About this dataset

Context

The dataset tabulates the Media population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Media. The dataset can be utilized to understand the population distribution of Media by age. For example, using this dataset, we can identify the largest age group in Media.

Key observations

The largest age group in Media, IL was for the group of age 50 to 54 years years with a population of 21 (21.21%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Media, IL was the 30 to 34 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Media is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Media total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Media Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Media, IL population pyramid, which represents the Media population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Media, IL, is 13.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Media, IL, is 23.6.
• Total dependency ratio for Media, IL is 37.5.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Media, IL is 4.2.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Media population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Media for the selected age group is shown in the following column.
• Population (Female): The female population in the Media for the selected age group is shown in the following column.
• Total Population: The total population of the Media for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Media Population by Age. You can refer the same here

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

Gen Z and Millennials are the biggest social media users of all age groups.

A structured, self-report questionnaire designed by our research team was used to develop a customized dataset. The questionnaire was in the form of an online questionnaire comprising 4 main sections: • Demographics: age, gender, and education. • Technology and social media use: Daily hours of screen time, time spent on social media, main platforms used, and preference for technology usage (work or leisure). • Psychological and Cognitive Indicators: Self-rated concentration during the study (1–5), number of interruptions, change in mood following technology use, and perceived difficulty concentrating while using social media. • Self-Awareness and Coping: Perception of being overused, concerns about the use of technology, use of apps to reduce mental fatigue, and use of strategies to reduce duration. The responses were numerical. Physicians left the respondents with missing or invalid responses, which were removed during the pre-processing stage. A new binary response was defined—Brain Rot (Yes/No). A participant was deemed to have brain rot if they demonstrated 3 or more of the 6 brain rot patterns: • Social media use ≥3 hours per day • Screen time ≥ 4 hours per day • Focus level ≤ 2 out of 5 • Reports frequent distraction • Notices mood shift as technology is used • Thinks social media is bad for mental health This was the target variable and the outcome label for classification. However, the dataset was cleaned and pre-processed as follows pre-analysis: • Elimination of incomplete or contradictory records • Conversion of categorical into the numerical form (namely, yes = 1, no = 0). • Normalization of numerical features, if necessary • Treatment of outliers and testing for normality The ultimate dataset was balanced, well-formatted for statistical and machine learning analyses, and presented with well-defined input features and a binary classification output.

EN:

Preface

I would like to begin this work by offering a few introductory words. This is the first time I am writing this type of work, and I want to emphasize that I am open to any comments and suggestions regarding my work. I know that there is always room for improvement, and I would gladly take advantage of your advice to become better at what I do.

github with Dashboard and python file: https://github.com/Dzynekz/Poland-s-population-by-voivodeship-2002-2021-

Thank you in advance for your time and I wish you a pleasant reading.

Introduction

The aim of the study is to approximate the trends and changes in selected demographic data describing the population of Poland from 2002 to 2021. The collected data allows for analysis, taking into account the administrative division into voivodeships, age groups and gender. The study focuses on answering the following research questions: 1. How has the population of Poland changed? 2. Does the introduction of the "500+" program in 2016 have a positive impact on increasing the number of births? 3. How have economic age groups changed over the years?

Data acquisition

One of the key tools used during the acquisition of reliable data was the API of the Central Statistical Office, which allowed me to access a huge database containing, among other things, information about the population in Poland from 2002 to 2021. Through analysis of the open API documentation of the CSO and the use of provided methods, I selected the most interesting ranges of information about the population, divided by voivodeships, age groups, and gender. I downloaded the complete set of statistical data using self-developed Python code, which, based on defined parameters, automated the necessary API method calls, conversion, and saving of the received data in CSV format. Having the data in the selected format, I was able to easily and efficiently import, process, and analyze the collected information using chosen tools. Without access to the open API of the CSO and the ability to use it, collecting data on population changes over the years would have been much more difficult and time-consuming. Thanks to widely used API interfaces in today's times, we can effectively acquire, gather, and process valuable data that can be used for analysis, forecasting trends, creating long-term strategies, or making daily decisions in many aspects of our daily lives (economy, finance, economics, etc.).

Visualization

Below I present a visualization that illustrates changes in the population of Poland over the years: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F14257214%2Fb7b5b7b2d92cfc75b225df87a9fd004f%2FDashboard.png?generation=1681134675762237&alt=media" alt="">

How has the population changed over the years?

