons were interviewed, representing all stationary points on the square. • On February 3, 2014 (Monday), the third survey of Maidan participants was conducted. In total, 502 people were interviewed at all stationary points of Maidan (tents, House of Trade Unions, the building of the Kyiv City State Administration, October Palace, Ukrainian House, and others), according to a sample that provided proportional coverage of Maidan participants. The topics addressed in these polls include the motivations and demands of the protesters, their willingness to continue participating in protests, the conditions under which they would leave, as well as the socio-demographic profile of participants. The purpose of the survey was to discover whether and what changes had happened among Maidan participants at different stages, exploring shifts in the social and demographic structure, as well as changes in views and demands. After the end of Euromaidan and a period of time passed, KIIS incorporated a question into its nationwide polls with the objective of understanding the public's perception of those protests. The question was: "Please tell me which of the following two statements is closer to your opinion? Euromaidan was... 1) a people's protest in support of Ukraine's European path of development, against government corruption, and violence from representatives of law enforcement OR 2) a struggle for power by anti-Russian, nationalist forces supported by Western intelligence services". This question was designed and employed as part of an assessment of the effectiveness of Russian propaganda; therefore, the second option deliberately repeats one of the Russian propaganda theses. In the period 2015-2018, this question was included in four public opinion polls. Each of the polls was carried out on a sample representative of Ukraine's adult population (aged 18 and older), with an average sample size of about 2,000 respondents. For ease of analysis, the data from these polls was merged into one dataset, with a total of 8,119 respondents. The background information includes respondents' socio-demographic profiles (gender, age, education, nationality, occupation, self-assessment of financial situation) and place of residence (oblast, type of settlement). These data can be used to analyse the transformations of retrospective perceptions of the Euromaidan events among the population of Ukraine, particularly as an indicator of the influence of various narratives across different territorial and socio-demographic groups.

Dataset

This dataset was created by Dipendu Kumar

Contents

EUROPOP2023 are the latest Eurostat long-term population projections produced at national level for 30 countries: all 27 European Union (EU) Member States and three European Free Trade Association (EFTA) countries (Iceland, Norway, and Switzerland), covering the time horizon from 2022 to 2100. Population projections are 'what-if scenario' that aim to show the hypothetically developments of the population size and structure based on a set of assumptions regarding fertility, mortality, and net migration. They are presented for a long time period that covers more than a half-century (50 years).

The datasets consist of the baseline population projections and five sensitivity tests, which are described as follows:

• no migration – it is assumed that net migration is zero for each year within the 2023-2100 time horizon;
• lower migration – it is assumed that the net migration is lower due to a 33% reduction in non-EU immigration flows for each year within the 2023-2100 time horizon;
• higher migration – it is assumed that the net migration is higher due to a 33% increase in non-EU immigration flows for each year within the 2023-2100 time horizon;
• lower fertility – it is assumed that the fertility rates are lower 20% than the baseline assumptions for each year within the 2023-2100 time horizon;
• lower mortality – it is assumed that the mortality rates are lower resulting in an increase of approximately two years in life expectancy at birth by 2070 compared to the baseline assumptions.

In each sensitivity test, the assumptions for the year 2022 were maintained as in the baseline projections. This is because, for that year, there is a combination of observed data (i.e. beneficiaries on temporary protections at the end of December 2022), information from the national authorities, and forecasting.

Data are available by single-year time interval, as detailed below:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, age-specific mortality rates and net migration levels;
• Projected life expectancy by age (in completed years) and sex.

Additionally, the demographic balances and indicators are available for the baseline projections and each of the five sensitive variants, including also:

• Total numbers of the projected live births and deaths;
• Projected population structure indicators including proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

STP2024 are the short-term population projections covering the time horizon from 2023 to 2050, and produced at national level for 30 countries: all 27 European Union (EU) Member States and three European Free Trade Association (EFTA) countries (Iceland, Norway, and Switzerland). Similar to long-term projections, these are 'what-if scenario' that aim to show the hypothetically developments of the population size and structure based on a set of assumptions regarding fertility, mortality and net migration. The latest demographic data published on Eurostat website, as of 06 September 2024, were used as input in building the assumptions, thereby including the published post-2021 census revisions and data related to the temporary protection granted to persons displaced from Ukraine due to Russia's invasion.

The dataset (proj_stp24) includes data by single-year time interval for two types of projections:

• Baseline projections:
  • Projected total population on 1 January, the working-age population (defined as persons aged from 15 to 74), and its share in the total population;
  • Assumptions on total fertility rates, life expectancy at birth by sex, and total net migration levels;
  • Total numbers of projected live births and deaths.

• No migration sensitivity test – it is assumed that the net migration is zero for each year within the 2024-2050 time horizon.
  • Projected total population on 1 January, the working-age population (defined as persons aged from 15to 74), and its share in the total population;
  • The 2023 net migration levels remain the same as in the baseline projections to reflect the nowcast data;
  • Total numbers of projected live births and deaths.

STP2025 are the latest short-term population projections covering the time horizon from 2024 to 2050, produced at national level for 30 countries: all 27 European Union (EU) Member States and three European Free Trade Association (EFTA) countries (Iceland, Norway, and Switzerland). Similar to long-term projections, these are 'what-if scenario' that aim to show the hypothetically developments of the population size and structure based on a set of assumptions regarding fertility, mortality, and net migration. The latest demographic data published on Eurostat website as of 15 May 2025, were used as input in building the assumptions, thereby including the published post-2021 census revisions and data related to temporary protection granted to persons displaced from Ukraine due to Russia's invasion.

The dataset (proj_stp25) includes data by single-year time interval for two types of projections:

• Baseline projections:
  • Projected total population on 1 January, working-age population (15-74 years) and its share in the total population;
  • Assumptions on total fertility rates, life expectancy at birth by sex, and total net migration levels;
  • Total numbers of projected live births and deaths.

• No migration sensitivity test – it is assumed that the net migration is zero in each year of the 2025-2050 time horizon.
  • Projected total population on 1 January, working-age population (15-74 years) and its share in the total population;
  • The 2024 net migration levels remain as in the baseline projections to reflect the nowcast data;
  • Total numbers of projected live births and deaths.