The number of Twitter users in the United States was forecast to continuously increase between 2024 and 2028 by in total 4.3 million users (+5.32 percent). After the ninth consecutive increasing year, the Twitter user base is estimated to reach 85.08 million users and therefore a new peak in 2028. Notably, the number of Twitter users of was continuously increasing over the past years.User figures, shown here regarding the platform twitter, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period.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 Twitter users in countries like Canada and Mexico.

The number of Reddit users in the United States was forecast to continuously increase between 2024 and 2028 by in total 10.3 million users (+5.21 percent). After the ninth consecutive increasing year, the Reddit user base is estimated to reach 208.12 million users and therefore a new peak in 2028. Notably, the number of Reddit users of was continuously increasing over the past years.User figures, shown here with regards to the platform reddit, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once. Reddit users encompass both users that are logged in and those that are not.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 Reddit users in countries like Mexico and Canada.

The number of social media users in the United States was forecast to continuously increase between 2024 and 2029 by in total 26 million users (+8.55 percent). After the ninth consecutive increasing year, the social media user base is estimated to reach 330.07 million users and therefore a new peak in 2029. Notably, the number of social media users of was continuously increasing over the past years.The shown figures regarding social media users 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).

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.

The report provides a snapshot of the social media usage trends amongst online Canadian adults based on an online survey of 1500 participants. Canada continues to be one of the most connected countries in the world. An overwhelming majority of online Canadian adults (94%) have an account on at least one social media platform. However, the 2022 survey results show that the COVID-19 pandemic has ushered in some changes in how and where Canadians are spending their time on social media. Dominant platforms such as Facebook, messaging apps and YouTube are still on top but are losing ground to newer platforms such as TikTok and more niche platforms such as Reddit and Twitch.

This dataset covers the use of social media to influence politics by promoting propaganda, advocating controversial viewpoints, and spreading disinformation. Influence efforts are defined as: (i) coordinated campaigns by a state, or the ruling party in an autocracy, to impact one or more specific aspects of politics at home or in another state, (ii) through media channels, including social media, by (iii) producing content designed to appear indigenous to the target state. Our data draw on more than 1000 media reports and 500 research articles/reports to identify IEs, track their progress, and classify their features. The data cover 78 foreign influence efforts (FIEs) and 25 domestic influence efforts (DIEs)—in which governments targeted their own citizens—against 51 different countries from 2011 through early-2021. The Influence Effort dataset measures covert information campaigns by state actors, facilitating research on contemporary statecraft.

The data presented in this data project were collected in the context of two H2020 research projects: ‘Enhanced migration measures from a multidimensional perspective’(HumMingBird) and ‘Crises as opportunities: Towards a level telling field on migration and a new narrative of successful integration’(OPPORTUNITIES). The current survey was fielded to investigate the dynamic interplay between media representations of different migrant groups and the governmental and societal (re)actions to immigration. With these data, we provide more insight into these societal reactions by investigating attitudes rooted in values and worldviews. Through an online survey, we collected quantitative data on attitudes towards:

1. Immigrants, Refugees, Muslims, Hispanics, Venezuelans
2. News Media Consumption
3. Trust in News Media and Societal Institutions
4. Frequency and Valence of Intergroup Contact
5. Realistic and Symbolic Intergroup Threat
6. Right-wing Authoritarianism
7. Social Dominance Orientation
8. Political Efficacy
9. Personality Characteristics
10. Perceived COVID-threat, and
11. Socio-demographic Characteristics

1. Austria
2. Belgium
3. Germany
4. Hungary
5. Italy
6. Spain
7. Sweden

1. United States of America
2. Colombia

The survey in the United States and Colombia was identical to the one in the European countries, although a few extra questions regarding COVID-19 and some region-specific migrant groups (e.g. Venezuelans) were added. We collected the data in cooperation with Bilendi, a Belgian polling agency, and selected the methodology for its cost-effectiveness in cross-country research. Respondents received an e-mail asking them to participate in a survey without specifying the subject matter, which was essential to avoid priming. Three weeks of fieldwork in May and June of 2021 resulted in a dataset of 13,645 respondents (a little over 1500 per country). Sample weights are included in the dataset and can be applied to ensure that the sample is representative for gender and age in each country. The cooperation rate ranged between 12% and 31%, in line with similar online data collections.