Overall population of the country

Analyzing the data on the population of Poland from 2002 to 2021, we can see that it underwent interesting changes. From 2002 to 2006, the population slightly decreased and amounted to: 38.21 million, 38.18 million, 38.17 million, 38.15 million, and 38.13 million, respectively. Then, from 2007 to 2011, the population strongly increased, reaching a peak of 38.53 million in 2011. In the following years, the population began to slightly decrease until 2019, to the level of 38.38 million. The largest decrease in population was recorded in 2020-2021, reaching a level of 37.9 million people, most likely due to the COVID-19 pandemic. Overall, over the entire period under investigation, the population in Poland decreased by about 1.3%.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F14257214%2F1a9ca78c8df280505efccfddb4d73cb5%2Fobraz_2023-04-10_155200671.png?generation=1681134723226009&alt=media" alt="">

Population by voivodeships

The changes in the population of residents in individual voivodeships are very interesting. The largest increase in population was recorded in the Mazowieckie voivodeship and amounted to 380 thousand. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F14257214%2F6de93256154094f2462b9f3c27bcba06%2Fobraz_2023-04-10_155258708.png?generation=1681134780752830&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F14257214%2Fad4b988567ac7a915f2ed4461c5b9c82%2Fobraz_2023-04-10_155318168.png?generation=1681134799959003&alt=media" alt="">

The largest population growth was recorded in the Mazowieckie, Małopolskie, Wielkopolskie and Pomorskie voivodeships. At the same time, the trend in the Śląskie and Lubelskie voivodeships was the opposite, with the population decreasing.

Furthermore, the data shows that in the remaining voivodeships of Poland, the number of inhabitants decreased. The largest decrease was recorded in the Śląskie voivodeship, which amounted to 350,000, and the...

In order to develop appropriate tools (e.g. a mobile app) we explored through a participant survey the issues such as the kinds of media coverage that engage and inform voters, whether and how this varies by subgroups such as generation, and the aspects of campaigns that contribute to more positive views of the political process. As part of ExpoNet's objectives to understand news and information exposure in the contemporary environment, we worked to to enhancing the quality of representative democracy through giving better access to citizens to quality information and the tools necessary to evaluate the news they consumed. By providing information about the nature and quality of traditional and new media election coverage over time and its impact on individuals, our research will offer pointers towards how to mobilize informed engagement with campaigns and in elections. The advent of Web 2.0 - the second generation of the World Wide Web, that allows users to interact, collaborate, create and share information online, in virtual communities - has radically changed the media environment, the types of content the public is exposed to as well as the exposure process itself. Individuals are faced with a wider range of options (from social and traditional media), new patterns of exposure (socially mediated and selective), and alternate modes of content production (e.g. user-generated content). In order to understand change (and stability) in opinions and behaviour, it is necessary to measure to what information a person has been exposed. The measures social scientists have traditionally used to capture information exposure usually rely on self-reports of newspaper reading and television news broadcast viewing. These measures do not take into account that individuals browse and share diverse information from social and traditional media on a wide range of platforms. According to the OECD's Global Science Forum 2013 report, social scientists' inability to anticipate the Arab Spring was partly due to a failure to understand 'the new ways in which humans communicate' via social media and the ways they are exposed to information. And social media's mixed record for predicting the results of recent UK elections suggests better tools and a unified methodology are needed to analyze and extract political meaning from this new type of data. We argue that a new set of tools, which models exposure as a network and incorporates both social and traditional media sources, is needed in the social sciences to understand media exposure and its effects in the age of digital information. Whether one is consuming the news online or producing/consuming information on social media, the fundamental dynamic of consuming public affairs news involves formation of ties between users and media content by a variety of means (e.g. browsing, social sharing, search). Online media exposure is then a process of network formation that links sources and consumers of content via their interactions, requiring a network perspective for its proper understanding. We propose a set of scalable network-oriented tools to 1) extract, analyse, and measure media content in the age of "big media data", 2) model the linkages between consumers and producers of media content in complex information networks, and 3) understand co-development of network structures with consumer attitudes/behaviours. In order to develop and validate these tools, we bring together an interdisciplinary and international team of researchers at the interface of social science and computer science. Expertise in network analysis, text mining, statistical methods and media analysis will be combined to test innovative methodologies in three case studies including information dynamics in the 2015 British election and opinion formation on climate change. Developing a set of sophisticated network and text analysis tools is not enough, however. We also seek to build national capacity in computational methods for the analysis of online 'big' data. The survey responses were collected from an online panel run by Dynata. There are 1802 respondents across a range of responses to attitudes and practices of using social media. Demographic variables have also been included. Like other companies where online samples can be purchased, Dynata uses invitations of all types including e-mail invitations, phone alerts, banners and messaging on panel community sites to include people with a diversity of motivations to take part in research. Respondents are paid for completing surveys. In terms of quality control, Dynata checks for duplicate participants by evaluating variables such as email address, matches across several demographic data, and device-related data through use of digital fingerprint technology. Participants are then directed to our survey, programmed in Qualtrics, that is hosted on a server at the University of Exeter in order to comply with data protection and privacy guidelines.

