The Office of the United Nations High Commissioner for Human Rights (OHCHR) verified a total of 41,783 civilian casualties during Russia's invasion of Ukraine as of January 31, 2025. Of them, 29,178 people were reported to have been injured. However, OHCHR specified that the real numbers could be higher. How many people have died during the war in Ukraine? OHCHR has estimated the number of deaths of civilians, or non-armed individuals, in Ukraine at 12,605 since the start of the war on February 24, 2022. The highest death toll was recorded in March 2022, at over 3,900. The figures on soldier deaths are reported by Russia and Ukraine’s governmental authorities, but they cannot be verified at this point and thus need to be taken with caution. Conflict-related deaths in Ukraine from 2014 to 2021 After Russia annexed Crimea in 2014, Ukraine has seen a military conflict between the government and the Russia-supported separatist regions of Donetsk and Luhansk. OHCHR estimates that between 14,200 and 14,400 people, including civilians and military personnel, were killed in relation to that conflict from April 14, 2014, to December 31, 2021. Of them, at least 3,400 were civilians.

As of January 31, 2025, 12,605 civilian deaths in Ukraine were reported by the Office of the United Nations High Commissioner for Human Rights (OHCHR) due to the Russian invasion that started on February 24, 2022. OHCHR specified that the real figures could be significantly higher. Furthermore, the increases in the figures each week should not be attributed to that week only because they include adjustments from previous weeks.

The highest number of civilian casualties in Ukraine during the Russian invasion that began on February 24, 2022, was recorded in March 2022, with 4,312 people killed and 3,018 injured. In January 2025, 139 civilian deaths were verified by the Office of the United Nations High Commissioner for Human Rights (OHCHR).

Which keywords are most widely used in online media worldwide in relation to the Russia-Ukraine war? Looking at the number of online articles published by global news outlets in 65 languages, keyword combinations related to sending weapons to Ukraine, Western sanctions on Russia, and nuclear weapons were used the most in 2024. The Russia-Ukraine war began in February 2022, resulting in a humanitarian crisis, economic, trade, and financial restrictions on Russia, and supply chain interruptions around the globe. Sending weapons to Ukraine has been widely covered in online media A keyword combination commonly mentioned in global online articles was that of the words "Ukraine" and "weapons." In total, from 2022 to 2024, around 2.3 million articles in online press mentioned them in one text. In view of the Russian invasion, Western countries provided military aid to Ukraine. The United States, Germany, and the United Kingdom (UK) provided the highest worth of military aid. The invasion has raised fears of a nuclear war Over the course of 2022, online press worldwide extensively covered the topic of nuclear weapons and the nuclear threat, with around 681,000 online articles published across the world mentioning "Russia" or "Ukraine" together with "nuclear" in combination with "war." In general, in that year, the number of online articles mentioning nuclear weapons was the highest over the past years.

Social media can be mirrors of human interaction, society, and world events. Their reach enables the global dissemination of information in the shortest possible time and thus the individual participation of people all over the world in global events in almost real-time. However, equally efficient, these platforms can be misused in the context of information warfare in order to manipulate human perception and opinion formation. The outbreak of war between Russia and Ukraine on February 24, 2022, demonstrated this in a striking manner.

Here we publish a dataset of raw tweets collected by using the Twitter Streaming API in the context of the onset of the war which Russia started on Ukraine on February 24, 2022. A distinctive feature of the dataset is that it covers the period from one week before to one week after Russia's invasion of Ukraine. We publish the IDs of all tweets we streamed during that time, the time we rehydrated them using Twitter's API as well as the result of the rehydration. If you use this dataset, please cite our related Paper:

Pohl, Janina Susanne and Seiler, Moritz Vinzent and Assenmacher, Dennis and Grimme, Christian, A Twitter Streaming Dataset collected before and after the Onset of the War between Russia and Ukraine in 2022 (March 25, 2022). Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4066543

