The Gross Domestic Product (GDP) in Russia was worth 2173.84 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Russia represents 2.05 percent of the world economy. This dataset provides the latest reported value for - Russia GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Dataset - Russia-Economic policy-1917 in the news

The Gross Domestic Product (GDP) in Russia expanded 1.40 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides the latest reported value for - Russia GDP Annual Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Sources distribution - Russia-Economic policy-1917 in the news

Sentiment polarity - Russia-Economic policy-1917 in the news

Inflation Rate in Russia decreased to 9.40 percent in June from 9.90 percent in May of 2025. This dataset provides - Russia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Evolution, trends - Russia-Economic policy-1917 in the news

Russia's main stock market index, the MOEX, fell to 2642 points on July 11, 2025, losing 3.31% from the previous session. Over the past month, the index has declined 3.94% and is down 11.21% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Russia. Russia Stock Market Index MOEX CFD - values, historical data, forecasts and news - updated on July of 2025.

Provides all of the data and code necessary to reproduce the findings in "How Autocrats Manipulate Economic News: Evidence from Russia’s State-Controlled Television."

Russia E-Commerce Transactions: AOV: News & Media data was reported at 69.980 USD in 18 Nov 2023. This records a decrease from the previous number of 75.806 USD for 17 Nov 2023. Russia E-Commerce Transactions: AOV: News & Media data is updated daily, averaging 46.459 USD from Dec 2018 (Median) to 18 Nov 2023, with 436 observations. The data reached an all-time high of 1,662.334 USD in 03 Mar 2020 and a record low of 0.097 USD in 24 Jun 2021. Russia E-Commerce Transactions: AOV: News & Media data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Russian Federation – Table RU.GI.EC: E-Commerce Transactions: by Category.

Russia E-Commerce Transactions: Volume: News & Media data was reported at 1.000 Unit in 18 Nov 2023. This stayed constant from the previous number of 1.000 Unit for 17 Nov 2023. Russia E-Commerce Transactions: Volume: News & Media data is updated daily, averaging 1.000 Unit from Dec 2018 (Median) to 18 Nov 2023, with 436 observations. The data reached an all-time high of 8.000 Unit in 05 Jun 2023 and a record low of 1.000 Unit in 18 Nov 2023. Russia E-Commerce Transactions: Volume: News & Media data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Russian Federation – Table RU.GI.EC: E-Commerce Transactions: by Category.

Sections distribution - Russia-Economic policy-1917 in the news

Exports in Russia decreased to 33060 USD Million in April from 34559 USD Million in March of 2025. This dataset provides - Russia Exports - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Please refer to: https://data.imf.org/en/news/accessing%20international%20financial%20statistics

