The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

With the internet becoming increasingly accessible, the number of e-mails sent and received globally has increased each year since 2017. In 2022, there were an estimated 333 billion e-mails sent and received daily around the world. This figure is projected to increase to 392.5 billion daily e-mails by 2026.

E-Mail marketing Despite the increasing popularity of messengers, chat apps and social media, e-mail has managed to remain central to digital communication and continues to grow in uptake. By 2025, the number of global e-mail users is expected to reach a total of 4.6 billion - an approximate six hundred thousand increase in users, up from 4 billion in 2020. Not only that, when it comes to online advertising e-mail has seen higher click-through-rates than on social media. In Belgium and Germany, these were 5.5 and 4.3 percent respectively - compared to the 1.3 percent global average CTR for social media during the same time period.

Gmail Launched in April 2004, Google’s Gmail has earned its spot as one of the most popular freemail services in the world. According to a 2019 survey, its popularity worldwide was trumped only by Apple’s native iPhone Mail app with 26 percent of all e-mail opens worldwide taking place on the platform. Millennials surveyed in the United Kingdom listed Gmail among their top 5 most important mobile apps, while a similar survey carried out in Sweden saw Gmail tie with WhatsApp for a spot among the top mobile apps nationwide.

The population share with mobile internet access in North America was forecast to increase between 2024 and 2029 by in total 2.9 percentage points. This overall increase does not happen continuously, notably not in 2028 and 2029. The mobile internet penetration is estimated to amount to 84.21 percent in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.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 population share with mobile internet access in countries like Caribbean and Europe.

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.

Abstract

The 2017-18 Albania Demographic and Health Survey (2017-18 ADHS) is a nationwide survey with a nationally representative sample of approximately 17,160 households. All women age 15-49 who are usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey. Women 50-59 years old were interviewed with an abbreviated questionnaire that only covered background characteristics and questions related to noncommunicable diseases.

The primary objective of the 2017-2018 ADHS was to provide estimates of basic sociodemographic and health indicators for the country as a whole and the twelve prefectures. Specifically, the survey collected information on basic characteristics of the respondents, fertility, family planning, nutrition, maternal and child health, knowledge of HIV behaviors, health-related lifestyle, and noncommunicable diseases (NCDs). The information collected in the ADHS will assist policymakers and program managers in evaluating and designing programs and in developing strategies for improving the health of the country’s population.

The sample for the 2017-18 ADHS was designed to produce representative results for the country as a whole, for urban and rural areas separately, and for each of the twelve prefectures known as Berat, Diber, Durres, Elbasan, Fier, Gjirokaster, Korce, Kukes, Lezhe, Shkoder, Tirana, and Vlore.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-59 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The ADHS surveys were done on a nationally representative sample that was representative at the prefecture level as well by rural and urban areas. A total of 715 enumeration areas (EAs) were selected as sample clusters, with probability proportional to each prefecture's population size. The sample design called for 24 households to be randomly selected in every sampling cluster, regardless of its size, but some of the EAs contained fewer than 24 households. In these EAs, all households were included in the survey. The EAs are considered the sample's primary sampling unit (PSU). The team of interviewers updated and listed the households in the selected EAs. Upon arriving in the selected clusters, interviewers spent the first day of fieldwork carrying out an exhaustive enumeration of households, recording the name of each head of household and the location of the dwelling. The listing was done with tablet PCs, using a digital listing application. When interviewers completed their respective sections of the EA, they transferred their files into the supervisor's tablet PC, where the information was automatically compiled into a single file in which all households in the EA were entered. The software and field procedures were designed to ensure there were no duplications or omissions during the household listing process. The supervisor used the software in his tablet to randomly select 24 households for the survey from the complete list of households.

All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for individual interviews with the full Woman's Questionnaire. Women age 50-59 were also interviewed, but with an abbreviated questionnaire that left out all questions related to reproductive health and mother and child health. A 50% subsample was selected for the survey of men. Every man age 15-59 who was a usual resident of or had slept in the household the night before the survey was eligible for an individual interview in these households.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the ADHS, one for the household and others for women age 15-49, for women age 50-59, and for men age 15-59. In addition to these four questionnaires, a form was used to record the vaccination information for children born in the 5 years preceding the survey whose mothers had been successfully interviewed.