Media usage of the population in 1986. The main focus of this survey part is on a detailed recording of the print media, while information on the radio media were recorded more summarily. Topics: frequency of conducting selected leisure activities; use of radio and television; detailed determination of familiarity and frequency of use of newspapers, magazines as well as inserts with radio and television schedules; subscriptions to newspapers and magazines; number of magazines subscribed to; knowledge and use of reading circles; subscription to reading circle; place of reading publications from reading circle; membership in a book club; frequency of going to the movies and time of last trip to the movies; possession of a telephone; number of telephones and main extensions in the household; possession of bicycle; number of cars available to the household; number of cars with car radio; car radios with cassette player and radio traffic service decoder; number of television sets as well as type and features of the equipment; possession or planned acquisition of one or several video recorders; number of video cassettes in the household; place and frequency of renting video cassettes; possession of a video camera; presence of personal computer and video games; type of antenna connection; presence of a cable connection on the street, in the building or residence; number of selected devices of entertainment electronics in the household; possession of durable economic goods; having a yard; pets; public transportation close to home; residential status and number of renters in the building; age of building; length of residence in the building; performing do-it-yourself and repair activities; time of last vacation trip and vacation destination; party preference; shopping habits in purchase of food and beverages; preferred type of business. Demography: age; sex; marital status; year of marriage and number of years of marriage; religious denomination; school education; vocational training; occupational position; employment; monthly net income; monthly net household income; income recipients in household; size of household; respondent is person managing household; respondent is head of household; characteristics of head of household; characteristics of person managing household; detailed demographic information on children in household; possession of drivers license. Interviewer rating: interest in survey topic and willingness of respondent to cooperate; length of interview; weekday of interview. Mediennutzung der Bevölkerung im Jahre 1986. Der Schwerpunkt dieses Erhebungsteils liegt bei einer detaillierten Erfassung der Printmedien, während Angaben zu den Funkmedien eher summarisch erfragt wurden. Themen: Häufigkeit der Ausübung ausgewählter Freizeitaktivitäten; Radio- und Fernsehkonsum; detaillierte Ermittlung des Bekanntheits grades und der Nutzungshäufigkeit von Zeitungen, Zeitschriften sow Beilagen mit Radio- und Fernsehprogramm; Zeitungs- und Zeitschriftenabonnements; Anzahl der abonnierten Zeitschriften; Kenntnis und Nutzung von Lesemappen; Bezug einer Lesemappe; Leseort von Lesemappen; Buchclubmitgliedschaft; Häufigkeit von Kinobesuche und Zeitraum des letzten Kinobesuchs; Telefonbesitz; Anzahl der Telefone und Hauptanschlüsse im Haushalt; Zweiradbesitz; Anzahl der dem Haushalt zur Verfügung stehenden PKW; Anzahl der PKW mit Autoradio; Autoradios mit Kassettenteil und Verkehrsfunkdecoder; Anzahl der Fernsehgeräte sowie Art und Ausstattung der Geräte; Besitz bzw. geplante Anschaffung eines oder mehrerer Videorecorder; Anzahl der Videokassetten im Haushalt; Ort und Häufigkeit des Leihens von Videokassetten; Besitz einer Videokamera; Vorhandensein von Heimcomputer und Telespielen; Art des Antennenanschlusses; Vorhandensein eines Kabelanschlusses in der Straße, im Haus oder der Wohnung; Anzahl ausgewählter Geräte der Unterhaltungselektronik im Haushalt; Besitz langlebiger Wirtschaftssgüter; Gartenbesitz; Haustiere; öffentliche Verkehrsmittel in Wohnungsnähe; Wohnstatus und Anzahl der Mietparteien im Haus; Gebäudealter; Wohndauer im Haus; Verrichtung von Heimwerker- und Reparaturtätigkeiten; Zeitpunkt der letzten Urlaubsreise und Urlaubsziel; Parteipräferenz; Einkaufsgewohnheiten beim Kauf von Lebensmitteln und Getränken; präferierter Geschäftstyp. Demographie: Alter; Geschlecht; Familienstand; Jahr der Eheschließung und Anzahl der Ehejahre; Konfession; Schulbildung; Berufsausbildung; berufliche Position; Berufstätigkeit; monatliches Netto-Einkommen; monatliches Netto-Haushaltseinkommen; Einkommensempfänger im Haushalt; Haushaltsgröße; Befragter ist haushaltsführende Person; Befragter ist Haushaltsvorstand; Charakteristika des Haushaltsvorstands; Charakteristika der haushaltsführenden Person; detaillierte demographische Angaben über Kinder im Haushalt; Führerscheinbesitz. Interviewerrating: Kooperationsbereitschaft und Interesse des Befragten am Befragungsthema; Interviewdauer; Wochentag des Interviews.