Facebook is fast approaching 3 billion monthly active users. That’s about 36% of the world’s entire population that log in and use Facebook at least once a month.

Spatially or temporally dense polling remains both difficult and expensive using existing survey methods. In response, there have been increasing efforts to approximate various survey measures using social media, but most of these approaches remain methodologically flawed. To remedy these flaws, this paper combines 1200 state-level polls during the 2012 presidential campaign with over 100 million state-located political Tweets; models the polls as a function of the Twitter text using a new linear regularization feature-selection method; and shows via out-of-sample testing that when properly modeled, the Twitter-based measures track and to some degree predict opinion polls, and can be extended to unpolled states and potentially sub-state regions and sub-day timescales. An examination of the most predictive textual features reveals the topics and events associated with opinion shifts, sheds light on more general theories of partisan difference in attention and information processing, and may be of use for real-time campaign strategy.

The average Twitter user spends 5.1 hours per month on the platform.

More than 100 social media channels and statistics for the National Archives and Records Administration.

In May 2020, the murder of George Floyd led to protests throughout the United States and around the world. Along with these protests, social media platforms saw a dramatic increase in the volume of discussion regarding Black Lives Matter (BLM). Two years on, online discussion of BLM continues to be lively, not just in the United States but also internationally. This dataset represents one of the most extensive collections of Black Lives Matter tweets available, covering from 2010 through May 2022 and including nearly 50 million tweets overall. Parallel corpora for All Lives Matter and Blue Lives matter are also included. Monthly updates for 2022 are available on Github (https://github.com/amaurits/BLMtwitter), along with a datasheet and a preprint describing the dataset in more detail.

This survey charted the gambling, social media usage and subjective well-being of young people aged 15-30 years in Finland. The study was conducted as part of the "Problem Gambling and Social Media: Social Psychological Study on Youth Behavior in Online Gaming Communities" research project. The aim of the project was to analyse how young social media users assess, adopt and share gambling-related online content and how online group processes affect their gambling and gambling-related attitudes. This dataset contains additional data collected from popular Finnish social media sites. FSD's holdings also include two other datasets that were collected using a nearly identical questionnaire (FSD3399 and FSD3591). Data for the research project have been collected in Finland, the United States, Spain, and South Korea. First, the respondents were asked which social media services they used (e.g. Facebook, YouTube, Instagram, discussion forums, online casinos) and how often. Topics that the respondents discussed on gambling-related social media were charted more closely, and they were asked, for example, whether the discussion usually related to instructions or tips on gambling or to problem gambling and recovering from problem gambling. Some questions on the respondents' social media activity were also presented, for instance, how often they saw gambling-related advertising online, how often they changed their most important social media passwords, and how often they uploaded pictures of themselves on social media. The respondents were asked whether they had ever been harassed online or had been the victim of a crime on the Internet in the past three years (e.g. defamation, identity theft, fraud, sexual harassment). The respondents' identity bubbles on social media were surveyed by using the IBR scale (Identity Bubble Reinforcement Scale). The respondents were asked, for instance, whether they thought they could be themselves on social media and whether they only interacted with people similar to them on social media. Additionally, the CIUS scale (Compulsive Internet Use) was used to examine problems related to Internet use. Questions focused on, for example, whether the respondents found it difficult to stop using the Internet when they were online, whether people close to them said they should use the Internet less, and whether they felt restless, frustrated or irritated when they couldn't use the Internet. In the next section of the questionnaire, the respondents were randomly assigned to two groups for a vignette experiment. Respondents in the test group were told they belong to Group C because they had answered the earlier questions in a similar manner to others in the group. Those in the control group were given no information on the group. The respondents were presented with different gambling-related social media scenarios, and they were asked to evaluate the contents of the gambling-related messages by "liking" or "disliking" the message or by not reacting to it at all. Each respondent was shown four different gambling messages with different contents. Three factors were manipulated in the scenarios (2x2x2 design): expressed stance of the message on gambling (positive or negative), narrative perspective of the message (experience-driven first-person narration or fact-driven third-person narration) and majority opinion of other respondents on the message (positively or negatively biased distribution of likes or dislikes). For Group C, the majority opinion was seemingly provided by other Group C members, whereas for the control group the majority opinion was seemingly provided by other respondents. Additionally, the respondents' attitudes towards the message were surveyed with statements regarding, for instance, how likely they would find the message interesting or share it on social media. Next, the respondents' attitudes towards gambling were charted by using the ATGS scale (Attitudes Towards Gambling Scale). They were asked, for example, whether people should have the right to gamble whenever they want, whether most people who gamble do so sensibly and whether it would be better if gambling was banned altogether. The respondents' gambling habits were examined by using the SOGS scale (South Oaks Gambling Screen), and they were asked, for instance, which types of gambling they had done in the past 12 months (played slot machines, visited an online casino, bet on lotteries etc.), whether the people close to them had gambling problems, and whether they had borrowed money to gamble or to pay gambling debts. In addition, the respondents' alcohol consumption was surveyed with a few questions from the AUDITC scale (The Alcohol Use Disorders Identification Test), and they were asked whether they had used various drugs for recreational purposes (e.g. cannabis, LSD, amphetamine, opioids). The respondents' subjective well-being and social relationships were examined next. The respondents were asked how happy they...