Cleaning operations

Supervisors sent the accumulated fieldwork data to INSTAT’s central office via internet every day, unless for some reason the teams did not have access to the internet at the time. The data received from the various teams were combined into a single file, which was used to produce quality control tables, known as field check tables. These tables reveal systematic errors in the data such as omission of potential respondents, age displacement, inaccurate recording of date of birth and age at death, inaccurate measurement of height and weight, and other key indicators of data quality. These tables were reviewed and evaluated by ADHS senior staff, which in turn provided feedback and advice to the teams in the field.

Response rate

A total of 16,955 households were selected for the sample, of which 16,634 were occupied. Of the occupied households, 15,823 were successfully interviewed, which represents a response rate of 95%. In the interviewed households, 11,680 women age 15-49 were identified for individual interviews. Interviews were completed for 10,860 of these women, yielding a response rate of 93%. In the same households, 4,289 women age 50-59 were identified, of which 4,140 were successfully interviewed, yielding a 97% response rate. In the 50% subsample of households selected for the male survey, 7,103 eligible men age 15-59 were identified, of which 6,142 were successfully interviewed, yielding a response rate of 87%.

Response rates were higher in rural than in urban areas, which is a pattern commonly found in household surveys because in urban areas more people work and carry out activities outside the home.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017-18 Albania Demographic and Health Survey (ADHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 ADHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017-18 ADHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

See details of the data quality tables in Appendix C of the survey final report.

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.

According to Cognitive Market Research, the global USB Extender market size will be USD 1324.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 8.00% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 529.6 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.2% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 397.2 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 304.5 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.0% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 66.21 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.4% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 26.48 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.7% from 2024 to 2031.
The USB 2.0 Type category is the fastest growing segment of the USB Extender industry

Market Dynamics of USB Extender Market

Key Drivers for USB Extender Market

Increasing Data Transfer Requirement to Boost Market Growth

The demand for high-speed, reliable data transfer has surged across various industries such as IT, gaming, broadcasting, healthcare, and industrial automation. In 2020, users generated 64.2 zettabytes (ZB) of data—surpassing the number of detectable stars in the cosmos. This figure is expected to grow, with data creation projected to reach 147 ZB by the end of 2024. With around 5.35 billion internet users globally, each individual is estimated to generate approximately 15.87 terabytes (TB) of data daily. In 2023, the world produced roughly 120 ZB, translating to about 337,080 petabytes (PB) of data per day. Given the vast number of internet users, this equates to an estimated 15.87 TB of data per person daily. USB extenders are essential for transmitting data over longer distances, exceeding the 5-meter limit of standard USB cables while maintaining signal quality. These devices are particularly important in applications requiring long-range data transmission, such as in security systems and data centers. As data-intensive activities like video editing, 4K content streaming, and high-definition surveillance become more prevalent, the demand for USB extenders continues to grow.

Expansion of Audio-Visual (AV) and Gaming Industries to Drive Market Growth

The expanding AV industry, particularly in broadcasting, video production, and gaming, is a key growth driver for the USB extender market. According to the 2024 "Essential Facts About the U.S. Video Games Industry" report, 190.6 million Americans play video games weekly. Generation Alpha and Generation Z are the largest users, with 54% preferring PC and 58% using consoles for gameplay. Additionally, 78% of U.S. households have engaged with at least one gaming device in the past 12 months, and 63% of players believe video games provide the best value for their money. High-performance USB extenders are critical for live streaming, video conferences, and gaming setups, where devices like cameras, microphones, and controllers need to be positioned at a distance from the main control systems. The growing demand for stable, high-speed connections in these industries is driving the increasing need for USB extenders.

Restraint Factor for the USB Extender Market

Limited Bandwidth and Distance Will Limit Market Growth

Distance and bandwidth limitations pose significant challenges to the growth of the global USB extender market. Restrictions on data transmission due to these factors can hinder uninterrupted data transfer, affecting market expansion. These constraints can impede the efficient transmission of data over long distances, thereby impacting the overall performance and usability of USB extenders across various sectors and applications. For example, as distance increases, so does propagation loss, resulting in diminished signal quality. Similarly, higher bandwidth leads to a higher thermal noise floor, reducing signal clarity over extended distances. Additionally, higher bandwidth increases data bitrate, which is influenced by the power and noise received, further impacti...