Abstract

Beyond causing immediate hardship and triggering a large exodus of displaced people, Russia’s military invasion of Ukraine and the blockade of its Black Sea export routes have also led to sharp increases in grain prices and raised concern about global food security. To provide information to the government for developing policies and programs to support the agricultural sector in Ukraine, the World Bank launched a nationwide survey of post-invasion farmers in cooperation with the Ministry of Agricultural Policy and Food (MAPF), with financial support from the EU, in areas controlled by Ukraine from October to December of 2022. The survey objective is to obtain information on changes in welfare, production, and productivity in the small and medium farm sector between 2021 and 2022 and to identify ways on how farmers could be most effectively supported. Data was collected via phone by the Kyiv International Institute of Sociology (KIIS) under the monitoring of World Bank research team.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame consisted of 63,374 registered farms. The distribution of farms by size and program participation shows that most of the farms are small (85%) with farm size less than 50 ha (35,264 PSG non-applicants vs. 18,605 PSG applicants) followed by farms with 50-120 ha (7.5% with 1,634 PSG non-applicants and 3,107 PSG applicants) and farms that are not eligible for PSG participation with size greater than 120 ha (7.5% with 2,743 less than 500 ha and 2,021 greater than 500 ha).

The expected sample size for the phone survey was 2,500 farms with 10% each in the small size category from PSG applicants and non-applicants, 20% each in the farm category of 50-120 ha from PSG applicants and non-applicants, 20% from the farm size category of 120-500 ha and 20% from the farm size category of greater than 500 ha. Given the expected high non-response rate of phone interviews, all the farms with size greater than 50 ha were included in the sample and then 1,125 and 1,126 farms were randomly selected from PSG non-participants and participants in the less than 50 ha category. The final response rate was about 20% with the lowest in the greater than 500 ha category (15%) and the highest in the 50-120 ha PSG non-applicant category (28%). The survey initially targets 2, 500 farms, and eventually collected data for 2, 251 farms.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaire comprised four sections namely: • Screener & Background • Household Roster • Agricultural Production • Property and Finance

Cleaning operations

Data have been collected electronically. Survey logic has been incorporated into the instrument. After data collection, mainly general data completeness and outliers have been checked. Also, all text responses to open-ended questions have been analyzed and coded if necessary.

The final data file contains data from 2,251 interviews. It was provided to the World Bank team in SPSS formats.

Response rate

The overall and cooperation response rates were 21.3% and 37.3% respectively.

This article probes into scope conditions for image change, investigating what changes in Russian images of the European Union (EU) have taken place as a result of the Russian-Ukrainian crisis. A catalytic event, the crisis has been surrounded by uncertainty and strong emotions and is seen as a potential historical watershed in EU-Russian relations. The article examines Russia’s images of the EU’s intentions (good or bad?), capabilities (strong or weak?), and cultural and political status (inferior or superior?); and how they change in connection with the Russian-Ukrainian crisis. The article compares across time EU images found in Russian major newspapers and public opinion (studies undertaken in 2011-12 and 2015, before and after the crisis).

As a result of Russia's invasion of Ukraine, the global economy is estimated to contract by 0.17 percent in 2022. Furthermore, due to sanctions imposed on Russia, its economy is projected to decline by 0.7 percent in 2022 and by 1.21 percent in 2023.

The dataset is composed of 10,348 tweets: 5,284 for English and 5,064 for Turkish. Tweets in the dataset are human-annotated in terms of "false", "true", or "other". The dataset covers multiple topics: the Russia-Ukraine war, COVID-19 pandemic, Refugees, and additional miscellaneous events. The details can be found at https://github.com/avaapm/mide22

Putin's missile war : Russia's strike campaign in Ukraine is a book. It was written by Ian Williams and published by Eurospan in 2023.

Using Russia, Ukraine, Russia-Ukraine, and Ukraine-Russia as keywords, data on Facebook news posts from February 1, 2022, to February 1, 2023, was collected through the Qsearch social data platform. After excluding irrelevant posts, a total of 995 posts from the Central News Agency and 1019 posts from People’s Daily were collected

This data was used in the following publications:

1. Koltsova, O., & Pashakhin, S. (2019). Agenda divergence in a developing conflict: Quantitative evidence from Ukrainian and Russian TV newsfeeds. Media, War & Conflict, 1750635 21982987. https://doi.org/10.1177/1750635219829876

2.Pashakhin S. Topic Modeling for Frame Analysis of News Media // Proceedings of the AINL FRUCT 2016. С. 103-105 – URL: http://fruct.org/publications/abstract-AINL-FRUCT-2016/files/Pas.pdf

The dataset contains 45,009 news messages collected from official websites of a Russian (Channel One) and a Ukrainian (Channel 5) TV channels. Ukrainian news items were translated into Russian.

