How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.
VITAL SIGNS INDICATOR List Rents (EC9)
FULL MEASURE NAME List Rents
LAST UPDATED October 2016
DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.
DATA SOURCE real Answers (1994 – 2015) no link
Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/
CONTACT INFORMATION vitalsigns.info@mtc.ca.gov
METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.
Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.
Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.
Inflation-adjusted data are presented to illustrate how rents have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.
During the third quarter of 2023, internet users in the United States spent over seven hours daily using the internet, with over 4.5 hours spent viewing video content on TV (both broadcast and streamed) as well as more than two hours devoted to using social media platforms. This substantial amount of time spent with online media reflects a significant trend in consumption habits, which have been influenced by the need for inexpensive, faster, and more accessible entertainment.
Media Consumption Trends and Future Plans The average daily time spent with digital media in the United States is expected to increase from 439 minutes (seven hours and 19 minutes) in 2022 to close to eight hours by the end of 2025. This pivot is dictated by the ease of access of online entertainment and variety of content available on numerous platforms.
According to a survey conducted in April 2023, the majority of consumers in the United States were not planning to make any major changes to most of their media habits in the following year. However, a notable 21 percent planned to increase their time spent listening to podcasts. In general, there was an evident shift towards reducing or ending paid subscriptions to numerous media services.
Free entertainment is on social A survey conducted in June 2023 highlighted that adults in the United States spent more time per day on TikTok than on any other leading social media platform, with an average of 53.8 minutes per day. The video sharing network gained more popularity with users than YouTube and Twitter. This underlines the growing interest in short form video and fast entertainment options. Today consumers step away from traditional media and dive into online offers.
VITAL SIGNS INDICATOR Rent Payments (EC8)
FULL MEASURE NAME Median rent payment
LAST UPDATED August 2019
DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time.
DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a
U.S. Census Bureau: American Community Survey 2005-2017 http://api.census.gov Note: Form B25058; 1-YR
Bureau of Labor Statistics: Consumer Price Index 1970-2017 http://www.bls.gov/data/ Note: All Urban Consumers Data Table (by metro)
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.
Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains 30-year rolling average of annual average precipitation across all four models and two greenhouse gas (RCP) scenarios in the four model ensemble. The year identified for a 30 year rolling average is the mid-point of the 30-year average. eg. The year 2050 includes the values from 2036 to 2065.
The downscaling and selection of models for inclusion in ten and four model ensembles is described in 'https://www.energy.ca.gov/sites/default/files/2019-11/Projections_CCCA4-CEC-2018-006_ADA.pdf#page=11' rel='nofollow ugc'>Pierce et al. 2018, but summarized here. Thirty two global climate models (GCMs) were identified to meet the modeling requirements. From those, ten that closely simulate California’s climate were selected for additional analysis ('https://www.energy.ca.gov/sites/default/files/2019-11/Projections_CCCA4-CEC-2018-006_ADA.pdf#page=11' rel='nofollow ugc'>Table 1, Pierce et al. 2018) and to form a ten model ensemble. From the ten model ensemble, four models, forming a four model ensemble, were identified to provide coverage of the range of potential climate outcomes in California. The models in the four model ensemble and their general climate projection for California are:
These data were downloaded from Cal-Adapt and prepared for use within CA Nature by California Natural Resource Agency and ESRI staff.
Cal-Adapt. (2018). LOCA Derived Data [GeoTIFF]. Data derived from LOCA Downscaled CMIP5 Climate Projections. Cal-Adapt website developed by University of California at Berkeley’s Geospatial Innovation Facility under contract with the California Energy Commission. Retrieved from https://cal-adapt.org/
Pierce, D. W., J. F. Kalansky, and D. R. Cayan, (Scripps Institution of Oceanography). 2018. Climate, Drought, and Sea Level Rise Scenarios for the Fourth California Climate Assessment. California’s Fourth Climate Change Assessment, California Energy Commission. Publication Number: CNRA-CEC-2018-006.