Abstract

The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16 and 2018/19. The GHS-Panel households were visited twice: during post-planting period (July - September 2023) and during post-harvest period (January - March 2024).

Geographic coverage

National

Analysis unit

• Households • Individuals • Agricultural plots • Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The original GHS‑Panel sample was fully integrated with the 2010 GHS sample. The GHS sample consisted of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs), chosen from each of the 37 states in Nigeria. This resulted in a total of 2,220 EAs nationally. Each EA contributed 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,200 households, 5,000 households from 500 EAs were selected for the panel component, and 4,916 households completed their interviews in the first wave.

After nearly a decade of visiting the same households, a partial refresh of the GHS‑Panel sample was implemented in Wave 4 and maintained for Wave 5. The refresh was conducted to maintain the integrity and representativeness of the sample. The refresh EAs were selected from the same sampling frame as the original GHS‑Panel sample in 2010. A listing of households was conducted in the 360 EAs, and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximately 3,600 households.

In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS‑Panel households from 2010 were selected to be included in the new sample. This “long panel” sample of 1,590 households was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across Nigeria’s six geopolitical zones.

The combined sample of refresh and long panel EAs in Wave 5 that were eligible for inclusion consisted of 518 EAs based on the EAs selected in Wave 4. The combined sample generally maintains both the national and zonal representativeness of the original GHS‑Panel sample.

Sampling deviation

Although 518 EAs were identified for the post-planting visit, conflict events prevented interviewers from visiting eight EAs in the North West zone of the country. The EAs were located in the states of Zamfara, Katsina, Kebbi and Sokoto. Therefore, the final number of EAs visited both post-planting and post-harvest comprised 157 long panel EAs and 354 refresh EAs. The combined sample is also roughly equally distributed across the six geopolitical zones.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The GHS-Panel Wave 5 consisted of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing, and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

GHS-Panel Household Questionnaire: The Household Questionnaire provided information on demographics; education; health; labour; childcare; early child development; food and non-food expenditure; household nonfarm enterprises; food security and shocks; safety nets; housing conditions; assets; information and communication technology; economic shocks; and other sources of household income. Household location was geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets (forthcoming).

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicited information on land ownership and use; farm labour; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; household fishing activities; and digital farming information. Some information is collected at the crop level to allow for detailed analysis for individual crops.

GHS-Panel Community Questionnaire: The Community Questionnaire solicited information on access to infrastructure and transportation; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; social norms; and local retail price information.

The Household Questionnaire was slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

The Agriculture Questionnaire collected different information during each visit, but for the same plots and crops.

The Community Questionnaire collected prices during both visits, and different community level information during the two visits.

Cleaning operations

CAPI: Wave five exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires (household, agriculture, and community questionnaires) were implemented in both the post-planting and post-harvest visits of Wave 5 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Living Standards Measurement Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given a tablet which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in Wave 5 was highly automated. Each field team was given a mobile modem which allowed for internet connectivity and daily synchronization of their tablets. This ensured that head office in Abuja had access to the data in real-time. Once the interview was completed and uploaded to the server, the data was first reviewed by the Data Editors. The data was also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file was generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files were then communicated back to respective field interviewers for their action. This monitoring activity was done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) outliers. However, special care was taken to avoid making strong assumptions when resolving potential errors. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.

Response

Context

Blockchain technology, first implemented by Satoshi Nakamoto in 2009 as a core component of Bitcoin, is a distributed, public ledger recording transactions. Its usage allows secure peer-to-peer communication by linking blocks containing hash pointers to a previous block, a timestamp, and transaction data. Bitcoin is a decentralized digital currency (cryptocurrency) which leverages the Blockchain to store transactions in a distributed manner in order to mitigate against flaws in the financial industry.

Nearly ten years after its inception, Bitcoin and other cryptocurrencies experienced an explosion in popular awareness. The value of Bitcoin, on the other hand, has experienced more volatility. Meanwhile, as use cases of Bitcoin and Blockchain grow, mature, and expand, hype and controversy have swirled.

