During a survey carried out among UK consumers, ** percent of respondents stated it was most important to see safe and appropriate content on social media. News websites ranked second, named by ** percent of the interviewed consumers.

In 2021, ** percent of the online traffic on household appliances and electronics e-shop websites in Russia stemmed from online search. Direct access to such web pages generated ** percent of the viewer flow. Social networks and media advertising accounted for three and two percent of the traffic on this marketplace segment over the period under consideration, respectively.

Introduction

Social Media Marketing Statistics: Social media marketing is a key part of any digital marketing plan today. With over 50% of the world’s population using social media, brands need to be active on these platforms. But it’s not just about making profiles and posting content. Effective social media marketing involves keeping up with changing algorithms and trends and understanding the behaviors of your target audience. Social media’s interactive and engaging nature helps businesses connect with their audience in ways they couldn’t before.

This opens up new opportunities for engaging with people, building the brand, and doing direct marketing. We shall shed more light on Social Media Marketing Statistics through this article.

Comprehensive dataset of 12 Superfund sites in Vietnam as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Mobile Views of AustinGO Site

This group includes the provision of infrastructure for hosting, data processing services and related activities, as well as search facilities and other portals for the Internet.

The Ecommerce Website Platform market has emerged as a crucial component in the digital economy, catering to the needs of businesses seeking to establish an online presence. With the rapid growth of online shopping, these platforms provide comprehensive solutions for retailers, enabling them to create, manage, and s

This folder contains 3 .csv files which contain all the observations for the suite of major ion and nutrient constituents for the Heart River Basin. These files contain the water-quality observations for the statistical summary tables in the report cited in this data release (Tatge and others, 2021).The allsiteinfo.table.csv file can be used to cross reference the sites with the main report (Tatge and others, 2021). Tatge, W.S., Nustad, R.A., and Galloway, J.M., 2021, Evaluation of Salinity and Nutrient Conditions in the Heart River Basin, North Dakota, 1970-2020: U.S. Geological Survey Scientific Investigations Report 2021-XXXX, XX p.

Market Size and Growth: The website visitor tracking software market is projected to reach USD XX million by 2033, expanding at a CAGR of XX% from 2025 to 2033. The market is driven by the increasing adoption of digital marketing and analytics, as businesses seek to understand their website visitors' behavior and optimize their marketing campaigns. The growing demand for data privacy and compliance regulations is also fueling market growth. Industry Trends and Dynamics: The website visitor tracking software market is experiencing several trends, including the rise of cloud-based solutions, the integration of artificial intelligence (AI) and machine learning (ML) for enhanced data analysis, and the increased focus on personalization and customer segmentation. Key players in the market include Visitor Queue, Crazy Egg, VWO Insights, Leadfeeder, and Google Analytics, among others. The competitive landscape is characterized by strategic partnerships, acquisitions, and product innovations. Regional markets are also witnessing significant growth, particularly in North America, Europe, and Asia Pacific, as businesses across these regions embrace digital transformation and customer-centric strategies.

This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal bed resource areas and attributed with statistics on the thickness of the Pond Creek coal zone, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.

In March 2024, Twitch.tv was the leading gaming website in Sweden. During the measured period, the video streaming platform accounted for over 15.95 percent of desktop traffic in the games subcategory. Creative gaming platform roblox.com was ranked second with a 3.86 percent market share of visits.

Traffic Volumes from SCATS Traffic Management System Jan-Jun 2022 DCC. Published by Dublin City Council. Available under the license cc-by (CC-BY-4.0).Traffic volumes data across Dublin City from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site. The vehicle sensors are generally inductive loops installed within the road.

3 resources are provided:

SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows.

Information provided:

End Time: time that one hour count period finishes.

Region: location of the detector site (e.g. North City, West City, etc).

