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The Afrobarometer is a comparative series of public attitude surveys that collects and disseminates data regarding Africans' views on democracy, governance, the economy, civil society, and related issues. This particular data collection was concerned with the attitudes and opinions of the citizens of Morocco, and also includes a number of "country-specific questions" designed specifically for the Morocco survey.

The data were collected from nationally representative samples in face-to-face interviews in the language of the respondent's choice. Standard topics for the Afrobarometer include attitudes toward and evaluations of democracy, governance and economic conditions, political participation, and national identity. In addition, Round 6 surveys included special modules on taxation; tolerance; crime, conflict and insecurity; political corruption; interregional relations; perceptions of China; use of technology; and social service delivery. The surveys for Morocco included specific questions about the usage of social media, choosing representatives, the impact of the Arab Spring, ISIL (The Islamic State of Iraq and the Levant) and AQIM (Al Qaida in the Maghreb), and human rights.

The surveys also collect a large set of socio-demographic indicators such as age, gender, education level, poverty level, language and ethnicity, and religious affiliation, as well as political party affiliation. Afrobarometer Round 6 surveys were implemented in 36 countries.

This study is part of the American National Election Study (ANES), a time-series collection of national surveys fielded continuously since 1948. The American National Election Studies are designed to present data on Americans' social backgrounds, enduring political predispositions, social and political values, perceptions and evaluations of groups and candidates, opinions on questions of public policy, and participation in political life. As with all Time Series studies conducted during years of presidential elections, respondents were interviewed during the two months preceding the November election (Pre-election interview), and then re-interviewed during the two months following the election (Post-election interview). Like its predecessors, the 2020 ANES was divided between questions necessary for tracking long-term trends and questions necessary to understand the particular political moment of 2020. The study maintains and extends the ANES time-series 'core' by collecting data on Americans' basic political beliefs, allegiances, and behaviors, which are so critical to a general understanding of politics that they are monitored at every election, no matter the nature of the specific campaign or the broader setting. This 2020 ANES study features a fresh cross-sectional sample, with respondents randomly assigned to one of three sequential mode groups: web only, mixed web (i.e., web and phone), and mixed video (i.e., video, web, and phone). The new content for the 2020 pre-election survey includes coronavirus pandemic, election integrity, corruption, impeachment, immigration and democratic norms. The pre-election survey also includes protests and unrest over policing and racism. The new content for the 2020 post-election survey includes voting experiences, anti-elitism, faith in experts or science, climate change, gun control, opioids, rural-urban identity, international trade, transgender military service, social media usage, misinformation, perceptions of foreign countries and group empathy. Phone and video interviews were conducted by trained interviewers using computer-assisted personal interviewing (CAPI) software on computers. Unlike in earlier years, the 2020 ANES did not use computer-assisted self interviewing (CASI) during any part of the interviewer-administered modes (video and phone). Rather, in interviewer-administered modes, all questions were read out loud to respondents, and respondents also provided their answers orally. Demographic variables include respondent age, education level, political affiliation, race/ethnicity, marital status, and family composition.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This is a dataset of tweets purchased from Twitter as part of the Beyond the Hashtags study. The dataset includes a year of tweets that mention one or more of 45 keywords associated with the BlackLivesMatter movement. This period covers a critical time in which social media was used to raise awareness about police killings of unarmed Black citizens in the United States.

This dataset consists of all starter packs and all following network data available on Bluesky as of late October 2025. Starter packs can be created by any Bluesky user. They are lists of users and curated feeds with a minimum of 6 and a maximum of 150 users, curated by the starter pack creator. The creator typically names them and provides a description. Other users can use a single click to follow all users in the starter pack, or they can scroll through a specific starter pack to decide who to follow within that starter pack. In our dataset, all DIDs (persistent, unique identifiers) are anonymized with a non-reversible hash function; users in the network, as well as users who created starter packs, or appear in starter packs, are identified by their hashed DIDs. Similarly, starter packs themselves are identified by their hashed identifiers.

First, we include the Bluesky following network as it appeared in late October 2025. This shows all available directed following relationships on Bluesky. We also include a network dataset of starter packs with information on creators and starter pack members. This is intended for users who wish to undertake a computational analysis of the networks created by starter packs or starter packs’ influences on networks.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

