East Baton Rouge Parish Library computer usage statistics are organized by branch, year, and month. This dataset only includes the count for library patrons who have logged in to the Library’s public computers, located at any of the 14 locations.

As of 2024, the estimated number of internet users worldwide was 5.5 billion, up from 5.3 billion in the previous year. This share represents 68 percent of the global population. Internet access around the world Easier access to computers, the modernization of countries worldwide, and increased utilization of smartphones have allowed people to use the internet more frequently and conveniently. However, internet penetration often pertains to the current state of development regarding communications networks. As of January 2023, there were approximately 1.05 billion total internet users in China and 692 million total internet users in the United States. Online activities Social networking is one of the most popular online activities worldwide, and Facebook is the most popular online network based on active usage. As of the fourth quarter of 2023, there were over 3.07 billion monthly active Facebook users, accounting for well more than half of the internet users worldwide. Connecting with family and friends, expressing opinions, entertainment, and online shopping are amongst the most popular reasons for internet usage.

As of the second quarter of 2025, around ** percent of men aged 65 and older used a laptop or desktop computer to go online. Women of the same age group were less likely to use a computer to go online, around ** percent. Overall, the usage of computers was lower among younger age groups.

Statistics of how many adults access the internet and use different types of technology covering:

home internet access

how people connect to the web

how often people use the web/computers

whether people use mobile devices

whether people buy goods over the web

whether people carried out specified activities over the internet

For more information see the ONS website and the UKDS website.

As of the second quarter of 2025, approximately **** percent of internet users worldwide accessed the web via smartphones, making them the most commonly used device for going online. Laptops and desktop computers ranked second, with nearly ** percent of users. Online video consumption In 2023, texting and watching online videos were among the most popular activities for smartphone users worldwide. By the first quarter of 2024, ** percent of internet users globally were watching online videos monthly. TikTok is a prime example of this trend, as it became the platform where U.S. adults spent more daily time than on any other social media app as of June 2023. Gaming and live-streaming Video game streaming has become a leading trend in watched video content, accounting for ** percent of online reach by the fourth quarter of 2024. This growth is driven mostly by the shift from single player to multiplayer gaming. For example, the multiplayer game Grand Theft Auto V was the most-watched game, with over *** million monthly watch hours across live-streaming platforms in June 2024. On Twitch alone, gamers watched over *** billion hours of live-streamed content in the first quarter of 2024.

Local libraries and community organizations that will allow you to use computers free of charge. Some locations also offer the following resources: Wi-fi, Printing, Internet, iPad rental, Classes, and special areas for kids and teens.

This layer shows Computers and Internet Use. This is shown by state and county boundaries. This service contains the 2017-2021 release of data from the 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 Percentage of Households with 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: 2018-2022ACS Table(s): DP02, S2801Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 2022National 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. 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:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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 Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. 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.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

3. description: Provides a concise description of the variable.

4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

DEMOGRAPHIC CATEGORIES

1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

5. education: Educational attainment is divided into "No Diploma," "High School Grad," "Some College," and "College Grad." High school graduates are considered to include GED completers, and those with some college include community college attendees (and graduates) and those who have attended certain postsecondary vocational or technical schools--in other words, it signifies additional education beyond high school, but short of attaining a bachelor's degree or equivilent. Note that educational attainment is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by education, even if they are otherwise considered part of the universe for the variable of interest.

6. sex: "Male" and "Female" are the two groups in this category. The CPS does not currently provide response options for intersex individuals.

7. race: This category includes "White," "Black," "Hispanic," "Asian," "Am Indian," and "Other" groups. The CPS asks about Hispanic origin separately from racial identification; as a result, all persons identifying as Hispanic are in the Hispanic group, regardless of how else they identify. Furthermore, all non-Hispanic persons identifying with two or more races are tallied in the "Other" group (along with other less-prevelant responses). The Am Indian group includes both American Indians and Alaska Natives.

8. disability: Disability status is divided into "No" and "Yes" groups, indicating whether the person was identified as having a disability. Disabilities screened for in the CPS include hearing impairment, vision impairment (not sufficiently correctable by glasses), cognitive difficulties arising from physical, mental, or emotional conditions, serious difficulty walking or climbing stairs, difficulty dressing or bathing, and difficulties performing errands due to physical, mental, or emotional conditions. The Census Bureau began collecting data on disability status in June 2008; accordingly, this category is unavailable in Supplements prior to that date. Note that disability status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by disability status, even if they are otherwise considered part of the universe for the variable of interest.

9. metro: Metropolitan status is divided into "No," "Yes," and "Unkown," reflecting information in the dataset about the household's location. A household located within a metropolitan statistical area is assigned to the Yes group, and those outside such areas are assigned to No. However, due to the risk of de-anonymization, the metropolitan area status of certain households is unidentified in public use datasets. In those cases, the Census Bureau has determined that revealing this geographic information poses a disclosure risk. Such households are tallied in the Unknown group.