Unemployment Rate in Russia decreased to 2.20 percent in May from 2.30 percent in April of 2025. This dataset provides - Russia Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This is a replication data for my paper under blind review. Abstract This paper develops a new prediction model for media content presence on a website. It analyses a new corpus of one million articles from five countries: Poland, Russia, Belarus, Kazakhstan and Ukraine, in two languages, Polish and Russian. These articles were scraped daily from seventeen websites in 2017-2020 period. The research applies a wide range of natural language processing methods to automatically derive several properties of each article: its topic, sentiment, basic emotions, mentions of influential domestic politicians. The articles’ embeddings and their cosine similarity are used to calculate the news context, such as how an article differs from the daily issue main themes. These features are used to estimate a logistic regression assessing the likelihood that the same or slightly modified, as measured by cosine similarity, article will remain on the main web page the next day. The key, and somewhat unexpected result is that articles with negative sentiment polarity are less likely to be published for more than one day. This result holds for all countries analyzed. It means that the negative news bias documented in the literature is partly offset by their shorter life cycle. Data is in the Python pickle format. Should be read into Python using the pickle.load() function. Each element (row) is the data frames or list represents one news article. Each file has the same format. Loading a pickle file returns a list of four elements: 1. A dummy variable equal to 1 when the article was published the next day, with the text being identical 2. A dummy variable equal to 1 when the article was published the next day, but we allow for small text modifications (cosine similarity > 0.99) 3. Dataframe with extracted features, described below. 4. List with texts of articles in Polish or Russian Ad 3. The columns of the dataframe are as follows (we refer to row number i in description): - pandas index (may appear once or twice in the datafame) - maxcosine: maximum cosine similarity between art i and all articles published next day - cosine_diff: cosine similarity between article i and the elementwise average of embeddings of all articles in the current issue. Measure how similar is the article i to the core narrative of the current issue - cosine_std: std. dev. of cosine similarity measures between all pairs of articles in the current issue. Measures how focused or dispersed is the current issue news coverage - thirteen LDA topic groups: politics, legislation and legal affairs (POL); economy, finance, various sectors of the economy (ECO); military, war, protests, crime, security threats (MIL); international affairs, specific issues concerning foreign countries (INT); technology (TECH); family issues, culture, sport, education (FAM); regional issues and housing (REG); health issues and the Covid-19 pandemic (HEA); media (MED); accidents (ACC); religion (REL); the Soviet Union (USSR); and articles for which no topic could be determined (MISC). - rsent.c: relative sentiment that is dictionary based sentiment of articles i minus the average sentiment of the newspaper. This approach eliminates newspaper or country idiosyncratic sentiment factors. c stands for Covid, the sentiment lexicon was augmented with Covid related terms - dip_*: Variable measuring if influential domestic politicians are mentioned in article i, * represent a country acronym. If N is equal to the number of occurrences of the names of influential domestic politicians in the article i, dip_* = 0 if N=0, dip_* = 1+ log(N) if N>0. - three or four names of news portals from which the data was scraped. - names of six basic emotions and the article i emotion scores calculated using zero-shot learning and the large version of the XLM (Conneau et al., 2019) model from the huggingface transformers library available at https://huggingface.co/vicgalle/xlm-roberta-large-xnli-anli Names of the politicians used to calculate dip variables Russia "putin" "medvedev" "vaino" "shoigu" "bortnikov" "lavrov" "mishustin" "kirienko" "sechin" Ukraine "zelensky" "shmygal" "akhmetov" "avakov" "ermak" "poroshenko" "medvedchuk" "groisman" Kazakhstan "sagyntaev" "mamin" "tokayev" "nnazarbayev" "dnazarbayeva" "kulibayev" "masimov" Belarus "alukashenko" "vakulchik" "vlukashenko" "kobyakov" "makei" "myasnikovich" [37] "rumas" "golovchenko" Poland "kaczynski" "duda" "morawiecki" "ziobro" Data coverage Country, news portal, numbr of articles Russia iz.ru 43,782 Russia kommersant.ru 46,070 Russia novayagazeta.ru 29,357 Russia vedomosti.ru 27,797 Kazakhstan informburo.kz 29,375 Kazakhstan nur.kz 67,350 Kazakhstan tengrinews.kz 44,285 Kazakhstan zakon.kz 109,442 Belarus bdg.by 33,447 Belarus belgazeta.by 21,995 Belarus sb.by 83,685 Ukraine kp.ua 194,792 Ukraine segodnya.ua 45,835 Ukraine vesti.ua 90,559 Poland gazeta.pl 53,321 Poland rp.pl 49,587 Poland wpolityce.pl 76,625 In the provided dataframes...

Voting behavior, political system and economic reforms. Topics: Watching news programs and reading newspaper; mood in the last few days; family´s current material situation; economic situation of town/region and country; general situation; market reforms; opinion on Yeltsin, Duma, Prime Minister and government; political situation; life satisfaction; expected improvements in the next 12 months; Russia out of control; democracy vs. order; trust in politicians; rating of Yeltsin and Chernomirdin; expectations concerning politics and economy in the next few months; the biggest problems of the society; possibility of mass demonstrations and taking part; voting intention for/against Yeltsin and reasons; income growth compared to the prices; money per capita needed; subsistence level; price trends; time to purchase goods and save money; economic situation in the last and in the next 6 months; economic situation in Russia in 12 months and in 5 years; renouncing from necessary things, holiday trips etc; assumed income level of poor families; domestic vs. imported goods, clothes and household goods; place of shopping; spending money; savings and shares in investment funds; save money in near future; assumed income level of a rich family; ideal number of children; way of increasing the number of children; planned number of children; having another child in the next 2-3 years; unplanned pregnancy; conditions for having another child; birth rate control; voting intention in the presidential elections; Yeltsin or Zyuganov; suspected election result; Zyuganov or Yavlinski; next Russian President; class self placement; sources of income; problem of lacking orders in the company; poor supplies of equipment and raw supplies; irregular work; leaders´ inability; selling products in the company; theft in the firm; high wages vs. social security; work preferences; importance of work; intensity of work; conditions for being successful at work; keeping job vs. unemployment; interpersonal relationship at work; involving in any conflicts last year; conflicts between the company´s management and the work team; conflicts between members of staff; most frequent reasons for conflict; way of solving the conflicts; opinion on strikes; second job; motivation of the workers; possibilities of initiative; successful groups in Russia; main income of the family; telephone; high and low self placement five years ago, today and in five years; religion; staying at home in June; voting in presidential election; voting decision in 1995 elections; region.

Russia recorded a trade surplus of 8720 USD Million in May of 2025. This dataset provides - Russia Balance of Trade - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita in Russia was last recorded at 11043.26 US dollars in 2024. The GDP per Capita in Russia is equivalent to 87 percent of the world's average. This dataset provides the latest reported value for - Russia GDP per capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Explore the rising European gas prices driven by reduced Russian supply and its impact on the economy and energy strategies.