This statistic shows the average monthly wireless data usage per user in the United States by age in the first two quarters of 2018. In the first half of 2018, users 25 years and younger used 4.1 GB of cellular and 16.8 GB of Wi-Fi wireless data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia Average Monthly Wages: Year to Date: OKVED2: Activities of Households as Employers; Undifferentiated Goods & Services Producing Activities of Households for Own Use data was reported at 7,125.000 RUB in Dec 2017. This records an increase from the previous number of 6,000.000 RUB for Sep 2017. Russia Average Monthly Wages: Year to Date: OKVED2: Activities of Households as Employers; Undifferentiated Goods & Services Producing Activities of Households for Own Use data is updated quarterly, averaging 6,562.500 RUB from Sep 2017 (Median) to Dec 2017, with 2 observations. The data reached an all-time high of 7,125.000 RUB in Dec 2017 and a record low of 6,000.000 RUB in Sep 2017. Russia Average Monthly Wages: Year to Date: OKVED2: Activities of Households as Employers; Undifferentiated Goods & Services Producing Activities of Households for Own Use data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.GC007: Average Monthly Wages: by Activity: Quarterly and Annual.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Average annual net CO2 emissions from land use change, by department.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This dataset contains a 30-year rolling average of annual average minimum and maximum temperatures from the four models and two greenhouse gas (RCP) scenarios included in the four model ensemble for the years 1950-2099.The year identified is the mid-point of the 30-year average. eg. The year 2050 includes the values from 2036 to 2065.
The downscaling and selection of models for inclusion in ten and four model ensembles is described in Pierce et al. 2018, but summarized here. Thirty two global climate models (GCMs) were identified to meet the modeling requirements. From those, ten that closely simulate California’s climate were selected for additional analysis (Table 1, Pierce et al. 2018) and to form a ten model ensemble. From the ten model ensemble, four models, forming a four model ensemble, were identified to provide coverage of the range of potential climate outcomes in California. The models in the four model ensemble and their general climate projection for California are:
HadGEM2-ES (warm/dry),CanESM2 (average), CNRM-CM5 (cooler/wetter), and MIROC5 the model least like the others to improve coverage of the range of outcomes.
These data were downloaded from Cal-Adapt and prepared for use within CA Nature by California Natural Resource Agency and ESRI staff.
Cal-Adapt. (2018). LOCA Derived Data [GeoTIFF]. Data derived from LOCA Downscaled CMIP5 Climate Projections. Cal-Adapt website developed by University of California at Berkeley’s Geospatial Innovation Facility under contract with the California Energy Commission. Retrieved from https://cal-adapt.org/
Pierce, D. W., J. F. Kalansky, and D. R. Cayan, (Scripps Institution of Oceanography). 2018. Climate, Drought, and Sea Level Rise Scenarios for the Fourth California Climate Assessment. California’s Fourth Climate Change Assessment, California Energy Commission. Publication Number: CNRA-CEC-2018-006.
This dataset provides the average (annual, winter, summer) residential metered water consumption (by year) within 400 m x 400m hexagons (approximately two city blocks) provided in m3/month for the City of Edmonton.
Average monthly residential winter water consumption is the average consumption of the following months: January, February, March, April, October, November and December.
Average monthly residential summer water consumption is the average consumption of the following months: May, June, July, August and September.
Only those hexagons that contain at least ten accounts are illustrated to ensure customer privacy.
Residential consumption refers to water used primarily for domestic purposes, where no more than four separate dwelling units are metered by a single water meter.
Thematic mapping is based on the following ranges:
0-10 m3/month – orange 10-20 m3/month – green 20-30 m3/month – purple 30-35 m3/month – blue 35-60 m3/month – red 60 m3/month and up – maroon
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Commitment Status, Average Months Since Loan (Commitment) Terms Were Set by Base Pricing Rate, Prime, Large Domestic Banks (DISCONTINUED) (ETRPRXSLNQ) from Q2 2003 to Q2 2017 about prime, domestic, loans, banks, depository institutions, rate, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This table shows regional figures on the average consumption of energy (natural gas and electricity) of private dwellings broken down by type of dwelling and ownership for Nederland, group of provinces, provinces and municipalities. Besides, for total dwellings only, the share of heat distribution (district heating) has been added, because this is relevant for the interpretation of the height of the average consumption of natural gas.
