The average for 2022 based on 167 countries was 50.52 million subscribers. The highest value was in China: 1770 million subscribers and the lowest value was in Palau: 0.02 million subscribers. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

We surveyed 10,208 people from more than 15 countries on their mobile app usage behavior. The countries include USA, China, Japan, Germany, France, Brazil, UK, Italy, Russia, India, Canada, Spain, Australia, Mexico, and South Korea. We asked respondents about: (1) their mobile app user behavior in terms of mobile app usage, including the app stores they use, what triggers them to look for apps, why they download apps, why they abandon apps, and the types of apps they download. (2) their demographics including gender, age, marital status, nationality, country of residence, first language, ethnicity, education level, occupation, and household income (3) their personality using the Big-Five personality traits This dataset contains the results of the survey.

Dataset from Info-communications Media Development Authority. For more information, visit https://data.gov.sg/datasets/d_8fa4828ceee7d00cce976470a934494c/view

Number of Mobile Phone Subscribers: per 1000 Persons: UF: Chelyabinsk Region data was reported at 1.898 Unit th in 2023. This records a decrease from the previous number of 1.898 Unit th for 2022. Number of Mobile Phone Subscribers: per 1000 Persons: UF: Chelyabinsk Region data is updated yearly, averaging 1.752 Unit th from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 2.079 Unit th in 2016 and a record low of 0.003 Unit th in 1999. Number of Mobile Phone Subscribers: per 1000 Persons: UF: Chelyabinsk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TG009: Number of Mobile Phone Subscribers: per 1000 Persons: by Region.

This data presents the Reference Signal Received power for LTE, GSM and HSPA. The Mobile signal measurement were taken around Covenant University, Nigeria. The experiment setup was on an indoor scenario. The data was collected to investigate the best network for Mobile subscribers on roaming services and local subscriber's high performance and data rates. After the experiment, Exploratory Data Analysis (EDA) was used to visualize the best Network; The data can be applied to determine the network services providing the best QoS between 4th Generation LTE/4G, 3rd generation UMTS/HSPA, and GSM. The data is vital for indoor localization applications and the mobile network provider for network optimizationThe experiment was conducted between July 1 and July 30, 2020. Measurements were taken from 7:30 am to 11.00 pm. The primary device collected data at an interval of 30 minutes within the time range, while the supporting devices randomly collected data during the day.

Forecast: Mobile Phone Subscribers in Spain 2024 - 2028 Discover more data with ReportLinker!

Forecast: Total Mobile Phone Subscriptions in Sweden 2022 - 2026 Discover more data with ReportLinker!

The number of mobile phone subscriptions in Italy was forecast to continuously decrease between 2024 and 2028 by in total 3.6. After the sixth consecutive decreasing year, the number is estimated to reach 128.11 subscriptions and therefore a new minimum in 2028. Shown is the number mobile cellular subscriptions. To control for differences in population size and allow for a ranking of countries, this number is expressed as subscriptions per 100 inhabitants. Included are only subscriptions that also allow voice communication over the Public Switched Telephone Network (PSTN). Pure data and M2M (machine-to-machine) connections are excluded.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 more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more information concerning Brazil and Central America.

This dataset provides information about the telecommunication activity over the city of Milano. The dataset is the result of a computation over the Call Detail Records (CDRs) generated by the Telecom Italia cellular network over the city of Milano. CDRs log the user activity for billing purposes and network management.

Number of Mobile Phone Subscribers per 1000 Persons: CF: Kursk Region data was reported at 1,808.900 Unit in 2016. This records an increase from the previous number of 1,777.900 Unit for 2015. Number of Mobile Phone Subscribers per 1000 Persons: CF: Kursk Region data is updated yearly, averaging 1,230.300 Unit from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 1,808.900 Unit in 2016 and a record low of 4.500 Unit in 2000. Number of Mobile Phone Subscribers per 1000 Persons: CF: Kursk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TG009: Number of Mobile Phone Subscribers: per 1000 Persons: by Region.

English(the United States) Spontaneous Dialogue Smartphone speech dataset, collected from dialogues based on given topics, covering generic domain. Transcribed with text content, speaker's ID, gender and other attributes. Our dataset was collected from extensive and diversify speakers(1,416 Americans), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

SKMM Annual Report - Number of Cellular Telephone Subscriptions and Penetration Rate since 2012

Mobile phone log data used to mine contextual behavioral rules of individual mobile phone users

Forecast: Mobile Telephony Subscribers in Germany 2024 - 2028 Discover more data with ReportLinker!

Distribution of Cellular Mobile Subscribers in Pakistan 2014-2015

The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.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 smartphone users in countries like Mexico and Canada.

English(the United Kingdom) Scripted Monologue Smartphone speech dataset, collected from monologue based on given scripts, covering generic domain, human-machine interaction, smart home command and in-car command, numbers and other domains. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers(1,651 British people in total), geographicly speaking, enhancing model performance in real and complex tasks.Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Quadrant provides Insightful, accurate, and reliable mobile location data.

Our privacy-first mobile location data unveils hidden patterns and opportunities, provides actionable insights, and fuels data-driven decision-making at the world's biggest companies.

These companies rely on our privacy-first Mobile Location and Points-of-Interest Data to unveil hidden patterns and opportunities, provide actionable insights, and fuel data-driven decision-making. They build better AI models, uncover business insights, and enable location-based services using our robust and reliable real-world data.

We conduct stringent evaluations on data providers to ensure authenticity and quality. Our proprietary algorithms detect, and cleanse corrupted and duplicated data points – allowing you to leverage our datasets rapidly with minimal processing or cleaning. During the ingestion process, our proprietary Data Filtering Algorithms remove events based on a number of both qualitative factors, as well as latency and other integrity variables to provide more efficient data delivery. The deduplicating algorithm focuses on a combination of four important attributes: Device ID, Latitude, Longitude, and Timestamp. This algorithm scours our data and identifies rows that contain the same combination of these four attributes. Post-identification, it retains a single copy and eliminates duplicate values to ensure our customers only receive complete and unique datasets.

We actively identify overlapping values at the provider level to determine the value each offers. Our data science team has developed a sophisticated overlap analysis model that helps us maintain a high-quality data feed by qualifying providers based on unique data values rather than volumes alone – measures that provide significant benefit to our end-use partners.

Quadrant mobility data contains all standard attributes such as Device ID, Latitude, Longitude, Timestamp, Horizontal Accuracy, and IP Address, and non-standard attributes such as Geohash and H3. In addition, we have historical data available back through 2022.

Through our in-house data science team, we offer sophisticated technical documentation, location data algorithms, and queries that help data buyers get a head start on their analyses. Our goal is to provide you with data that is “fit for purpose”.

Number of Mobile Phone Subscribers per 1000 Persons: CF: Smolensk Region data was reported at 2,095.900 Unit in 2016. This records an increase from the previous number of 2,052.800 Unit for 2015. Number of Mobile Phone Subscribers per 1000 Persons: CF: Smolensk Region data is updated yearly, averaging 1,491.500 Unit from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 2,095.900 Unit in 2016 and a record low of 16.700 Unit in 2000. Number of Mobile Phone Subscribers per 1000 Persons: CF: Smolensk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TG009: Number of Mobile Phone Subscribers: per 1000 Persons: by Region.

Spanish(Spain) Spontaneous Dialogue Smartphone speech dataset, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(596 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.