Instagram’s most popular post

              As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
              After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.

              Instagram’s most popular accounts

              As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.

              Instagram influencers

              In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.

              Instagram around the globe

              Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.

Unemployment Rate in the United States decreased to 4.10 percent in June from 4.20 percent in May of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The minimization of open stacks problem (MOSP) aims to determine the ideal production sequence to optimize the occupation of physical space in manufacturing settings. Most of current methods for solving the MOSP were not designed to work with large instances, precluding their use in specific cases of similar modeling problems. We therefore propose a PageRank-based heuristic to solve large instances modeled in graphs. In computational experiments, both data from the literature and new datasets up to 25 times fold larger in input size than current datasets, totaling 1330 instances, were analyzed to compare the proposed heuristic with state-of-the-art methods. The results showed the competitiveness of the proposed heuristic in terms of quality, as it found optimal solutions in several cases, and in terms of shorter run times compared with the fastest available method. Furthermore, based on specific graph densities, we found that the difference in the value of solutions between methods was small, thus justifying the use of the fastest method. The proposed heuristic is scalable and is more affected by graph density than by size.

Since the 1860 election, U.S. presidential elections have been dominated by candidates affiliated with the Democratic and Republican parties. While the electoral votes decide the winner of the election, these are generally decided by the winner of the popular vote in each state (or district), and the winner of the nationwide popular vote does not always go on to win the electoral vote. Interestingly, there have been a number of occasions where the winner of the popular vote did not go on to win the electoral vote, for example in the 2016 election, or, most famously, in 2000.

Anomaly detection in time series data is essential for fraud detection and intrusion monitoring applications. However, it poses challenges due to data complexity and high dimensionality. Industrial applications struggle to process high-dimensional, complex data streams in real time despite existing solutions. This study introduces deep ensemble models to improve traditional time series analysis and anomaly detection methods. Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks effectively handle variable-length sequences and capture long-term relationships. Convolutional Neural Networks (CNNs) are also investigated, especially for univariate or multivariate time series forecasting. The Transformer, an architecture based on Artificial Neural Networks (ANN), has demonstrated promising results in various applications, including time series prediction and anomaly detection. Graph Neural Networks (GNNs) identify time series anomalies by capturing temporal connections and interdependencies between periods, leveraging the underlying graph structure of time series data. A novel feature selection approach is proposed to address challenges posed by high-dimensional data, improving anomaly detection by selecting different or more critical features from the data. This approach outperforms previous techniques in several aspects. Overall, this research introduces state-of-the-art algorithms for anomaly detection in time series data, offering advancements in real-time processing and decision-making across various industrial sectors.

The EB_Composite Knowledge Graph represents information from the first eight editions of the Encyclopaedia Britannica (1768–1860), structured using the Heritage Textual Ontology (HTO). It extends our previously developed EB_HQ by incorporating multiple text sources, such as the National Library of Scotland and the Nineteenth-Century Knowledge Project, for each edition. A particular source is added, comprising of post-corrected textual content generated using deep-learning-based OCR error correction methods. These sources presents different levels of text quality, and EB_Composite enables researchers to compare these texts, and track how they are digitised or extracted from these sources.

The EB_Composite captures 4150776 RDF triples. Same as EB_HQ, it provides structured metadata and descriptions for each edition, volume, and term. By integrating information across different editions, it enables smooth tracking of concept evolution over time. Additionally, the dataset features semantic connections to external knowledge bases such as DBpedia and Wikidata, enhancing links to modern information and supporting more comprehensive analyses.

Designed to support historical research, this dataset offers rich semantic data for exploring the development of knowledge and concepts in the Encyclopaedia Britannica. It categorizes terms as either Articles or Topics, each with detailed metadata extracted from METS and ALTO XML files. OCR errors common in historical texts have been mitigated using deep-learning-based corrections.

Interactive chart of the Dow Jones Industrial Average (DJIA) stock market index for the last 100 years. Historical data is inflation-adjusted using the headline CPI and each data point represents the month-end closing value. The current month is updated on an hourly basis with today's latest value.

The choice of words describing cultural heritage can cause debates. It is especially sensitive when artefacts relate to different cultures and peoples who have been historically marginalised. Words chosen by archivists or curators may transmit stereotypes. The cultural heritage community has produced knowledge on potentially stereotyping and offensive terminology in heritage collections. At the same time, their knowledge is difficult to incorporate into existing online collections unless this knowledge is structured and machine-readable.