Knowing who your consumers are is essential for businesses, marketers, and researchers. This detailed demographic file offers an in-depth look at American consumers, packed with insights about personal details, household information, financial status, and lifestyle choices. Let's take a closer look at the data:

Personal Identifiers and Basic Demographics At the heart of this dataset are the key details that make up a consumer profile:

Unique IDs (PID, HHID) for individuals and households Full names (First, Middle, Last) and suffixes Gender and age Date of birth Complete location details (address, city, state, ZIP) These identifiers are critical for accurate marketing and form the base for deeper analysis.

Geospatial Intelligence This file goes beyond just listing addresses by including rich geospatial data like:

Latitude and longitude Census tract and block details Codes for Metropolitan Statistical Areas (MSA) and Core-Based Statistical Areas (CBSA) County size codes Geocoding accuracy This allows for precise geographic segmentation and localized marketing.

Housing and Property Data The dataset covers a lot of ground when it comes to housing, providing valuable insights for real estate professionals, lenders, and home service providers:

Homeownership status Dwelling type (single-family, multi-family, etc.) Property values (market, assessed, and appraised) Year built and square footage Room count, amenities like fireplaces or pools, and building quality This data is crucial for targeting homeowners with products and services like refinancing or home improvement offers.

Wealth and Financial Data For a deeper dive into consumer wealth, the file includes:

Estimated household income Wealth scores Credit card usage Mortgage info (loan amounts, rates, terms) Home equity estimates and investment property ownership These indicators are invaluable for financial services, luxury brands, and fundraising organizations looking to reach affluent individuals.

Lifestyle and Interests One of the most useful features of the dataset is its extensive lifestyle segmentation:

Hobbies and interests (e.g., gardening, travel, sports) Book preferences, magazine subscriptions Outdoor activities (camping, fishing, hunting) Pet ownership, tech usage, political views, and religious affiliations This data is perfect for crafting personalized marketing campaigns and developing products that align with specific consumer preferences.

Consumer Behavior and Purchase Habits The file also sheds light on how consumers behave and shop:

Online and catalog shopping preferences Gift-giving tendencies, presence of children, vehicle ownership Media consumption (TV, radio, internet) Retailers and e-commerce businesses will find this behavioral data especially useful for tailoring their outreach.

Demographic Clusters and Segmentation Pre-built segments like:

Household, neighborhood, family, and digital clusters Generational and lifestage groups make it easier to quickly target specific demographics, streamlining the process for market analysis and campaign planning.

Ethnicity and Language Preferences In today's multicultural market, knowing your audience's cultural background is key. The file includes:

Ethnicity codes and language preferences Flags for Hispanic/Spanish-speaking households This helps ensure culturally relevant and sensitive communication.

Education and Occupation Data The dataset also tracks education and career info:

Education level and occupation codes Home-based business indicators This data is essential for B2B marketers, recruitment agencies, and education-focused campaigns.

Digital and Social Media Habits With everyone online, digital behavior insights are a must:

Internet, TV, radio, and magazine usage Social media platform engagement (Facebook, Instagram, LinkedIn) Streaming subscriptions (Netflix, Hulu) This data helps marketers, app developers, and social media managers connect with their audience in the digital space.

Political and Charitable Tendencies For political campaigns or non-profits, this dataset offers:

Political affiliations and outlook Charitable donation history Volunteer activities These insights are perfect for cause-related marketing and targeted political outreach.