Candidata is a dataset of social media handles and posts for candidates for primary and general federal elections in the United States in 2024 across multiple social media platforms. The dataset spans Facebook, Instagram, Threads, TikTok, X (Twitter), YouTube, Gettr, Rumble, Telegram, and Truth Social. For interoperability, we provide FEC IDs and ICPSR IDs where available.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains descriptive statistics and characteristics of network-affiliated Facebook Groups that were removed due to Meta’s Coordinated Inauthentic Behavior and Inauthentic Behavior policies.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains descriptive statistics and characteristics of network-affiliated Facebook Pages that were removed due to Meta’s Coordinated Inauthentic Behavior and Inauthentic Behavior policies.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains descriptive statistics and characteristics of network-affiliated Facebook user accounts that were removed due to Meta’s Coordinated Inauthentic Behavior and Inauthentic Behavior policies.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains descriptive statistics and characteristics of network-affiliated Instagram user accounts that were removed due to Meta’s Coordinated Inauthentic Behavior and Inauthentic Behavior policies.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

The rapid advancements in generative AI models present new opportunities in the education sector. However, it is imperative to acknowledge and address the potential risks and concerns that may arise with their use. We collected Twitter data to identify key concerns related to the use of ChatGPT in education. This dataset is used to support the study "ChatGPT in education: A discourse analysis of worries and concerns on social media."

In this study, we particularly explored two research questions. RQ1 (Concerns): What are the key concerns that Twitter users perceive with using ChatGPT in education? RQ2 (Accounts): Which accounts are implicated in the discussion of these concerns? In summary, our study underscores the importance of responsible and ethical use of AI in education and highlights the need for collaboration among stakeholders to regulate AI policy.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

The metrics in this dataset measure the audience size and views of posts with links to a specific pair of domains classified as civic news. The dataset contains domain-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes, political interest.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

The metrics in this dataset measure the audience size and views of posts with links to a specific pair of URLs classified as civic news. The dataset contains URL-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes, political interest.

The goal of this Common Sense research study was to provide current information about parent media use and their perceptions of their children and teens' (ages 8-18) media use. Data is from a nationally representative, probability-based, and cross-sectional online survey that was taken by parents of children and teens ages 8- to 18-years-old. Participants answered questions about their media use and their perception of their tweens or teens' media use. Media use included watching television, movies, and videos; playing video games; listening to music; using social media, reading either print or electronic books; and using digital devices for other purposes, such as browsing websites, playing games, or any other activity. We also asked about computer, smartphone, and tablet (and similar device) use for work purposes. Demographics include age, household income, parent education, race/ethnicity, gender, household size, and parent/caregiver employment status.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset includes aggregated statistics about the gender and age of monthly active users of Facebook. These data are related to adult U.S. Facebook users reached by social issues, elections, and political (SIEP) ads from September 24, 2020 through November 3rd, 2020.

Dating It Safe is a longitudinal cohort study of 1,042 youth in southeast Texas. Primarily freshmen high school students were recruited and assessed in the spring of 2010. Follow-up waves were collected annually each spring from 2011 through 2017 (Waves 2-8). The primary aims of this research study were to examine the:

• longitudinal association between the three different forms of teen dating violence (TDV; i.e., physical violence, psychological abuse, and sexual aggression), and
• risk and protective factors of TDV perpetration and victimization.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing U.S. adult active users' exposure to ads on Facebook and Instagram by the official presidential campaign accounts during each survey wave period before the 2020 election.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing U.S. adult active users' exposure to social issues, elections, and political ads (excluding official presidential campaign ads) on Facebook and Instagram during the study period.

The COVID-19 Trends and Impact Survey (CTIS) was conducted by the Delphi Group at Carnegie Mellon University (CMU) in the United States (US) and by the University of Maryland (UMD) Social Data Science Center (SoDa) globally, in partnership with Meta. CTIS was a daily repeated cross-sectional survey that ran continuously starting April 6, 2020 in the US and starting April 23, 2020 globally. Both surveys concluded data collection on June 25, 2022. CTIS collected data in 200+ countries and territories, including 114 where Meta provided survey weights. The sampling frame was Facebook users aged 18 years or older who have been active on the platform in the last month. Sampled Facebook users saw the invitation at the top of their Feed, but the surveys were collected by the universities using Qualtrics. Meta neither collected nor received survey responses. The sample was stratified by subnational regions. Respondents were sampled as frequently as every month and as infrequently as every six months, depending on the population density of the subnational region in which they lived. Due to the minimum sampling frequency, pooled analyses should not combine more than a month of data. There were 12 versions of the survey questionnaires. The Delphi US CTIS was translated into 8 languages. The UMD Global CTIS was translated into 66 languages.

This collection is comprised of three categories of data:

a. Individual-level microdata files, which will be available to eligible academic and nonprofit researchers with fully executed Data Use Agreements (DUAs).

b. Daily aggregate estimates at the country and subnational region levels disseminated via public APIs at CMU and UMD.

c. Weekly and monthly aggregate estimates broken out by respondent characteristics (e.g., age, gender, vaccination status) at the country and subnational administrative level-1 region-level disseminated via publicly available CSV-formatted contingency tables.