According to a March 2024 survey conducted in the United States, 32 percent of adults reported feeling that social media had neither a positive nor negative effect on their own mental health. Only seven percent of social media users said that online platforms had a very positive effect on their mental health, while 12 percent of users said it had a very negative impact. Furthermore, 22 percent of respondents said social media had a somewhat negative effect on their mental health. Is social media addictive? A 2023 survey of individuals between 11 and 59 years old in the United States found that over 73 percent of TikTok users agreed that the platform was addictive. Furthermore, nearly 27 percent of those surveyed reported experiencing negative psychological effects related to TikTok use. Users belonging to Generation Z were the most likely to say that TikTok is addictive, yet millennials felt the negative effects of using the app more so than Gen Z. In the U.S., it is also not uncommon for social media users to take breaks from using online platforms, and as of March 2024, over a third of adults in the country had done so. Following mental health-related content Although online users may be aware of the negative and addictive aspects of social media, it is also a useful tool for finding supportive content. In a global survey conducted in 2023, 32 percent of social media users followed therapists and mental health professionals on social media. Overall, 24 percent of respondents said that they followed people on social media if they had the same condition as they did. Between January 2020 and March 2023, British actress and model Cara Delevingne was the celebrity mental health activist with the highest growth in searches tying her name to the topic.

This dataset comprises a set of Twitter accounts in Singapore that are used for social bot profiling research conducted by the Living Analytics Research Centre (LARC) at Singapore Management University (SMU). Here a bot is defined as a Twitter account that generates contents and/or interacts with other users automatically (at least according to human judgment). In this research, Twitter bots have been categorized into three major types:

Broadcast bot. This bot aims at disseminating information to general audience by providing, e.g., benign links to news, blogs or sites. Such bot is often managed by an organization or a group of people (e.g., bloggers). Consumption bot. The main purpose of this bot is to aggregate contents from various sources and/or provide update services (e.g., horoscope reading, weather update) for personal consumption or use. Spam bot. This type of bots posts malicious contents (e.g., to trick people by hijacking certain account or redirecting them to malicious sites), or promotes harmless but invalid/irrelevant contents aggressively.

