As of 2025, approximately 93.1 percent of the United States' population accessed the internet, up from approximately 71 percent in 2013. The United States is one of the biggest online markets worldwide. Additionally, in 2025, over 322 million individuals in the country went online. Furthermore, social media apps were among the most popular category of mobile apps used in the market. Social media usage in the U.S. Social media usage in the United States has seen significant growth in recent years, amassing 310 million as of 2025. By the third quarter of 2024, internet users in the U.S. were spending around two hours on social media out of seven hours of internet usage. The most common activities among U.S. users include sending private messages and liking posts or following people, which highlights widespread engagement with social media platforms among internet users in the United States. TikTok surge in the U.S. TikTok continues to be one of the most popular social media platforms in the United States. As of February 2025, over 135 million individuals or 45 percent of internet users in the country used the social network. This surge in popularity is the result of user’s high engagement with short-form videos and quick entertainment in which TikTok managed to capture users’ attention. Users in the United States spent an average of 45 hours and 37 minutes monthly in 2023.

In November 2021, it was found that Idaho had the highest online penetration rate among all the states in the U.S., as 88.6 percent of the state's population used the internet. Wisconsin and Illinois ranked second with 87.8 percent of online access in both states, while Oregon followed, with 87.4 percent.

Graph and download economic data for Internet users for the United States (ITNETUSERP2USA) from 1990 to 2023 about internet, persons, and USA.

According to United States census data, 91.2 percent of all U.S. households reported having some form internet subscription in 2022. This was up from 90.3 percent of households in 2021.

These datasets contain measures of internet access per United States census tract and ZIP code tabulation area (ZCTA) from the 2015-2019 American Community Survey five-year estimate. Key variables include the number and percent of households per tract or ZCTA with any type of internet subscription, with broadband internet, and with a computer or smartphone.

In 2019, 90.4 percent of households in Colorado used a broadband internet connection at home. Washington, Utah, and Colorado were the only three states with over 90 percent of households having a broadband connection at home.

Internet Access Connection: Pennsylvania data was reported at 16,344.000 Number th in Dec 2017. This records an increase from the previous number of 15,989.000 Number th for Jun 2017. Internet Access Connection: Pennsylvania data is updated semiannually, averaging 5,411.000 Number th from Dec 2000 (Median) to Dec 2017, with 35 observations. The data reached an all-time high of 16,344.000 Number th in Dec 2017 and a record low of 177.000 Number th in Dec 2000. Internet Access Connection: Pennsylvania data remains active status in CEIC and is reported by Federal Communications Commission. The data is categorized under Global Database’s United States – Table US.TB021: Internet Access.

As of November 2021, it was found that around 82 percent of the population of the United States aged 25 to 44 years were living in households with internet access. In comparison, 69 percent of the population aged 65 years and older had internet access at home.

Part of the What Works Cities criterion to achieve Certification, we need to meet the industry standard of at least 75% of our households have subscriptions / access to high-speed broadband servicesPart of the American Community Survey (ACS) asks the levels of internet access residents have. We use the 5-Year Estimates to have a greater level of precision to our data, according to the Distinguishing features of ACS 1-year, 1-year supplemental, 3-year, and 5-year estimates table.We query attributes of the DP02 (Selected Social Characteristics in the United States) Group of questions for years available.This dataset has been narrowed down to Cary township using following the geographies codes supported for the ACS dataset:state: 37county: 183county subdivision: 90536