Site: this can be matched with the SCATS Sites file to show location

Detector: the detectors/ sensors at each site are numbered

Sum volume: total traffic volumes in preceding hour

Avg volume: average traffic volumes per 5 minute interval in preceding hour

All Dates Traffic Volumes Data

This file contains daily totals of traffic flow at each site location.

SCATS Site Location Data Contained in this report, the location data for the SCATS sites is provided. The meta data provided includes the following;

Site id – This is a unique identifier for each junction on SCATS

Site description( CAP) – Descriptive location of the junction containing street name(s) intersecting streets

Site description (lower) - – Descriptive location of the junction containing street name(s) intersecting streets

Region – The area of the city, adjoining local authority, region that the site is located

LAT/LONG – Coordinates

Disclaimer: the location files are regularly updated to represent the locations of SCATS sites under the control of Dublin City Council. However site accuracy is not absolute. Information for LAT/LONG and region may not be available for all sites contained. It is at the discretion of the user to link the files for analysis and to create further data. Furthermore, detector communication issues or faulty detectors could also result in an inaccurate result for a given period, so values should not be taken as absolute but can be used to indicate trends....

Analysis of ‘United States COVID-19 Cases and Deaths by State over Time’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/94385ab5-449a-41ff-8253-15a9f6283539 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

CDC reports aggregate counts of COVID-19 cases and death numbers daily online. Data on the COVID-19 website and CDC’s COVID Data Tracker are based on these most recent numbers reported by states, territories, and other jurisdictions. This data set of “United States COVID-19 Cases and Deaths by State over Time” combines this information. However, data are dependent on jurisdictions’ timely and accurate reporting.

Separately, CDC also regularly reports provisional death certificate data from the National Vital Statistics System (NVSS) on data.cdc.gov. Details are described on the NCHS website. Reporting the number of deaths by using death certificates ultimately provides more complete information but is a longer process; therefore, these numbers will be less than the death counts on the COVID-19 website.

Accuracy of Data
CDC tracks COVID-19 illnesses, hospitalizations, and deaths to track trends, detect outbreaks, and monitor whether public health measures are working. However, counting exact numbers of COVID-19 cases is not possible. COVID-19 can cause mild illness, symptoms might not appear immediately, there are delays in reporting and testing, not everyone who is infected gets tested or seeks medical care, and there are differences in how completely states and territories report their cases.

COVID-19 is one of about 120 diseases or conditions health departments voluntarily report to CDC. State, local, and territorial public health departments verify and report cases to CDC. When there are differences between numbers of cases reported by CDC versus by health departments, data reported by health departments should be considered the most up to date. Health departments may update case data over time when they receive more complete and accurate information. The number of new cases reported each day fluctuates. There is generally less reporting on the weekends and holidays.

CDC reports death data on three other sections of the website: U.S. Cases & Deaths, COVID Data Tracker, and NCHS Provisional Death Counts. The U.S. Cases and Deaths webpages and COVID Data Tracker get their information from the same source (total case counts); however, NCHS Death Counts are based on death certificates that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Data from each of these pages are considered provisional (not complete and pending verification) and are therefore subject to change. Counts from previous weeks are continually revised as more records are received and processed. Because not all jurisdictions report counts daily, counts may increase at different intervals.

Confirmed & Probable Counts
As of April 14, 2020, CDC case counts and death counts include both confirmed and probable cases and deaths. This change was made to reflect an interim COVID-19 position statement issued by the Council for State and Territorial Epidemiologists on April 5, 2020. The position statement included a case definition and made COVID-19 a nationally notifiable disease. Nationally notifiable disease cases are voluntarily reported to CDC by jurisdictions. Confirmed and probable case definition criteria are described here: https://wwwn.cdc.gov/nndss/conditions/coronavirus-disease-2019-covid-19/case-definition/2020/. Not all jurisdictions report probable cases and deaths to CDC. When not available to CDC, it is noted as N/A. Please note that jurisdiction