This categorization is general enough to cater for new, emerging types of bot (e.g., chatbots can be viewed as a special type of broadcast bots). The dataset was collected from 1 January to 30 April 2014 via the Twitter REST and streaming APIs. Starting from popular seed users (i.e., users having many followers), their follow, retweet, and user mention links were crawled. The data collection proceeds by adding those followers/followees, retweet sources, and mentioned users who state Singapore in their profile location. Using this procedure, a total of 159,724 accounts have been collected. To identify bots, the first step is to check active accounts who tweeted at least 15 times within the month of April 2014. These accounts were then manually checked and labelled, of which 589 bots were found. As many more human users are expected in the Twitter population, the remaining accounts were randomly sampled and manually checked. With this, 1,024 human accounts were identified. In total, this results in 1,613 labelled accounts. Related Publication: R. J. Oentaryo, A. Murdopo, P. K. Prasetyo, and E.-P. Lim. (2016). On profiling bots in social media. Proceedings of the International Conference on Social Informatics (SocInfo’16), 92-109. Bellevue, WA. https://doi.org/10.1007/978-3-319-47880-7_6

Aineistossa on selvitetty 15-25-vuotiaiden rahapelaamista, sosiaalisen median käyttöä ja yleistä subjektiivista hyvinvointia. Aineisto kerättiin osana Atte Oksasen johtamaa tutkimushanketta Rahapeliongelmat ja verkkoyhteisöt: Sosiaalipsykologinen tutkimus nuorten toiminnasta sosiaalisen median peliyhteisöissä. Hankkeessa tutkitaan, kuinka nuoret käyttäjät arvioivat, omaksuvat ja jakavat sosiaalisessa mediassa rahapelaamiseen liittyviä verkkosisältöjä ja kuinka ryhmäprosessit vaikuttavat heidän rahapelaamiseensa ja sitä koskeviin asenteisiin. Tietoarkistoon on tallennettu myös hankkeessa lähes vastaavalla kyselylomakkeella kerätyt aineistot (FSD3400 ja FSD3591). Hankkeen aineistoja on kerätty Suomen ja Yhdysvaltojen lisäksi myös Espanjassa ja Etelä-Koreassa. Vastaajilta kysyttiin, mitä sosiaalisen median palveluita he käyttävät, sekä heidän yleisiä sosiaalisen median käyttötottumuksiaan. Heiltä kysyttiin myös riskikokemuksista netissä, kuten nettihäirinnän ja nettirikoksen uhriksi joutumisesta. Kyselyn seuraavassa osiossa vastaajat jaettiin satunnaisesti kahteen ryhmään vignette-koeasetelmaa varten. Toiselle ryhmälle kerrottiin, että heidät oli sijoitettu ryhmään C, koska heidän vastauksensa olivat lähellä ryhmän muiden jäsenten vastauksia. Kontrolliryhmälle ei annettu ryhmätietoa. Vastaajille näytettiin erilaisia kuvitteellisia sosiaalisen median rahapeliaiheisia skenaarioita, ja heitä pyydettiin arvioimaan rahapeliaiheisten viestien sisältöä. Vastaajia pyydettiin reagoimaan viestiin joko "tykkäämällä", "ei-tykkäämällä" tai olemalla reagoimatta lainkaan. Jokaiselle vastaajalle näytettiin neljä erilaista skenaariota, joiden sisältö vaihteli. Skenaarioissa varioitiin kolmea asiaa (2x2x2): viestin suhtautuminen rahapelaamiseen (myönteinen tai kielteinen), viestin narratiivinen sävy (kokemuspohjainen tai tutkimustietoon perustuva fakta), sekä muiden vastaajien aiemmat reaktiot kyseiseen viestiin (pääosin myönteinen tai kielteinen suhtautuminen). Toiselle ryhmälle (ryhmä C) muiden reaktiot esitettiin samaan ryhmään kuuluvien vastaajien reaktioina, kontrolliryhmälle muiden kyselyyn vastaajien reaktioina. Lisäksi vastaajia pyydettiin arvioimaan suhtautumistaan viestin sisältöön kysymällä esimerkiksi, kuinka todennäköisesti hän pitäisi kyseistä viestiä kiinnostavana tai hakeutuisi vastaavan sisällön pariin tulevaisuudessa. Vastaajilta kysyttiin heidän rahapelaamisensa laajuudesta, rahapelaamiseen liittyvistä mahdollisista ongelmista sekä rahapelaamiseen liittyvistä asenteista. Päihde- ja addiktio-ongelmat kartoitettiin kysymällä vastaajilta heidän huumeiden käytöstään sekä alkoholin ja Internetin ongelmakäytöstä. Kysymykset käsittelivät myös vastaajien subjektiivista hyvinvointia ja sosiaalisia suhteita. Vastaajilta kysyttiin muun muassa psyykkisestä kuormittuneisuudesta, koetusta itsetunnosta sekä onnellisuuden tasosta. Lisäksi kartoitettiin vastaajien sosiaaliset vuorovaikutussuhteet ja läheisiltä saatu sosiaalinen tuki. Kysymykset koskivat yleisesti sosiaalisia suhteita, ystävyyssuhteita, kiinnittymistä erilaisiin yhteisöihin sekä koettua yksinäisyyden tunnetta. Lopuksi kysyttiin vastaajien kokemasta elämänhallinnan tunteesta sekä kartoitettiin impulsiivisuutta ja lyhytjänteisyyttä muun muassa palkintoviiveeseen liittyvillä kysymyksillä. Aineistossa on käytetty seuraavia mittareita ja muuttujien nimissä niiden lyhenteitä: IBR = samanmielisyys ja identiteettikuplat sosiaalisessa mediassa (Identity Bubble Reinforcement Scale), ATGS = Rahapeliasenteet (Attitudes Toward Gambling Scale), SOGS = Rahapeliongelmat (South Oaks Gambling Screen), CIUS = Internetin ongelmakäyttö (Compulsive Internet Use), AUDITC = Alkoholin ongelmakäyttö (The Alcohol Use Disorders Identification Test), SISE = Itsetunto (Single-item Self-esteem Scale), LONE = Yksinäisyyden tunne (Three-item Loneliness Scale), GHQ = Psyykkinen kuormittuneisuus (General Health Questionnaire), MASTERY = Hallinnan tunne (Sense of Mastery Scale), EIS = Impulsiivisuus (Eysenck Impulsivity Scale) ja GRATIF = Palkintoviive (Delay of Gratification). Taustamuuttujia aineistossa ovat sukupuoli, ikä, synnyinmaa (oma ja vanhempien), koulutus, asuinalueen tyyppi, asumismuoto, tulotaso, taloudelliset ongelmat ja päätoimi. This survey charted the gambling, social