Content

In this dataset, you will have access to information about blockchain blocks and transactions. All historical data are in the bigquery-public-data:crypto_bitcoin dataset. It’s updated it every 10 minutes. The data can be joined with historical prices in kernels. See available similar datasets here: https://www.kaggle.com/datasets?search=bitcoin.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.crypto_bitcoin.[TABLENAME]. Fork this kernel to get started.

Method & Acknowledgements

Allen Day (Twitter | Medium), Google Cloud Developer Advocate & Colin Bookman, Google Cloud Customer Engineer retrieve data from the Bitcoin network using a custom client available on GitHub that they built with the bitcoinj Java library. Historical data from the origin block to 2018-01-31 were loaded in bulk to two BigQuery tables, blocks_raw and transactions. These tables contain fresh data, as they are now appended when new blocks are broadcast to the Bitcoin network. For additional information visit the Google Cloud Big Data and Machine Learning Blog post "Bitcoin in BigQuery: Blockchain analytics on public data".

Photo by Andre Francois on Unsplash.

Inspiration

• How many bitcoins are sent each day?
• How many addresses receive bitcoin each day?
• Compare transaction volume to historical prices by joining with other available data sources

How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

Context

Ethereum Classic is an open-source, public, blockchain-based distributed computing platform featuring smart contract (scripting) functionality. It provides a decentralized Turing-complete virtual machine, the Ethereum Virtual Machine (EVM), which can execute scripts using an international network of public nodes. Ethereum Classic and Ethereum have a value token called "ether", which can be transferred between participants, stored in a cryptocurrency wallet and is used to compensate participant nodes for computations performed in the Ethereum Platform.

Ethereum Classic came into existence when some members of the Ethereum community rejected the DAO hard fork on the grounds of "immutability", the principle that the blockchain cannot be changed, and decided to keep using the unforked version of Ethereum. Till this day, Etherum Classic runs the original Ethereum chain.

Content

In this dataset, you will have access to Ethereum Classic (ETC) historical block data along with transactions and traces. You can access the data from BigQuery in your notebook with bigquery-public-data.crypto_ethereum_classic dataset.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.crypto_ethereum_classic.[TABLENAME]. Fork this kernel to get started.

Acknowledgements

This dataset wouldn't be possible without the help of Allen Day, Evgeny Medvedev and Yaz Khoury. This dataset uses Blockchain ETL. Special thanks to ETC community member @donsyang for the banner image.

Inspiration

One of the main questions we wanted to answer was the Gini coefficient of ETC data. We also wanted to analyze the DAO Smart Contract before and after the DAO Hack and the resulting Hardfork. We also wanted to analyze the network during the famous 51% attack and see what sort of patterns we can spot about the attacker.

Abstract

The Integrated Household Survey (IHS) is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO; www.nso.malawi.net) roughly every 5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs) as well as the goals listed as part of the Malawi Growth and Development Strategy (MGDS).

The First Integrated Household Survey (IHS1) was implemented with technical assistance from the International Food Policy Research Institute (IFPRI) and the World Bank (WB). The IHS1 was conducted in Malawi from November 1997 through October 1998 and provided for a broad set of applications on policy issues regarding households’ behavior and welfare, distribution of income, employment, health and education. The Second Integrated Household Survey (IHS2; http://go.worldbank.org/JABABM36V0) was implemented with technical assistance from the World Bank in order to compare the current situation with the situation in 1997-98, and to collect more detailed information in specific areas. The IHS2 fieldwork took placed from March 2004 through February 2005.

The Third Integrated Household Survey (IHS3) expanded on the agricultural content of the IHS2 and was implemented from March 2010 to March 2011 under the umbrella of the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) initiative, whose primary objective is to provide financial and technical support to governments in sub-Saharan Africa in the design and implementation of nationally-representative multi-topic panel household surveys with a strong focus on agriculture.

A sub-sample of IHS3 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection. The LSMS-ISA initiative provided technical and financial assistance to the design and implementation of the IHPS, alongside DFID, Norway and Government of Malawi funding for the exercise. The IHPS main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.

