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Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.

              The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.

              How popular is Instagram?

              Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.

              Who uses Instagram?

              Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.

              Celebrity influencers on Instagram
              Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

The Gross Domestic Product (GDP) in Congo expanded 6.20 percent in the fourth quarter of 2023 over the same quarter of the previous year. This dataset provides - Congo GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

              Instagram’s Global Audience

              As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
              As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.

              Who is winning over the generations?

              Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.

Ecommerce marketplace app Shopee started life out as a customer-to-customer marketplace, in the same vein as eBay, but over the past few years has remodelled itself as a b2c marketplace. That switch...

This data publication contains urban tree growth data collected over a period of 14 years (1998-2012) in 17 cities from 13 states across the United States: Arizona, California, Colorado, Florida, Hawaii, Idaho, Indiana, Minnesota, New Mexico, New York, North Carolina, Oregon, and South Carolina.

Measurements were taken on over 14,000 urban street and park trees. Key information collected for each tree species includes bole and crown size, location, and age. Based on these measurements, 365 sets of allometric equations were developed for tree species from around the U.S. Each “set” consists of eight equations for each of the approximately 20 most abundant species in each of 16 climate regions. Tree age is used to predict a species diameter at breast height (dbh), and dbh is used to predict tree height, crown diameter, crown height, and leaf area. Dbh is also used to predict age. For applications with remote sensing, average crown diameter is used to predict dbh. There are 171 distinct species represented within this database. Some species grow in more than one region. The Urban Tree Database (UTD) contains foliar biomass data (raw data and summarized results from the foliar sampling for each species and region) that are fundamental to calculating leaf area, as well as tree biomass equations (compiled from literature) for carbon storage estimates. An expanded list of dry weight biomass density factors for common urban species is made available to assist users in using volumetric equations.Information on urban tree growth underpins models used to calculate effects of trees on the environment and human well-being. Maximum tree size and other growth data are used by urban forest managers, landscape architects and planners to select trees most suitable to the amount of growing space, thereby reducing costly future conflicts between trees and infrastructure. Growth data are used to develop correlations between growth and influencing factors such as site conditions and stewardship practices. Despite the importance of tree growth data to the science and practice of urban forestry, our knowledge is scant. Over a period of 14 years scientists with the U.S. Forest Service recorded data from a consistent set of measurements on over 14,000 trees in 17 U.S. cities.These data were originally published on 03/02/2016. The metadata was updated on 10/06/2016 to include reference to a new publication. Minor metadata updates were made on 12/15/2016. On 01/07/2020 this data publication was updated to correct a few species' names and systematic errors in the data that were found. A complete list of these changes is included (\Supplements\Errata_Jan2020_RDS-2016-0005.pdf). In addition, we have included a list of changes for the General Technical Report associated with these data (\Supplements\Errata_Jan2020_PNW-GTR-253.pdf).

Employment Rate in the United States decreased to 59.70 percent in May from 60 percent in April of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The model estimated in this document uses a set of variables that are available for a wide range of countries with different levels of development, resulting in a sample of 91 countries for the period 1970-2010. The file titled “Database PLS-PM” contains the data with which is possible to estimate the human capital index (ich) calculated in the paper. The variables used and their notation is as follows: FR= Fertility Rates VAAS = value-added contributed by the agricultural sector to GDP GNI = Gross National Incomes per capita LE = Life Expectancy MR = Mortality rate for children under five years AYE = Average Years of Education SPR = Student-Professor Ratio EC = Energy Consumption per capita PP = patent applications by residents per capita Given the database is not complete for all countries or for all years, this missing data was complete through interpolation method. All variables were transformed by mean of logarithms, except GNI. In the case of EC and PP, block of returns on human capital, the manifest variables are transformed such that they may be retrieved in levels at a later stage. 2. Data to estimate the economic growth regressions Cross-section: The file titled “Database – Cross-Section” contains the data with which it is possible to estimate the results shown in tables 1-5 of the manuscript. The variables used and their notation is the following: grow = GDP per capita, rate of change log(gdp75) = lag of GDP in 1975, logarithm demo = a binary variable measuring the level of democracy in the countries contes = indicators by principal component analysis to approximate the degree of contestation inclu = indicators by principal component analysis to approximate the degree of inclusiveness lnihc = human capital index estimated through PLS-PM, logarithm lnaye = average years of education developed by Barro and Lee (2013), logarithm lninves = investment in physical capital, measured as the average share of investment real to GDP, logarithm lngov = average government consumption as a percentage of GDP, logarithm lninfla = inflation measured by consumer prices, logarithm lnpop = population growth rate, logarithm lnich70, lnich75, lnape70, lnape75 lninves70 lninves75 lnpop70 lnpop75 = lags of lnich, lnaye, lninves and lnpop dafri = dummy for African countries Panel data: The file titled “Database – Panel data” contains the data with which it is possible to estimate the results shown in tables 6-9 of the manuscript. All variables are averages for the underlying period. The variables used and their notation is the following: grow = GDP per capita, rate of change lngdp75 = initial GDP in 1975, logarithm demo = a binary variable measuring the level of democracy in the countries contes = indicators by principal component analysis to approximate the degree of contestation inclu = indicators by principal component analysis to approximate the degree of inclusiveness lnihc = human capital index estimated through PLS-PM, logarithm lnaye = average years of education developed by Barro and Lee (2013), logarithm lninves = investment in physical capital, measured as the average share of investment real to GDP, logarithm lngov = average government consumption as a percentage of GDP, logarithm lninfla = inflation measured by consumer prices, logarithm lnpop = population growth rate, logarithm dafri = dummy for African countries