This collection currently only contains the aggregate data, contingency tables and associated documentation. The microdata are forthcoming.

The United States COVID-19 Trends and Impact Survey (CTIS) was a voluntary survey of Facebook users in the United States conducted from April 2020 to June 2022. CTIS was intended to aid in pandemic forecasting and response at fine spatiotemporal detail. Through collaboration with Meta, it randomly sampled Facebook active users at a rate sufficient to provide roughly 35,000 responses per day, on average. Survey questions covered topics including COVID-like symptoms, behavior (such as social distancing), COVID testing, mental health, health-related beliefs, trust in officials and information sources, schooling, vaccination acceptance and hesitancy, and related subjects. Respondents provided their ZIP code. Demographic variables include age, gender, education, race/ethnicity, and occupation. Meta generated survey weights to correct for non-response and to match the US adult population age and gender distribution.

The 27 datasets make up the microdata. Users should see the Microdata User Guide for documentation on the use and interpretation of the microdata files.

Two zip files are available for public download: a monthly data zip file and a weekly data zip file. These include the aggregate data. To access these files, go to the "Download" tab and select "Other." Ensure you have enough storage space before proceeding, as the files are large.

This study examines the radicalization of Western women to extremist violence, both through the creation of a moral-situational-action risk model and the examination of their responses to various types of online propaganda. The Moral-Situational-Action Risk Model for Extremist Violence (MSA-RMEV) was developed using situational action theory from criminology and violence risk practice literature. The MSA-RMEV revolves around three domains reflective of propensity, mobilization, and capacity building, geared towards providing a violence risk assessment that can assist the intelligence community in preventing future acts of violence.

A sample of women who self-identified as conservative, liberal, and Muslim were exposed to jihadist, alt-right, and alt-left online propaganda. Physiological responses and self-report assessments were recorded. Eye-gaze, pupil dilation, galvanic skin response, heart rate, and facial emotions were documented, along with women's judgment of their emotional, cognitive, and arousal states, while viewing propaganda.

Based on their results, women were categorized as high-risk, medium-risk, or low-risk for violence. Additionally, numerous variables were created to identify participant's beliefs and behavior related to radicalization. Beliefs included religiosity, political affiliation, the presence of moral emotions, sacred values, developmental maturity, and militant thinking. Behaviors included group affiliations, extent of involvement in extremist activities, and presence on social media platforms such as Facebook, Reddit, and Twitter. Demographic variables such as age, marital status, number of children, race, ethnicity, country of origin, and educational status were included.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing cumulative U.S. adult active users' exposure to and engagement with Facebook content by deceptive online networks. Exposure and engagement metrics include viewers, views, and reshares. The dataset is structured by cumulative exposure by percentile of active users (incremented by 0.01%). Each row represents the cumulative exposure to deceptive online networks by a cumulative percentile of monthly active Facebook users.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing cumulative U.S. adult active users' exposure to and engagement with Instagram content by deceptive online networks. Exposure and engagement metrics include viewers, views, and reshares. The dataset is structured by cumulative exposure by percentile of active users (incremented by 0.01%). Each row represents the cumulative exposure to deceptive online networks by a cumulative percentile of monthly active Instagram users.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains user-level metrics from aggregated Facebook activity data for U.S. adult monthly active users.

These metrics measure the creation of ad content by network-affiliated accounts and reshares of original network posts by accounts unaffiliated with the deceptive online network daily during the study period.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains user-level metrics from aggregated Facebook activity data for U.S. adult monthly active users.

These metrics measure the creation of and engagement with content by network-affiliated accounts and reshares of original network posts by accounts unaffiliated with the deceptive online network on Facebook daily during the study period.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains user-level metrics from aggregated Instagram activity data for U.S. adult monthly active users.