The Words Matter Knowledge Graph represents domain expert knowledge on discussions about contentious terminology in the cultural sector. In the knowledge graph, 75 English and 83 Dutch contentious terms are linked to explanations of their usage and suggested alternatives from domain experts. There are also related matches between contentious terms and sources from external datasets: Wikidata, Princeton WordNet, Open Dutch WordNet, and Getty Art & Architecture Thesaurus.

This Zenodo publication includes the CULCO scheme used to model contentious terms in the knowledge graph. The scheme documentation is available on a separate page.

This knowledge graph is based on the publication “Words Matter: An Unfinished Guide to Word Choices in the Cultural Sector” by the National Museum of World Cultures (NMVW).

Read more about this work in the paper "A Knowledge Graph of Contentious Terminology for Inclusive Representation of Cultural Heritage" (2023) by Andrei Nesterov, Laura Hollink, Marieke van Erp & Jacco van Ossenbruggen.

In this version:

• the CULCO scheme documentation is updated
• versioning is fixed
• typos are corrected

The Gross Domestic Product (GDP) in the United States contracted 0.50 percent in the first quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - United States GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Every four years in the United States, the electoral college system is used to determine the winner of the presidential election. In this system, each state has a fixed number of electors based on their population size, and (generally speaking) these electors then vote for their candidate with the most popular votes within their state or district. Since 1964, there have been 538 electoral votes available for presidential candidates, who need a minimum of 270 votes to win the election. Because of this system, candidates do not have to win over fifty percent of the popular votes across the country, but just win in enough states to receive a total of 270 electoral college votes. The use of this system is a source of debate in the U.S.; those in favor claim that it prevents candidates from focusing on the interests of urban populations, and must also appeal to smaller and less-populous states, and they say that this system preserves federalism and the two-party system. However, critics argue that this system does not represent the will of the majority of American voters, and that it encourages candidates to disproportionally focus on winning in swing states, where the outcome is more difficult to predict. Popular results From 1789 until 1820, there was no popular vote, and the President was then chosen only by the electors from each state. George Washington was unanimously voted for by the electorate, receiving one hundred percent of the votes in both elections. From 1824, the popular vote has been conducted among American citizens, to help electors decide who to vote for (although the 1824 winner was chosen by the House of Representatives, as no candidate received over fifty percent of electoral votes). Since 1924, the difference in the share of both votes has varied, with several candidates receiving over ninety percent of the electoral votes while only receiving between fifty and sixty percent of the popular vote. The highest difference was for Ronald Reagan in 1980, where he received just 50.4 percent of the popular vote, but 90.9 percent of the electoral votes. Unpopular winners Since 1824, there have been 49 elections, and in 18 of these the winner did not receive over fifty percent of the popular vote. In the majority of these cases, the winner did receive a plurality of the votes, however there have been five instances where the winner of the electoral college vote lost the popular vote to another candidate. The most recent examples of this were in 2000, when George W. Bush received roughly half a million fewer votes than Al Gore, and in 2016, where Hillary Clinton won approximately three million more votes than Donald Trump.

Online Social Networks (OSN) are used by millions of users, daily. This user-base shares and discovers different opinions on popular topics.
Social influence of large groups may be influenced by user believes or be attracted the interest in particular news or products. A large number of users, gathered in a single group or number of followers, increases the probability to influence OSN users.
Botnets, collections of automated accounts controlled by a single agent, are a common mechanism for exerting
maximum influence. Botnets may be used to better infiltrate the social graph over time and create an illusion of community
behaviour, amplifying their message and increasing persuasion.

This paper investigates Twitter botnets, their behavior, their interaction with user communities and their evolution over time.
We analyze a dense crawl of a subset of Twitter traffic, amounting to nearly all interactions by Greek-speaking Twitter users for a period
of 36 months.

The collected users are labeled as botnets, based on long term and frequent content similarity events. We detect over a million events, where seemingly unrelated accounts tweeted nearly identical content, at almost the same time. We filter these concurrent content injection events and detect a set of 1,850 accounts that repeatedly exhibit this pattern of behavior, suggesting that they are fully or in part controlled and orchestrated by the same entity. We find botnets that appear for brief intervals and disappear, as well as botnets that evolve and grow, spanning the duration of our dataset. We analyze statistical differences between the bot accounts and human users, as well as the botnet interactions with the user communities and the Twitter trending topics.