B2B IP Address to Email Linkage Database

Elevate your digital advertising and marketing strategies with Solution Publishing by Allforce "B2B IP Address to Email Linkage Database," a comprehensive dataset offering an unparalleled linkage of 30 million business email addresses to over 90 million IP addresses. This invaluable resource is derived from engagement with our B2B email newsletters, designed to empower businesses to achieve pinpoint accuracy in targeting, enhance cybersecurity, and drive B2B sales with unmatched precision.

Key Features: • Expansive Dataset: Gain access to a vast pool of 30 million business email addresses, each mapped to an average of 3 IP addresses, encompassing a broad spectrum of industries and regions. • Premium Data Quality: Benefit from our meticulously curated and monthly-refreshed dataset, ensuring you receive the most accurate and up-to-date information for your business needs. • Seamless Integration: Effortlessly integrate our database with your existing CRM and marketing automation tools for a streamlined application in your business operations. Benefits: • Targeted Digital Advertising: Utilize precise IP-to-email mappings to refine your digital advertising targeting, ensuring your ads are displayed to the most relevant B2B audience, thus increasing ROI on ad spend. • Enhanced Email Campaigns: Personalize and optimize your email marketing efforts with our data, leading to higher engagement rates and improved campaign performance. • Robust Cybersecurity: Strengthen your security measures by correlating IP addresses with business emails, helping to detect and mitigate potential threats more effectively. • Informed Decision-Making: Leverage our comprehensive dataset to fuel data-driven strategies in marketing, sales, and beyond, enabling smarter business decisions. Applications: • Precision in Digital Advertising: Harness the power of IP address targeting to deliver your digital ads to the specific business audience, enhancing the efficiency of programmatic advertising campaigns and reducing ad waste. • Sales and Marketing Alignment: Equip your teams with detailed lead insights, fostering more effective sales pitches and marketing messages tailored to the audience's specific needs and behaviors. • Threat Detection and Prevention: Use our dataset to augment your cybersecurity protocols, identifying suspicious activities by matching IP addresses with corresponding business emails. • Market Trends Analysis: Perform thorough market analysis to uncover trends, gauge competitor activity, and understand customer preferences, driving strategic business decisions.

The "B2B IP Address to Email Linkage Database" is an essential tool for businesses aiming to revolutionize their approach to digital advertising, cybersecurity, and B2B engagement. Offered exclusively on Datarade.ai, this database is the cornerstone for leveraging digital intelligence to target ads more effectively, secure business operations, and unlock growth opportunities.

With Solution Publishing's rich heritage in data-driven solutions, tap into the potential of precise IP address data to transform your digital advertising strategies and achieve unparalleled success in your B2B endeavors.

This dataset contains special education indicators since 2017. It is a long file that contains multiple rows for each district, with rows for different years, comparing students with disabilities, students without disabilities, and all students on a wide range of indicators. Not all indicators are available for all years. For definitions of each indicator, please visit the RADAR Special Education Dashboard.

Resource Allocation and District Action Reports (RADAR) enable district leaders to compare their staffing, class size, special education services, school performance, and per-pupil spending data with similar districts. They are intended to support districts in making effective strategic decisions as they develop district plans and budgets.

This dataset is one of five containing the same data that is also published in the RADAR Special Education Dashboard: Special Education Program Characteristics and Student Demographics Special Education Placement Trajectory Students Moving In and Out of Special Education Services Special Education Indicators Special Education Student Progression from High School through Postsecondary Education

Below is a list of indicators that are included within the dataset. Note: "Student progression from high school through second year of postsecondary education" and "Student progression from high school through postsecondary degree completion" are available for download in this companion dataset. These two indicators are separate from the main Special Education Indicators download since the data are in a different format.