media usage and subjective well-being of young people aged 15-25 years in Finland. The study was conducted as part of the "Problem Gambling and Social Media: Social Psychological Study on Youth Behavior in Online Gaming Communities" research project. The aim of the project was to analyse how young social media users evaluate, adopt and share gambling-related online content and how online group processes affect their gambling and gambling-related attitudes. FSD's holdings also include two other datasets that were collected using a nearly identical questionnaire (FSD3400 and FSD3591). Data for the research project have been collected in Finland, the United States, Spain, and South Korea. First, the respondents were asked which social media services they used (e.g. Facebook, YouTube, Instagram, discussion forums, online casinos) and how often. Topics that the respondents discussed on gambling-related social media were charted more closely, and they were asked, for example, whether the discussion usually related to instructions or tips on gambling or to problem gambling and recovering from problem gambling. Some questions on the respondents' social media activity were also presented, for instance, how often they saw gambling-related advertising online, how often they changed their most important social media passwords, and how often they uploaded pictures of themselves on social media. The respondents were asked whether they had ever been harassed online or had been the victim of a crime on the Internet in the past three years (e.g. defamation, identity theft, fraud, sexual harassment). The respondents' identity bubbles on social media were surveyed by using the IBR scale (Identity Bubble Reinforcement Scale). The respondents were asked, for instance, whether they thought they could be themselves on social media and whether they only interacted with people similar to them on social media. Additionally, the CIUS scale (Compulsive Internet Use) was used to examine problems related to Internet use. Questions focused on, for example, whether the respondents found it difficult to stop using the Internet when they were online, whether people close to them said they should use the Internet less, and whether they felt restless, frustrated or irritated when they couldn't use the Internet. In the next section of the questionnaire, the respondents were randomly assigned to two groups for a vignette experiment. Respondents in the test group were told they belong to Group C because they had answered the earlier questions in a similar manner to others in the group. Those in the control group were given no information on the group. The respondents were presented with different gambling-related social media scenarios, and they were asked to evaluate the contents of the gambling-related messages by "liking" or "disliking" the message or by not reacting to it at all. Each respondent was shown four different gambling messages with different contents. Three factors were manipulated in the scenarios (2x2x2 design): expressed stance of the message on gambling (positive or negative), narrative perspective of the message (experience-driven first-person narration or fact-driven third-person narration) and majority opinion of other respondents on the message (positively or negatively biased distribution of likes or dislikes). For Group C, the majority opinion was seemingly provided by other Group C members, whereas for the control group the majority opinion was seemingly provided by other respondents. Additionally, the respondents' attitudes towards the message were surveyed with statements regarding, for instance, how likely they would find the message interesting or share it on social media. Next, the respondents' attitudes towards gambling were charted by using the ATGS scale (Attitudes Towards Gambling Scale). They were asked, for example, whether people should have the right to gamble whenever they want, whether most people who gamble do so sensibly and whether it would be better if gambling was banned altogether. The respondents' gambling habits were examined by using the SOGS scale (South Oaks Gambling Screen), and they were asked, for instance, which types of gambling they had done in the past 12 months (played slot machines, visited an online casino, bet on lotteries etc.), whether the people close to them had gambling problems, and whether they had borrowed money to gamble or to pay gambling debts. In addition, the respondents' alcohol consumption was surveyed with a few questions from the AUDITC scale (The Alcohol Use Disorders Identification Test), and they were asked whether they had used various drugs for recreational purposes (e.g. cannabis, LSD, amphetamine, opioids). The respondents' subjective well-being and social relationships were examined next. The respondents were asked how happy they were in general and how satisfied they were with their financial circumstances and life in general. They were also asked how well the single statement "I have high self-esteem" from the SISE scale (Single-item Self-esteem Scale) described them. The three statements on lacking companionship, feeling left out and feeling isolated from the LONE scale (Three-item Loneliness Scale) were also included in the survey. Feelings of belonging to different groups or communities (e.g. family, friends, neighbourhood, parish/religious community) were charted, and the 12-item GHQ scale (General Health Questionnaire) was used to survey the respondents' recent mental health. Questions included, for example, whether the