Graph and download economic data for Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for United Kingdom (IRLTLT01GBM156N) from Jan 1960 to May 2025 about long-term, 10-year, United Kingdom, bonds, yield, government, interest rate, interest, and rate.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Since 1824, when the popular vote was first used to determine the overall winner in U.S. presidential elections, the share of the population who participate in these elections has gradually increased. Despite this increase, participation has never reached half of the total population; partly due to the share of the population below the voting age of eighteen, but also as many potential voters above the age of eighteen do not take part, or are ineligible to vote. For example, in the 2016 election, approximately twenty million U.S. adults were ineligible to vote, while over 94 million simply did not participate; in this election, Donald Trump won the electoral college with 63 million votes, which means that 19.4 percent of the total U.S. population (or 27.3 percent of eligible voters) voted for the current president.

Development throughout history

While the figures for the 2016 election may appear low, over 42 percent of the total population participated in this election, which was the third highest participation rate ever recorded (after the 2008 and 2020 elections). In the first election decided by a popular vote in 1824, only 350 thousand votes were cast from a total population of 10.6 million, although this increased to over four million votes by the 1856 election, as restrictions that applied to non-property holding white males were gradually lifted. Participation levels then dropped during the Civil War and Reconstruction era, as those who lived in Confederate states could not vote in 1864, and many white southerners were restricted or discouraged in the following election. Although universal suffrage was granted to black males in the wake of the Civil War, the majority of black Americans lived in the southern states, where lawmakers introduced Jim Crow laws in the late 1800s to suppress and disenfranchise the black vote, as well as poor white voters.

The next major milestone was the introduction of women's suffrage in 1920, which saw voter participation increase by seven million votes (or seven percent) between the 1916 and 1920 elections. Between the 1910s and 1970s, the Great Migration saw many black Americans move away from the south to northern and western states, where they faced fewer obstacles when voting and greater economic mobility. This period of black migration began to decline in the 1960s and 1970s, during which time many Jim Crow laws were repealed in the south, through legislation such as the Voting Rights Act of 1965. Female participation also grew gradually, and has exceeded male voting participation in all elections since the 1980s. The minimum voting age was lowered from 21 to 18 in all states in 1971, although this seemingly had a minimal impact on the short-term trajectory of voter participation.

Recent elections

The 1992 election was the first in which more than one hundred million votes were cast, which was almost 41 percent of the total population. All elections since 2004 have also had more than one hundred million votes cast, which has again been more than forty percent of the total population. Another key factor in the increase in voter participation is the fact that people are living longer than ever before, and that those aged 65 and over have had the highest turnout levels since 1992. While some figures may be subject to change, the 2020 election set new records for voter turnout. Despite the global coronavirus pandemic, which many thought could cause the lowest turnout in decades, a record number of voters cast their ballots early or by mail, setting a new record of votes just shy of 160 million. In the 2020 election, Joe Biden and Donald Trump received 81.3 million and 74.2 million votes respectively, both beating Barack Obama's previous record of 69.3 million ballots in 2008.

The Gross Domestic Product (GDP) in the United States expanded 2 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides the latest reported value for - United States GDP Annual Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

As of March 2025, Google represented 79.1 percent of the global online search engine market on desktop devices. Despite being much ahead of its competitors, this represents the lowest share ever recorded by the search engine in these devices for over two decades. Meanwhile, its long-time competitor Bing accounted for 12.21 percent, as tools like Yahoo and Yandex held shares of over 2.9 percent each. Google and the global search market Ever since the introduction of Google Search in 1997, the company has dominated the search engine market, while the shares of all other tools has been rather lopsided. The majority of Google revenues are generated through advertising. Its parent corporation, Alphabet, was one of the biggest internet companies worldwide as of 2024, with a market capitalization of 2.02 trillion U.S. dollars. The company has also expanded its services to mail, productivity tools, enterprise products, mobile devices, and other ventures. As a result, Google earned one of the highest tech company revenues in 2024 with roughly 348.16 billion U.S. dollars. Search engine usage in different countries Google is the most frequently used search engine worldwide. But in some countries, its alternatives are leading or competing with it to some extent. As of the last quarter of 2023, more than 63 percent of internet users in Russia used Yandex, whereas Google users represented little over 33 percent. Meanwhile, Baidu was the most used search engine in China, despite a strong decrease in the percentage of internet users in the country accessing it. In other countries, like Japan and Mexico, people tend to use Yahoo along with Google. By the end of 2024, nearly half of the respondents in Japan said that they had used Yahoo in the past four weeks. In the same year, over 21 percent of users in Mexico said they used Yahoo.

Labor Force Participation Rate in the United States decreased to 62.30 percent in June from 62.40 percent in May of 2025. This dataset provides the latest reported value for - United States Labor Force Participation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Consumer Confidence in the United States increased to 60.70 points in June from 52.20 points in May of 2025. This dataset provides the latest reported value for - United States Consumer Sentiment - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.