List of Indicators

Context

• Stability rate (enrolled all year)
• Student Enrollment

• 4-year cohort graduation rate
• 5-year cohort graduation rate
• 9th to 10th grade promotion rate (first-time 9th graders only)
• Annual dropout rate
• Chronically absent rate (% of students absent 10% or more each year)
• Student attendance rate
• Students absent 10 or more days each year
• Students suspended in school at least once
• Students suspended out-of-school at least once

• Average student growth percentiles (SGP) in ELA (Grades 3-8)
• Average student growth percentiles (SGP) in ELA (Grade 10)
• Average student growth percentiles (SGP) in math (Grades 3-8)
• Average student growth percentiles (SGP) in math (Grade 10)
• Meeting or exceeding expectations on ELA (Grades 3-8)
• Meeting or exceeding expectations on ELA (Grade 10)
• Meeting or exceeding expectations on math (Grades 3-8)
• Meeting or exceeding expectations on math (Grade 10)
• Meeting or exceeding expectations on science (Grades 5 and 8)
• Meeting or exceeding expectations on science (Grade 10)

• Jr / Sr AP test takers scoring 3 or above
• Jr / Sr enrolled in one or more AP / IB courses
• Jr / Sr who took AP courses and participated in one or more AP tests
• SAT average score - Mathematics
• SAT average score - reading

• 12th graders passing a full year of mathematics coursework
• 12th graders passing a full year of science and technology/engineering coursework
• 9th graders completing and passing all courses
• High school graduates who completed MassCore

• College students persistently enrolled in postsecondary education for the first two years
• High school graduates enrolled in 2-year postsecondary education
• High school graduates enrolled in 4-year postsecondary education
• Students enrolled in postsecondary education in the immediate fall after high school graduation
• Student progression from high school through postsecondary degree completion
• Student progression from high school through second year of postsecondary education

• Special education director FTE
• Special education teachers per 100 SWD
• Special education paraprofessionals per 100 SWD
• Special education support staff per 100 SWD

Temperature, Emissions & Environmental Trends (2000-2024)

This dataset provides a comprehensive overview of key environmental indicators collected over a span of 24 years (2000–2024) across multiple countries. It is designed to support analyses that explore the interplay between climate variables, human activities, and environmental changes. The dataset is particularly useful for researchers, data scientists, and policy analysts interested in climate change, sustainability, and environmental impact studies.

Key Features:

• Year: Indicates the calendar year of each record.
• Country: The country from which the data was recorded.
• Avg_Temperature_degC: Average annual temperature in degrees Celsius, offering insights into regional and global warming trends.
• CO2_Emissions_tons_per_capita: Annual per capita carbon dioxide emissions, a critical metric for assessing environmental impact and sustainability.
• Sea_Level_Rise_mm: Measured sea level rise in millimeters, useful for understanding coastal and climate-related risks.
• Rainfall_mm: Total annual rainfall in millimeters, which can be analyzed in relation to climate variability and water resource management.
• Population: The total population of the country, providing context for per capita analyses.
• Renewable_Energy_pct: The percentage of energy derived from renewable sources, highlighting progress towards sustainable energy transitions.
• Extreme_Weather_Events: The number of recorded extreme weather events, enabling studies of climate variability and disaster management.
• Forest_Area_pct: The percentage of land covered by forests, an important indicator of ecological health and carbon sequestration potential.

Applications:

• Climate Change Analysis: Explore trends in temperature, sea level rise, and extreme weather events to better understand global warming and its impacts.
• Environmental Policy: Assess the effectiveness of policies aimed at reducing CO2 emissions and increasing renewable energy usage.
• Sustainability Studies: Investigate the relationships between population growth, environmental degradation, and forest cover changes.
• Time Series Forecasting: Use historical data to predict future environmental conditions and inform mitigation strategies.

Data Source:

The dataset is curated with high-quality environmental metrics and is referenced from OpenML, ensuring a robust foundation for academic research and policy analysis.

The main stock market index of United States, the US500, rose to 6173 points on June 27, 2025, gaining 0.52% from the previous session. Over the past month, the index has climbed 4.83% and is up 13.05% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on June of 2025.

Data includes: board and school information, grade 3 and 6 EQAO student achievements for reading, writing and mathematics, and grade 9 mathematics EQAO and OSSLT. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools.

How Are We Protecting Privacy?

Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented.

* Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. * Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up.

The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible.

This information is also available on the Ministry of Education's School Information Finder website by individual school.

Descriptions for some of the data types can be found in our glossary.

School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 149 zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than 394 zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just two percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of 19.2 percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached 6.7 zettabytes.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

Single Family Home Prices in the United States increased to 422800 USD in May from 414000 USD in April of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset provides values for EMPLOYMENT RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.