Data available from: 2010
Status of the figures: All figures from 2010 - 2021 are definite. Figures of 2022 are provisional.
Changes as of October 2023: Provisional figures of 2022 have been added. Figures of 2021 have been updated. The category “Average consumption of electricity” is replaced by “Average supply of electricity” and a category “Average net supply of electricity” has been added.
When will new figures be published? A revision to the method of this statistic is currently underway, causing the table to be delayed. New figures will come in the 3rd quarter of the folowing year.
During the third quarter of 2023, global internet users spent over six hours daily using the internet, with over three hours spent viewing video content on TV (both broadcast and streamed) as well as more than two hours devoted to using social media platforms. This substantial amount of time spent with online media reflects a significant trend in consumption habits, which have been influenced by the need for inexpensive, faster, and more accessible entertainment.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
Thumbnail image by Tony Moody.This dataset includes all housing developments approved by the City of Boise’s (“city”) Planning Division since 2020 that are known by the city to have received or are expected to receive support or incentives from a government entity. Each row represents one development. Data may be unavailable for some projects and details are subject to change until construction is complete. Addresses are excluded for projects with fewer than five homes for privacy reasons.
The dataset includes details on the number of “homes” in a development. We use the word "home" to refer to any single unit of housing regardless of size, type, or whether it is rented or owned. For example, a building with 40 apartments counts as 40 homes, and a single detached house counts as one home.
The dataset includes details about the phase of each project. The process for build a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.
The dataset also includes data on the affordability level of each development. To receive a government incentive, a developer is typically required to rent or sell a specified number of homes to households that have an income below limits set by the government and their housing cost must not exceed 30% of their income. The federal government determines income limits based on a standard called “area median income.” The city considers housing affordable if is targeted to households earning at or below 80% of the area median income. For a three-person household in Boise, that equates to an annual income of $60,650 and monthly rent or mortgage of $1,516. See Boise Income Guidelines for more details.Project Address(es) – Includes all addresses that are included as part of the development project.Address – The primary address for the development.Parcel Number(s) – The identification code for all parcels of land included in the development.Acreage – The number of acres for the parcel(s) included in the project.Planning Permit Number – The identification code for all permits the development has received from the Planning Division for the City of Boise. The number and types of permits required vary based on the location and type of development.Date Entitled – The date a development was approved by the City’s Planning Division.Building Permit Number – The identification code for all permits the development has received from the city’s Building Division.Date Building Permit Issued – Building permits are required to begin construction on a development.Date Final Certificate of Occupancy Issued – A certificate of occupancy is the final approval by the city for a development, once construction is complete. Not all developments require a certificate of occupancy.Studio – The number of homes in the development that are classified as a studio. A studio is typically defined as a home in which there is no separate bedroom. A single room serves as both a bedroom and a living room.1-Bedroom – The number of homes in a development that have exactly one bedroom.2-Bedroom – The number of homes in a development that have exactly two bedrooms.3-Bedroom – The number of homes in a development that have exactly three bedrooms.4+ Bedroom – The number of homes in a development that have four or more bedrooms.# of Total Project Units – The total number of homes in the development.