Geographic coverage

National

Analysis unit

• Household
• Individual

Universe

The IHPS attempted to track all baseline households (from the IHS3) as well as individuals that moved away from the baseline dwellings between 2010 and 2013 as long as they were neither servants nor guests at the time of the IHS3; were projected to be at least 12 years of age and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sub-sample of IHS3 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection.. The LSMS-ISA initiative provided technical and financial assistance to the design and implementation of the IHPS, alongside DFID, Norway and Government of Malawi funding for the exercise. The IHPS main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.

At baseline, the IHPS sample was selected to be representative at the national, regional, urban/rural levels and for each of the following 6 strata: (i) Northern Region - Rural, (ii) Northern Region - Urban, (iii) Central Region - Rural, (iv) Central Region - Urban, (v) Southern Region - Rural, and (vi) Southern Region - Urban.

Mode of data collection

Face-to-face [f2f]

Research instrument

The IHPS was comprised of the following questionnaires : 1. Agriculture Questionnaire 2. Community Questionnaire 3. Fishery Questionnaire 4. Household Questionnaire 5. Market Questionnaire

Cleaning operations

The IHPS CSPro based data entry application was designed to stream-line the data collection process from the field. Completed data capture for enumerations areas was packaged automatically by the data entry application into a compressed zip file specific to each enumeration area code. These files contained all household level interviews for that enumeration area and were then submitted back to the NSO central office. These files were to be transmitted back on a rolling basis. For IHPS the field teams were each provided an internet dongle and airtime for timely submission of the data files as limited access to internet cafes and file corruption was a notable issue in the IHS3 project.

Once data files were received by the NSO central office, enumeration area files were downloaded and cataloged by date received. Data was compiled and exported into Stata files on a regular basis and weekly reports were generated with assistance from the IHPS World Bank Resident Advisor on the status of data completion. Over-all data collection status reports were relayed to NSO IHPS Managers on a weekly basis. Overdue or incomplete data files were flagged for immediately follow-up.

The IHPS data files received from the field were also downloaded by the IHPS Data Manager and uploaded to the data verification server to await second data entry. To perform second data entry, individual computers would retrieve and load the field data for the specific enumeration area. Once data verification was complete, verified enumeration data files were zipped and uploaded automatically to the server. Daily back-up of the server to a local network computer was conducted at the end of every day and back-ups to remote location weekly.

Abstract

The Integrated Household Survey (IHS) is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office roughly every 5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs) as well as the goals listed as part of the Malawi Growth and Development Strategy (MGDS).

The First Integrated Household Survey (IHS1) was implemented with technical assistance from the International Food Policy Research Institute (IFPRI) and the World Bank (WB). The IHS1 was conducted in Malawi from November 1997 through October 1998 and provided for a broad set of applications on policy issues regarding households' behaviour and welfare, distribution of income, employment, health and education. The Second Integrated Household Survey was implemented with technical assistance from the World Bank in order to compare the current situation with the situation in 1997-98, and to collect more detailed information in specific areas. The IHS2 fieldwork took placed from March 2004 through February 2005. The Third Integrated Household Survey (IHS3) expanded on the agricultural content of the IHS2 and was implemented from March 2010 to March 2011 under the umbrella of the World Bank Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) initiative, whose primary objective is to provide financial and technical support to governments in sub-Saharan Africa in the design and implementation of nationally-representative multi-topic panel household surveys with a strong focus on agriculture.

A sub-sample of IHS3 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS) (ii) (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection.

Geographic coverage

National

Analysis unit

Households

Universe

The IHPS attempted to track all baseline households (from the IHS3) as well as individuals that moved away from the baseline dwellings between 2010 and 2013 as long as they were neither servants nor guests at the time of the IHS3; were projected to be at least 12 years of age and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sub-sample of IHS3 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection. At baseline, the IHPS sample was selected to be representative at the national, regional, urban/rural levels and for each of the following 6 strata: (i) Northern Region - Rural, (ii) Northern Region - Urban, (iii) Central Region - Rural, (iv) Central Region - Urban, (v) Southern Region - Rural, and (vi) Southern Region - Urban.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The IHPS CSPro based data entry application was designed to stream-line the data collection process from the field. Completed data capture for enumerations areas was packaged automatically by the data entry application into a compressed zip file specific to each enumeration area code. These files contained all household level interviews for that enumeration area and were then submitted back to the NSO central office. These files were to be transmitted back on a rolling basis. For IHPS the field teams were each provided an internet dongle and airtime for timely submission of the data files as limited access to internet cafes and file corruption was a notable issue in the IHS3 project.