Neighborhood Characteristics By incorporating census data, the file provides a bigger picture of the consumer's environment:

Population density, racial composition, and age distribution Housing occupancy and ownership rates This offers important context for understanding the demographic landscape.

Predictive Consumer Indexes The dataset includes forward-looking indicators in categories like:

Fashion, automotive, and beauty products Health, home decor, pet products, sports, and travel These predictive insights help businesses anticipate consumer trends and needs.

Contact Information Finally, the file includes ke...

The results might surprise you when looking at internet users that are active on social media in each country.

Mediennutzung der Bevölkerung im Jahre 1986. Der Schwerpunktdieses Erhebungsteils liegt bei einer detaillierten Erfassungder Funkmedien, während Angaben zu den Printmedien ehersummarisch erfragt wurden. Themen: Häufigkeit der Ausübung ausgewählter Freizeitaktivitäten;detaillierte Ermittlung des Radio- und Fernsehkonsums bezüglichZeitpunkt, Wochentag und Sendeanstalt; Zeitbudget; Ermittlungdes Bekanntheitsgrades und der Nutzungshäufigkeit von Zeitungen;Zeitungs- und Zeitschriftenabonnements; Anzahl der abonniertenZeitschriften; Kenntnis und Nutzung von Lesemappen; Bezug einerLesemappe; Leseort von Lesemappen; Buchclubmitgliedschaft;Häufigkeit von Kinobesuchen und Zeitraum des letzten Kinobesuchs;Telefonbesitz; Anzahl der Telefone und Hauptanschlüsse im HaushaltZweiradbesitz; Anzahl der dem Haushalt zur Verfügung stehenden PKWAnzahl der PKW mit Autoradio; Autoradios mit Kassettenteilund Verkehrsfunkdecoder; Anzahl der Fernsehgeräte sowie Art undAusstattung der Geräte; Besitz bzw. geplante Anschaffung einesoder mehrerer Videorecorder; Anzahl der Videokassetten im HaushaltOrt und Häufigkeit des Leihens von Videokassetten; Besitz einerVideokamera; Vorhandensein von Heimcomputer und Telespielen;Art des Antennenanschlusses; Vorhandensein eines Kabelanschlussesin der Straße, im Haus oder der Wohnung; empfangbareFernsehprogramme und Empfangsqualität; Anzahl ausgewählter Geräte derUnterhaltungselektronik im Haushalt; Besitz langlebigerWirtschaftsgüter; Gartenbesitz; Haustiere; öffentliche Verkehrsmitin Wohnungsnähe; Wohnstatus und Anzahl der Mietparteien im Haus;Gebäudealter; Wohndauer im Haus; Verrichtung von Heimwerker- undReparaturtätigkeiten; Zeitpunkt der letzten Urlaubsreise undUrlaubsziel; Parteipräferenz; Einkaufsgewohnheiten beim Kaufvon Lebensmitteln und Getränken; präferierter Geschäftstyp. Demographie: Alter; Geschlecht; Familienstand; Jahr der Eheschließungund Anzahl der Ehejahre; Konfession; Schulbildung; Berufsausbildung;berufliche Position; Berufstätigkeit; monatliches Netto-Einkommen;monatliches Netto-Haushaltseinkommen; Einkommensempfänger im Haushalt;Haushaltsgröße; Befragter ist haushaltsführende Person; Befragter istHaushaltsvorstand; Charakteristika des Haushaltsvorstands;Charakteristika der haushaltsführenden Person; detailliertedemographische Angaben über Kinder im Haushalt; Führerscheinbesitz. Interviewerrating: Kooperationsbereitschaft und Interesse desBefragten am Befragungsthema; Interviewdauer; Wochentag desInterviews. Media usage of the population in 1986. The main focus of this survey part is on a detailed recording of radiomedia, while information on the print media was surveyed more insummary. Topics: frequency of conducting selected leisure activities; detaileddetermination of use of radio and television regarding point in time,weekday and broadcaster; time budget; determination of the degree offamiliarity and frequency of use of newspapers; subscribing tonewspapers and magazines; number of magazines subscribed to; knowledgeand use of reading circles; belonging to a reading circle; place ofreading publications from reading circle; membership in a book club;frequency of going to the movies and time of last trip to the movies;possession of a telephone; number of telephones and main extensions inthe household; possession of bicycle; number of cars available to thehousehold; number of cars with car radio; car radios with cassetteplayer and radio traffic service decoder; number of television sets aswell as type and features of the equipment; possession or plannedacquisition of one or several video recorders; number of videocassettes in the household; place and frequency of renting videocassettes; possession of a video camera; presence of personal computerand video games; type of antenna connection; presence of a cableconnection in the street, in the building or apartment; televisionstations that can be received and quality of reception; number ofselected devices of entertainment electronics in the household;possession of durable economic goods; having a yard; pets; publictransportation close to home; residential status and number of rentersin the building; age of building; length of residence in building;performing do-it-yourself and repair activities; time of last vacationtrip and vacation destination; party preference; shopping habits inpurchase of food and beverages; preferred type of business. Demography: age; sex; marital status; year of marriage and number ofyears of marriage; religious denomination; school education; vocationaltraining; occupational position; employment; monthly net income;monthly net household income; income recipients in household; size ofhousehold; respondent is person managing household; respondent is headof household; characteristics of head of household; characteristics ofperson managing household; detailed demographic information on childrenin household; possession of drivers license. Interviewer rating: interest in survey topic and willingness ofrespondent to cooperate; length of interview; weekday of interview.