The internet service providers industry uses wired infrastructure to provide clients with internet access and related services, like web hosting, web page designing and consulting related to internet connectivity. Rising internet usage has benefited industry revenue growth, and government-subsidized network expansion has done the same, increasing the number of US broadband connections. A push toward broadband expansion in rural markets and a climb in demand from business customers has boosted industry revenue, which is poised to incline at an annualized rate of 3.5% to $168.5 billion in 2025, including growth of 4.2% in 2025 as investments and activity mount in line with an improving macroeconomic environment. As households increasingly rely on the internet for streaming, gaming, remote work, and cloud computing, ISPs are scrambling to deliver faster and more reliable service. The rising adoption of cloud computing, which involves accessing data online, has boosted demand for dedicated internet access services sold at a higher profit. With increasing demand, providers have begun launching fiber optic networks, rapidly improving connection speeds. Major enterprises that typically benefit from economies of scale also continue to bundle TV and phone, which includes Voice over Internet Protocol services and high-speed internet into one service package, adopting new technology. Consolidation has swept the industry, with blockbuster mergers—such as T-Mobile’s tie-up with Sprint and Verizon’s multi-billion-dollar acquisition push—reshaping market share and intensifying competition. At the same time, average broadband speeds have more than doubled, but ISPs have faced mounting pressure from cord-cutters, OTT competitors and fierce price wars, often leading to flat or declining revenues per user even as consumer bandwidth use reaches new heights. This competitive environment has led to plummeting profit. Looking ahead, the ISP industry shows no sign of slowing down. Over the next five years, fiber expansion and 5G fixed wireless will reach an even greater share of US households. Providers will continue investing heavily in gigabit networks, edge computing and advanced Wi-Fi to keep pace with the explosion in cloud computing, IoT devices and remote work. Retaining customers will hinge on delivering faster speeds, greater reliability, strong security and innovative value-added services, especially as open-access networks and new entrants threaten to erode traditional market advantages. Continued demand will lead to industry revenue growth, poised to climb at an annualized rate of 4.4% to $208.9 billion in 2030.

Information on access to the internet and broadband subscriptions in New York City by select demographic groups, according to data from the American Community Survey.

Internet Access Connection: Business: Kentucky data was reported at 590.000 Number th in Dec 2017. This records an increase from the previous number of 569.000 Number th for Jun 2017. Internet Access Connection: Business: Kentucky data is updated semiannually, averaging 274.000 Number th from Dec 2000 (Median) to Dec 2017, with 35 observations. The data reached an all-time high of 590.000 Number th in Dec 2017 and a record low of 16.000 Number th in Jun 2001. Internet Access Connection: Business: Kentucky data remains active status in CEIC and is reported by Federal Communications Commission. The data is categorized under Global Database’s United States – Table US.TB021: Internet Access.

This layer shows computer ownership and internet access by income group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of households without a broadband internet subscription. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B28004Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

United States Internet Access Connection: Business: Wisconsin data was reported at 956.000 Number th in Dec 2017. This records a decrease from the previous number of 963.000 Number th for Jun 2017. United States Internet Access Connection: Business: Wisconsin data is updated semiannually, averaging 376.000 Number th from Dec 2000 (Median) to Dec 2017, with 35 observations. The data reached an all-time high of 963.000 Number th in Jun 2017 and a record low of 18.000 Number th in Dec 2000. United States Internet Access Connection: Business: Wisconsin data remains active status in CEIC and is reported by Federal Communications Commission. The data is categorized under Global Database’s United States – Table US.TB021: Internet Access.

This dataset contains measures of broadband internet access and usage per United States ZIP code tabulation area (ZCTA) in 2014 through 2018. The data is derived primarily from internet service providers’ Form 477 reports to the Federal Communications Commission. Key variables include the average upload and download speed of fixed broadband connections, the number of internet service providers, and the number of households with broadband.

This layer shows computer ownership and internet access by education. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of the population age 25+ who are high school graduates (includes equivalency) and have some college or associate's degree in households that have no computer. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B28006 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This graph shows the percentage of American household with access to or internet subscription in 2017, sorted by region. During the survey period, 81.9 percent of households in the South had an internet subscription.

Forecast: Households with Internet Access at Home in the US 2024 - 2028 Discover more data with ReportLinker!

Graph and download economic data for Real personal consumption expenditures: Services: Internet access (DINTRX1A020NBEA) from 2007 to 2024 about internet, PCE, consumption expenditures, consumption, personal, services, real, GDP, and USA.

This layer shows computer ownership and internet access by age and race. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of population age 18 to 64 in households with no computer. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B28005, B28003, B28009B, B28009C, B28009D, B28009E, B28009F, B28009G, B28009H, B28009I Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.