--- Original source retains full ownership of the source dataset ---

Households in sample (Number) by Region and Year

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The data set consists of evapotranspiration measurements made at the USGS Dead River forested wetland climate station beginning November 21, 2009 and ending February 29, 2016. Annual ET rates corrected to a near-surface energy-budget varied from 1448 mm (2012) to 1614 mm (2010). The eddy-covariance method was used, with high-frequency sensors installed above the forest canopy to measure sensible and latent heat fluxes. Ancillary meteorological data are also included in the data set: net radiation, soil temperature and moisture, air temperature, relative humidity, wind speed and direction, rainfall, and ground-water levels. Data were collected at 30-minute resolution, with evapotranspiration corrected to the near-surface energy-budget at a daily timescale. The study was conducted at an undeveloped mixed hardwood swamp within Dead River Wilderness Park, located at the end of Dead River Rd., west of U.S. Highway 301, 27 km northeast of Tampa in Hillsborough County, Florida (latitude 28 07’ 43” N longitude 82 15’ 44” W, Section 13, Township 27S, Range 20E). Study instruments were installed in November 2009. The 46-m instrument tower was located about 90 m northeast of the final pullout before the parking area, which is 2.6 km from the park entrance gate on Dead River Rd. The station is within the Hillsborough River floodplain, and is inundated at high river stages (Lewelling, 2004). The site is classified as a freshwater palustrine forested broad-leaf deciduous wetland that is seasonally flooded (U.S. Fish and Wildlife Service, 2010). Dominant tree species are cabbage palm (Sabal palmetto), red maple (Acer rubrum), sweet-gum (Liquidambar styraciflua), live oak (Quercus virginiana), elm (Ulmus americana), with occasional slash pine, magnolia, and hickory. Canopy height is 20-24 m. The site is located near the middle of the floodplain at least 1 km away from different land cover types in all directions. The floodplain extends farther to the northeast and southwest along the path of the river. The soils at the site are Chobee sandy loam, frequently flooded, which are nearly level, very poorly drained bottomland soils with a surface layer of black sandy loam. The subsoil is dark to very dark gray mottled sandy clay loam (Soil Conservation Service, 1989). Clay dominates in the subsoil to the east of the station based on holes dug for the tower guy cable bases. Lewelling, B.R., 2004. Extent of areal inundation of riverine wetlands along five river systems in the Upper Hillsborough River Watershed, west-central Florida: U.S. Geological Survey Scientific Investigations Report 2004-5133, 49 p., plus appendixes. Soil Conservation Service, 1989. Soil survey of Hillsborough County, Florida: U.S. Department of Agriculture, Soil Conservation Service, 168 p. U.S. Fish and Wildlife Service, 2010. National Wetlands Inventory website: U.S. Department of Interior, Washington, D.C. http://www.fws.gov/wetlands/

This dataset contains statistics on the number of tourist arrivals from different countries (USA, Canada, UK, Germany) on a monthly basis for the year 2024.

The Office of Gun Violence Prevention (OGVP) shares real-time gun violence data to increase government transparency, improve the public's awareness, and support community-based gun violence prevention and reduction partners. All District crime data is available through Crime Cards. The dashboards below focus on gun violence only. The data in these dashboards is updated daily at 7:40AM with the incidents from the day before. View data covering 7-Day Look-back of Gun Violence and Year-to-date Gun Violence.All statistics presented here are based on preliminary DC criminal code offense definitions. The data do not represent official statistics submitted to the FBI under the Uniform Crime Reporting program (UCR) or National Incident Based Reporting System (NIBRS). All preliminary offenses are coded based on DC criminal code and not the FBI offense classifications. Please understand that any comparisons between MPD preliminary data as published on this website and the official crime statistics published by the FBI under the Uniform Crime Reporting Program (UCR) are inaccurate and misleading. The MPD does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information. The MPD will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. Read complete data notes at buildingblocks.dc.gov/data.