This is one of over 400 major media market consumer surveys which have been gifted to Washington State University (WSU) by Leigh Stowell & Company, Inc. of Seattle, Washington, USA. This is a market research firm which specializes in providing newspapers, television affiliates and cable operators with market segmentation research pertinent to consumer purchasing patterns and the effective marketing of goods and services to program audiences. The data in the Stowell Archive were collected via random digit dialing and computer-aided telephone interviews (CATI). Most of the surveys focus on the marketing needs of mass media clients and contain demographics, psychographics, media exposure information, and purchasing behavior data about consumers in major metropolitan areas of the United States and Canada starting in 1989. The sample sizes of the surveys range from 500 to 3,000 respondents, averaging 1,000 observations per study. Data are available at the respondent level, and all observations are keyed to zip code or other geographic identifiers. Additional surveys are anticipated, with over twenty new media marke t studies being donated annually. The University's relationship with Leigh Stowell & Company, Inc. was cultivated by Dr. Nicholas Lovrich, Director of WSU's Division of Governmental Studies and Services (DGSS) and by Dr. John Pierce, former Dean of the WSU College of Liberal Arts over the course of a decade. DGSS collaborated with WSU Libraries Digital Services to process the gifted data files into this digital archive which features powerful search and download capabilities. Further refinement of the archive in accordance with the Data Documentation Initiative is progressing with support from the Office of the Provost, the College of Liberal Arts and the WSU Libraries. It is important to note that the year indicated by the study's title is the year that the original survey was published, and is not necessarily the year in which the interviews were conducted. Refer to the metadata field "Dates of Collection" to di scern the interview dates of each specific survey. Refer also to date fields within the data file itself.