10. scChldHome:

In 2019, almost half of private households worldwide were estimated to have a computer at home. In developing countries, the PC penetration rate is lower with around a third of households having a computer. In contrast the share of households with a personal computer in developed countries was closer to 80 percent. In general, the share of households with a computer has steadily increased worldwide as computer usage and internet access is becoming more prevalent around the world.

PC sales declining despite higher penetration

As the share of households with a PC has been on the rise, so too were global PC unit sales have in recent years. This has come despite the still growing popularity and usage of smartphones which some analysts thought would render owning a PC as an additional device superfluous for many people. Segments of the PC market are increasing in sales value more than others: the amount of PC gaming device shipments worldwide is expected to reach over 61 million units by 2020. Worldwide gaming laptop sales alone have reached a revenue of 11 billion U.S. dollars in 2020. The gaming industry drives many innovations in PC design, as personal computers are often used for such focused tasks.

PC utilization

PCs have been used for many activities, such as watching online videos, playing computer games, and completing work tasks. Though computers or laptops are still among the most used devices to watch online videos among users worldwide, smartphones are now used more frequently in many different contexts. One of the advantages of using PCs was its connectivity, as internet usage was possible through the high-speed fixed broadband connections desktop computers offer. Yet now, with the advent of 5G technology, growing mobile broadband might decrease the stationary use of PCs even further.

Latvia Computer Usage: Individuals: Men data was reported at 84.100 % in 2016. This records an increase from the previous number of 82.300 % for 2014. Latvia Computer Usage: Individuals: Men data is updated yearly, averaging 74.100 % from Dec 2003 (Median) to 2016, with 13 observations. The data reached an all-time high of 84.100 % in 2016 and a record low of 55.000 % in 2003. Latvia Computer Usage: Individuals: Men data remains active status in CEIC and is reported by Central Statistical Bureau of Latvia. The data is categorized under Global Database’s Latvia – Table LV.TB001: Computer and Internet Usage.

Computer Use Dataset - PSAI

A large-scale, multimodal dataset of human-computer interactions for training and evaluating AI agents.

🔗 Access Dataset: https://huggingface.co/datasets/anaisleila/computer-use-data-psai

  📊 Dataset Overview

This dataset contains 3,167 completed tasks of human-computer interactions captured with video, screenshots, DOM snapshots, and detailed interaction events. Created by Paradigm Shift AI for advancing computer use AI agent research.… See the full description on the dataset page: https://huggingface.co/datasets/anaisleila/computer-use-data-psai.

Information on person and household broadband (high-speed Internet) use, where it is used, by what types of devices, what type of service provider, and other characteristics.

Morocco ICT Usage: Households: Computer & or Tablet data was reported at 60.600 % in 2018. This records an increase from the previous number of 58.400 % for 2017. Morocco ICT Usage: Households: Computer & or Tablet data is updated yearly, averaging 39.000 % from Dec 2004 (Median) to 2018, with 15 observations. The data reached an all-time high of 60.600 % in 2018 and a record low of 11.000 % in 2004. Morocco ICT Usage: Households: Computer & or Tablet data remains active status in CEIC and is reported by National Telecommunication Regulatory Agency. The data is categorized under Global Database’s Morocco – Table MA.TB001: Internet Statistics.

Dataset from Info-communications Media Development Authority. For more information, visit https://data.gov.sg/datasets/d_60b6af0457f16ed39dba466386f5fc9b/view

This web map visualizes the prevalence of households in a given geography that do not own a computer, smartphone, or tablet. Data are shown by tract, county, and state boundaries -- zoom out to see data visualized for larger geographies. The map also displays the boundary lines for the jurisdiction of Rochester, NY (visible when viewing the tract level data), as this map was created for a Rochester audience.This web map draws from an Esri Demographics service that is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. 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: 2014-2018ACS Table(s): B28001, B28002 (Not all lines of ACS table B28002 are available in this feature layer)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 19, 2019National 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. 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. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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., -555555...) have been set to null. 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. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

How often Persons used a Computer or used the Internet in the last 3 months by Principal Economic Status, Year, Statistic and Frequency of Use

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This dataset shows the number and percentage of Qatari individuals aged 4 years and above who use computers, categorized by age group and place of usage, based on the 2020 Census.

Latvia Computer Usage: Individuals data was reported at 84.100 % in 2016. This records an increase from the previous number of 81.700 % for 2014. Latvia Computer Usage: Individuals data is updated yearly, averaging 72.900 % from Dec 2003 (Median) to 2016, with 13 observations. The data reached an all-time high of 84.100 % in 2016 and a record low of 54.500 % in 2003. Latvia Computer Usage: Individuals data remains active status in CEIC and is reported by Central Statistical Bureau of Latvia. The data is categorized under Global Database’s Latvia – Table LV.TB001: Computer and Internet Usage.

The global number of households with a computer in was forecast to continuously increase between 2024 and 2029 by in total 88.6 million households (+8.6 percent). After the fifteenth consecutive increasing year, the computer households is estimated to reach 1.1 billion households and therefore a new peak in 2029. Notably, the number of households with a computer of was continuously increasing over the past years.Computer households are defined as households possessing at least one computer.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of households with a computer in countries like Caribbean and Africa.