The dataset has six variables:

• text -- a news item;
• channel -- a source of an item ('first' -- Russian TV channel, 'five' -- Ukrainian TV channel);
• date -- the date of publishing;
• url -- links to original news messages.

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 data package includes the underlying data files to replicate the data and charts presented in Russia’s invasion of Ukraine has cemented the European Union’s commitment to carbon pricing PIIE Policy Brief 23-13.

If you use the data, please cite as: Kirkegaard, Jacob Funk. 2023. Russia’s invasion of Ukraine has cemented the European Union’s commitment to carbon pricing. PIIE Policy Brief 23-13. Washington, DC: Peterson Institute for International Economics.

We use plausibly exogenous variation in the availability of the Russian analog television signal in Ukraine to study how a media source with a conspicuous political agenda impacts political behavior and attitudes. Using highly disaggregated election data and an original survey we estimate that Russian television substantially increased average electoral support for parties and candidates with a `pro-Russian' agenda in the 2014 presidential and parliamentary elections. Evidence suggests that this effect is attributable to persuasion rather than differential mobilization. The effectiveness of biased media varied in a politically consequential way: its impact was largest on voters with strong pro-Russian priors but was less effective, and to some degree even counter-effective, in persuading those with strong pro-Western priors. Our finding suggests that exposing an already polarized society to a biased media source can result in even deeper polarization.

The G7 is a forum designed for frank and open discussion between leaders, ministers and policy-makers. As a member of the G7, Canada plays a leading role on the international stage and is able to advance domestic and international priorities. The G7 provides global leadership and serves as a powerful catalyst on issues that are later taken up by other fora with broader global and regional membership. The G7 brings together the world’s advanced economies to influence global trends and tackle pervasive and crosscutting issues, as well as emergent global crises. The G7 has strengthened international economic and security policies, advanced discussion of global issues including climate change and gender equality, brought donors together and supported disarmament programs. Most recently, the G7 has worked to tackle the COVID-19 pandemic and respond to Russia’s illegal invasion of Ukraine. At the G7, Canada has advanced its domestic and international priorities, including gender equality, peace and security, climate change and building a sustainable global economy. Transparent and inclusive engagement with Canadian and international stakeholders has helped Canada to deliver on priorities that are important to Canadians.

The data set contains posts from social media networks popular among Russian-speaking communities. Information was searched based on pre-defined keywords ("war", "special military operation", etc.) and is mainly related to the ongoing war in Ukraine with Russia. After a thorough review and analysis of the data, both propaganda and fake news were identified. The collected data is anonymized. Feature engineering and text preprocessing can be applied to obtain new insights and knowledge from this data set. The data set is useful for the study of information wars and propaganda identification.

The repository contains an ongoing collection of tweets IDs associated with the current conflict in Ukraine and Russia, which we commenced collecting on Februrary 22, 2022. To comply with Twitter’s Terms of Service, we are only publicly releasing the Tweet IDs of the collected Tweets. The data is released for non-commercial research use. Note that the compressed files must be first uncompressed in order to use included scripts. This dataset is release v1.3 and is not actively maintained -- the actively maintained dataset can be found here: https://github.com/echen102/ukraine-russia. This release contains Tweet IDs collected from 2/22/22 - 1/08/23. Please refer to the README for more details regarding data, data organization and data usage agreement. This dataset is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License . By using this dataset, you agree to abide by the stipulations in the license, remain in compliance with Twitter’s Terms of Service, and cite the following manuscript: Emily Chen and Emilio Ferrara. 2022. Tweets in Time of Conflict: A Public Dataset Tracking the Twitter Discourse on the War Between Ukraine and Russia. arXiv:cs.SI/2203.07488

This data package includes the underlying data to replicate the calculations and charts presented in Fiscal support and monetary vigilance: Economic policy implications of the Russia-Ukraine war for the European Union, PIIE Policy Brief 22-5.

If you use the data, please cite as: Blanchard, Olivier, and Jean Pisani-Ferry (2022). Fiscal support and monetary vigilance: Economic policy implications of the Russia-Ukraine war for the European Union, PIIE Policy Brief 22-5. Peterson Institute for International Economics.

This dataset is about book series and is filtered where the books is Armies of Russia's war in Ukraine, featuring 10 columns including authors, average publication date, book publishers, book series, and books. The preview is ordered by number of books (descending).