Once data files were received by the NSO central office, enumeration area files were downloaded and catalogued by date received. Data was compiled and exported into Stata files on a regular basis and weekly reports were generated with assistance from the IHPS World Bank Resident Advisor on the status of data completion. Over-all data collection status reports were relayed to NSO IHPS Managers on a weekly basis. Overdue or incomplete data files were flagged for immediately follow-up.

The IHPS data files received from the field were also downloaded by the IHPS Data Manager and uploaded to the data verification server to await second data entry. To perform second data entry, individual computers would retrieve and load the field data for the specific enumeration area. Once data verification was complete, verified enumeration data files were zipped and uploaded automatically to the server. Daily back-up of the server to a local network computer was conducted at the end of every day and back-ups to remote location weekly.

The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 billion 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 Australia & Oceania and Asia.

By 2025, forecasts suggest that there will be more than ** billion Internet of Things (IoT) connected devices in use. This would be a nearly threefold increase from the IoT installed base in 2019. What is the Internet of Things? The IoT refers to a network of devices that are connected to the internet and can “communicate” with each other. Such devices include daily tech gadgets such as the smartphones and the wearables, smart home devices such as smart meters, as well as industrial devices like smart machines. These smart connected devices are able to gather, share, and analyze information and create actions accordingly. By 2023, global spending on IoT will reach *** trillion U.S. dollars. How does Internet of Things work? IoT devices make use of sensors and processors to collect and analyze data acquired from their environments. The data collected from the sensors will be shared by being sent to a gateway or to other IoT devices. It will then be either sent to and analyzed in the cloud or analyzed locally. By 2025, the data volume created by IoT connections is projected to reach a massive total of **** zettabytes. Privacy and security concerns   Given the amount of data generated by IoT devices, it is no wonder that data privacy and security are among the major concerns with regard to IoT adoption. Once devices are connected to the Internet, they become vulnerable to possible security breaches in the form of hacking, phishing, etc. Frequent data leaks from social media raise earnest concerns about information security standards in today’s world; were the IoT to become the next new reality, serious efforts to create strict security stands need to be prioritized.

Switzerland is leading the ranking by population share with mobile internet access, recording 95.06 percent. Following closely behind is Ukraine with 95.06 percent, while Moldova is trailing the ranking with 46.83 percent, resulting in a difference of 48.23 percentage points to the ranking leader, Switzerland. The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection. 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).

Despite the growth and prominence of mobile messengers and chat apps, e-mail is an integral part of daily online life. In 2023, the number of global e-mail users amounted to **** billion and is set to grow to **** billion users in 2027. Global e-mail audiencesIn 2023, approximately *** billion e-mails were sent and received every day worldwide. This figure is projected to increase to over *** billion daily e-mails in 2027. As of July 2022, Apple Mail Privacy accounted for over half of the e-mail opens, while mobile use of e-mails saw a significant decrease in their market shares. Apple MPP e-mail app was the most popular e-mail client, accounting for ** percent of e-mail opens. Gmail, the free e-mail service owned by Google, was ranked second with a ** percent open share. Malicious mailMany online users use e-mails for website and newsletter signups and brace themselves for the inevitable flood of spam and marketing communications. Whereas most unwanted e-mails are annoying yet ultimately benign, consumers are right to be wary of malicious e-mail that can be used to compromise their digital accounts and devices. In 2023, ** percent of fraud reports in the United States related to cases in which victims were contacted via e-mail.

During a 2024 survey, 77 percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just 23 percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis.

              Social media: trust and consumption

              Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than 35 percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than 50 percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media.

              What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis.
              Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers.
              Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

Instagram’s most popular post

              As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
              After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.

              Instagram’s most popular accounts

              As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.

              Instagram influencers

              In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.

              Instagram around the globe

              Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.

Facebook received 73,390 user data requests from federal agencies and courts in the United States during the second half of 2023. The social network produced some user data in 88.84 percent of requests from U.S. federal authorities. The United States accounts for the largest share of Facebook user data requests worldwide.