How much time do people spend on social media? As of 2025, the average daily social media usage of internet users worldwide amounted to 141 minutes per day, down from 143 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 3 hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just 2 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.

IntroductionDespite the Sustainable Development Goal to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030, abortion remains one of the top five causes of maternal mortality in low and middle-income countries. However, there is a lack of comprehensive data on the pooled prevalence and determinants of abortion in sub-Saharan Africa (SSA). Therefore, this study aims to investigate the pooled prevalence and determinants of abortion among women of reproductive age in 24 SSA countries using the most recent Demographic and Health Surveys.MethodsThe most recent Demographic and Health Survey (DHS) data from 24 Sub-Saharan African (SSA) countries were analyzed, using a weighted sample of 392,332 women of reproductive age. To address the clustering effects inherent in DHS data and the binary nature of the outcome variable, a multilevel binary logistic regression model was employed. The results were reported as adjusted odds ratios with 95% confidence intervals to indicate statistical significance. Additionally, the model with the lowest deviance was identified as the best fit for the data.ResultsThe pooled prevalence of abortion in SSA were 6.93% (95%CI: 5.38, 8.48). Older age (AOR = 3.71; 95%CI: 3.46, 3.98), ever married (AOR = 3.87; 95%CI: 3.66, 4.10), being educated (AOR = 1.35; 95%CI: 1.28, 1.44), having formal employment (AOR = 1.19; 95%CI: 1.16, 1.23), traditional contraceptive use (AOR = 1.27; 95%CI: 1.19, 1.36) and media exposure (AOR = 1.37; 95%CI: 1.32, 1.41) found to be a predisposing factors for abortion. While high parity (AOR = 0.72; 95%CI: 0.68, 0.76), rural residence (AOR = 0.87; 95%CI: 0.85, 0.91), and rich (AOR = 0.96; 95%CI: 0.93, 0.99) wealth index were a protective factors.ConclusionThe study found that the pooled prevalence of abortion in Sub-Saharan Africa is 7%. Potential interventions include comprehensive sexual education to inform and empower women, increased access to modern contraceptives to reduce unintended pregnancies, improved healthcare services especially in rural areas, economic empowerment through education and employment opportunities, media campaigns to disseminate information and reduce stigma, and policy development to ensure safe and legal access to abortion services. These interventions aim to improve reproductive health outcomes and reduce unsafe abortions in SSA.

As of April 2024, it was found that men between the ages of 25 and 34 years made up Facebook largest audience, accounting for 18.4 percent of global users. Additionally, Facebook's second largest audience base could be found with men aged 18 to 24 years.

              Facebook connects the world

              Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger,
              as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.

              The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.

              How popular is Instagram?

              Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.

              Who uses Instagram?

              Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.

              Celebrity influencers on Instagram
              Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.

The provided dataset consists of 454 cases collected for the research of participation in non-probability online research panels. The dataset includes the following variables:

Demographics variables

The following demographic variables are included: participants' age, gender, level of education, and working status.

Trust Scale

The six-item General Trust Scale (Yamagishi, T., & Yamagishi, M., 1994) is used to examine the general level of trust of the respondents.

Big Five Scale

BFI-S (15 items) measuring the Big Five personality characteristics of the participants

Online panel participation

Online panel participation is measured with one categorical variable.

Social media use

Social media use is measured with one categorical variable exploring the duration of daily time spent on social media.