Varieties of Democracy (V-Dem) is a new approach to conceptualizing and measuring democracy. We provide a multidimensional and disaggregated dataset that reflects the complexity of the concept of democracy as a system of rule that goes beyond the simple presence of elections. The V-Dem project distinguishes between five high-level principles of democracy: electoral, liberal, participatory, deliberative, and egalitarian, and collects data to measure these principles. V-Dem draws on theoretical and methodological expertise from its worldwide team to produce data in the most objective and reliable way possible. Approximately half of the indicators in the V-Dem dataset are based on factual information obtainable from offcial documents such as constitutions and government records. The other half consists of evaluative indicators on topics like political practices and compliance with de jure rules. On such issues, typically five experts provide ratings. V-Dem works closely with leading social science research methodologists and has developed a state of the art Bayesian Item Response Theory measurement model that, to the extent possible, minimizes coder error and addresses issues of comparability across countries and over time. V-Dem also draws on the team’s academic expertise to develop theoretically informed techniques for aggregating indicators into mid- and high-level indices. In this sense, V-Dem is at the cutting edge of developing new and improved methods of social science measurement. Varianter på demokrati (V-Dem) är ett internationellt forskningsprojekt vars syfte är att ta fram nya indikatorer på demokrati, i alla världens länder från år 1789 fram till idag. V-Dem erbjuder ett nytt sätt att konceptualisera och mäta demokrati, och särskiljer mellan fem demokratiprinciper: val-, liberal-, deltagar-, deliberativ- och jämlikhetsdemokrati, och samlar in data för att mäta dessa. V-Dem draws on theoretical and methodological expertise from its worldwide team to produce data in the most objective and reliable way possible. Approximately half of the indicators in the V-Dem dataset are based on factual information obtainable from offcial documents such as constitutions and government records. The other half consists of evaluative indicators on topics like political practices and compliance with de jure rules. On such issues, typically five experts provide ratings.V-Dem draws on theoretical and methodological expertise from its worldwide team to produce data in the most objective and reliable way possible. Approximately half of the indicators in the V-Dem dataset are based on factual information obtainable from offcial documents such as constitutions and government records. The other half consists of evaluative indicators on topics like political practices and compliance with de jure rules. On such issues, typically five experts provide ratings. OtherOther ÖvrigtÖvrigt Communications Media Computer Communicat... Computer Systems Computing Methodolo... Datametoder Datornät Datorsystem Government Information Science Information Sources Informationskällor Informationsvetenskap Internet Kommunikationsmedia POLITICS POLITIK Political Science Political Science e... Regering Samhällsvetenskap Social Media Social Sciences Sociala medier Statsvetenskap Statsvetenskap exkl... civil and political... communications corruption data democracy democratization demokrati demokratisering election data elections electoral issues gender equality heads of government heads of state human rights international law internationell rätt juridik jämställdhet kommunikation korruption lag och rätt lagstiftande försam... law law and justice legislature mass communication mass media mass media bias mass media coverage mass media use masskommunikation massmedia massmediabevakning medborgerliga och p... media literacy mediaanvändning mediavinkling mediekunskap mänskliga rättigheter naturvetenskaplig f... offentliga personer political change political groups political institutions political parties political systems political systems a... politicians politics politik politiker politisk förändring politiska grupper politiska instituti... politiska partier politiska system politiska system oc... public figures regeringschefer right to non discri... rights and privileges rätten till likabeh... rättigheter och pri... science and technology scientific research social inequality social ojämlikhet social stratification social stratifiering social structure social struktur sovereignty stat state statschefer suveränitet technology and inno... teknologi val valdata valproblem vetenskap och tekno...

https://store.poidata.xyz/br

Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Brazil POI Dataset is one of our worldwide POI datasets with over 90% coverage.

This is our process flow:

Our machine learning systems continuously crawl for new POI data
Our geoparsing and geocoding calculates their geo locations
Our categorization systems cleanup and standardize the datasets
Our data pipeline API publishes the datasets on our data store

POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

The main attribute coverage is as follows:

Poi Field Data Coverage (%) poi_name 100 brand 6 poi_tel 53 formatted_address 100 main_category 100 latitude 100 longitude 100 neighborhood 1 source_url 30 email 5 opening_hours 58

A data sample may be downloaded at https://store.poidata.xyz/datafiles/br_sample.csv and the data may be previewed on a map at https://store.poidata.xyz/br

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