# of units toward goals – The number of homes in a development that contribute to either the city’s goal to produce housing affordable at or under 60% of area median income, or the city’s goal to create permanent supportive housing for households experiencing homelessness.Rent at or under 60% AMI - The number of homes in a development that are required to be rented at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 61-80% AMI – The number of homes in a development that are required to be rented at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 81-120% AMI - The number of homes in a development that are required to be rented at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Own at or under 60% AMI - The number of homes in a development that are required to be sold at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Own 61-80% AMI – The number of homes in a development that are required to be sold at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Own 81-120% AMI - The number of homes in a development that are required to be sold at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Housing Land Trust – “Yes” if a development receives or is expected to receive this incentive. The Housing Land Trust is a model in which the city owns land that it leases to a developer to build affordable housing.City Investment – “Yes” if the city invests funding or contributes land to an affordable development.Zoning Incentive - The city's zoning code provides incentives for developers to create affordable housing. Incentives may include the ability to build an extra floor or be subject to reduced parking requirements. “Yes” if a development receives or is expected to receive one of these incentives.Project Management - The city provides a developer and their design team a single point of contact who works across city departments to simplify the permitting process, and assists the applicants in understanding the city’s requirements to avoid possible delays. “Yes” if a development receives or is expected to receive this incentive.Low-Income Housing Tax Credit (LIHTC) - A federal tax credit available to some new affordable housing developments. The Idaho Housing and Finance Association is a quasi-governmental agency that administers these federal tax credits. “Yes” if a development receives or is expected to receive this incentive.CCDC Investment - The Capital City Development Corp (CCDC) is a public agency that financially supports some affordable housing development in Urban Renewal Districts. “Yes” if a development receives or is expected to receive this incentive. If “Yes” the field identifies the Urban Renewal District associated with the development.City Goal – The city has set goals to produce housing affordable to households at or below 60% of area median income, and to create permanent supportive housing for households experiencing homelessness. This field identifies whether a development contributes to one of those goals.Project Phase - The process for build a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Brazil CES: 2008-2009: Average Monthly Family Expenditure: Current: Consumption data was reported at 2,134.770 BRL in 2008. This records an increase from the previous number of 1,473.290 BRL for 2002. Brazil CES: 2008-2009: Average Monthly Family Expenditure: Current: Consumption data is updated yearly, averaging 1,804.030 BRL from Jun 2002 (Median) to 2008, with 2 observations. The data reached an all-time high of 2,134.770 BRL in 2008 and a record low of 1,473.290 BRL in 2002. Brazil CES: 2008-2009: Average Monthly Family Expenditure: Current: Consumption data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Domestic Trade and Household Survey – Table BR.HC004: Consumer Expenditure Survey: 2008-2009: Average Monthly Family Expenditure.
People in Japan on average spent 12.5 minutes per weekday on using the internet via a television set in fiscal year 2023. The usage time increased by about two minutes over the previous fiscal year.
In the second quarter of 2023, a web radio listener in Brazil spent, on average, 165 minutes (two hours and 45 minutes) listening to online radio daily, which has remained unchanged since the previous year. In 2022, almost three out of 10 web radio listeners in Brazil were in their thirties.
In 2020, desktop and laptop usage in the United States is projected to increase to an average of two hours per day due to the coronavirus crisis before returning to the downward trend. Coronavirus-related work from home and homeschooling directives have given computer usage a small bump but overall, the majority of digital media minutes are spent via mobile.
How much time do internet users in North America spend consuming media? According to a report from the second half of 2022, they spent most of the time on their PCs, laptops, and tablets consuming media at 3 hours 29 minutes daily. This was followed closely with mobile usage at 3 hours 26 minutes on average. Broadcast TV was consumed for an average of 2 hours 52 minutes per day, while music and online/TV streaming were consumed for 1 hour 54 minutes and 1 hour 52 minutes respectively. The press received the least consumption time with just 41 minutes of print press and 56 minutes of online press. Gaming accounted for an average of 1 hour 22 minutes of consumption time per day.
According to a survey on the daily average usage time of Wi-fi in South Korea in 2019, respondents in their twenties spent the most time using Wi-fi per day with roughly 139.9 minutes spent online. In South Korea a lot of places are offering free Wi-fi and the government realized two public Wi-fi projects, leading to 24,000 city buses being installed with free Wi-fi.
How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.