These metrics measure the creation of and engagement with content by network-affiliated accounts and reshares of original network posts by accounts unaffiliated with the deceptive online network on Instagram daily during the study period.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset measures the ideological segregation index and favorability score of the potential, exposed and engaged audience of posts with links to domains and URLs classified as civic news. The dataset contains domain- and URL-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated daily over the study period. Includes ideological segregation index, favorability score, content attributes, user attributes.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains a reference list of domains that were shared on Facebook during the study period, used for domain classification.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains the percentage breakdown of Facebook Monthly Active Users (MAU) by age, gender, political leaning, page/group admin status, and battleground state location.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains the percentage breakdown of Instagram Monthly Active Users (MAU) by gender and battleground state location.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains information about the demographics and on-platform behaviors of all Deactivation experiment participants, including those who left the study. The purpose of this dataset is to understand the bias in who stayed in the study compared to everyone who initially agreed to participate.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated information about the spread of ad content from deceptive online networks during the study period. Each row of the dataset corresponds to properties of an individual reshare tree. Each variable contains a value, or set of values, that aggregates data for that tree size over the period of time.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.This dataset contains information about all content reshared 100 times or more from July 1, 2020 through February 1, 2021. Each row of the dataset corresponds to properties of an individual reshare tree. Each column contains a value, or set of values, that aggregates data for that specific reshare tree over the study period.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.This dataset contains aggregated information about all content reshared at least one time but fewer than 100 times, from July 1, 2020 through February 1, 2021. Each row of the dataset contains aggregated statistics for all trees of a certain size (from 1 to 99) and content category (e.g. misinformation, user posts, group posts, Page posts, COVID-related posts, etc.). Each column contains a value, or set of values, that aggregates data for that tree size and content category over the study period.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated information about the spread of content from deceptive online networks during the study period. Each row of the dataset corresponds to properties of an individual reshare tree. Each variable contains a value, or set of values, that aggregates data for that tree size over the study period.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.This dataset contains aggregated information about all content reshared 100 or more times from July 1, 2020 through February 1, 2021. Each row of the dataset corresponds to an individual tree and its size and depth at specific hours and days from initial posting.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing U.S. adult active users’ exposure to and engagement with Facebook content by deceptive online networks. Exposure and engagement metrics include viewers, views, reactions, comments, clicks, and reshares.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing U.S. adult active users' exposure to and engagement with Facebook content by deceptive online networks. Exposure and engagement metrics include viewers, views, and reshares.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains aggregated metrics summarizing U.S. adult active users' exposure to and engagement with Instagram content by deceptive online networks. Exposure and engagement metrics include viewers, views, and reshares.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.The metrics in this dataset measure users who engaged with posts with links to civic news domains and the volume of their engagement. The dataset contains domain-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.The metrics in this dataset measure users who engaged with posts with links to civic news URLs and the volume of their engagement. The dataset contains URL-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes.

The Eurobarometer series is a unique cross-national and cross-temporal survey program conducted on behalf of the European Commission. These surveys regularly monitor public opinion in the European Union (EU) member countries and consist of standard modules and special topic modules. The standard modules address attitudes towards European unification, institutions and policies, measurements for general socio-political orientations, as well as respondent and household demographics. The special topic modules address such topics as agriculture, education, natural environment and resources, public health, public safety and crime, and science and technology.

Eurobarometer 86.1 covered the following special topics: (1) Parlemeter 2016, (2) Future of Europe, (3) Media pluralism and democracy. Respondents' opinions were collected regarding their awareness of, knowledge about, attitudes towards and trust in the European Parliament (EP). Respondents were also questioned regarding EP policy priorities and values, European identity issues, and attitudes towards and (dis-)advantages of European Union (EU) membership. Additional questions were asked about main EU assets, future EU challenges, EU political influence, and future priorities and perspective. Respondents were also asked about their trust in media, media independence and reliability, and their social media use and perceptions and experiences of abuse therein.

Demographic and other background information collected includes age, gender, nationality, marital status, occupation, age when stopped full-time education, household composition, ownership of a fixed or mobile telephone and other goods, difficulties in paying bills, level in society, and Internet use. In addition, country-specific data includes type and size of locality, region of residence, and language of interview (select countries).

This project convened experts and practitioners in the areas of program evaluation, radicalization to violent extremism, and social media analytics in order to generate and integrate scientifically derived knowledge into strategies for effective prevention and intervention against domestic radicalization and violent extremism in the United States. More specifically, we generated substantive evaluation data, which can be used by practitioners and policy makers to enhance the creation and dissemination of effective counter-narratives for reducing the threat of ideologically-motivated violence in the US. We used a mixed-methods approach to evaluate an existing nationwide initiative, Peer-to-Peer (P2P): Challenging Extremism, which aims at engaging youth in countering violent extremism in schools and online arenas.

The project had four specific objectives: 1) Evaluate the content and dissemination of the P2P Initiative social media products, 2) evaluate the impact of the P2P Initiative on youth engaged in its development, 3) evaluate the impact of youth exposure to the P2P educational activities, and 4) assess the drivers of success and barriers in the implementation of the initiative.

To complete these objectives, the following research phases were conducted:

A secondary review of 150 P2P social media products created between fall 2015 and spring 2017, including data on end-users interactivity.

Phone and in-person group interviews with faculty and students engaged in the P2P Initiative.

A prospective cohort study evaluating the impact of the Kombat with Kindness (KWK) campaign on Utah secondary school students, using a pre-post intervention design.

A randomized control study evaluating the impact of the Operation 250 (OP250) on Massachusetts secondary school students, using a pre-post intervention design.

Phone interviews with faculty who implemented the P2P Initiative.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This Monthly Active Population (MAP) dataset contains aggregated Facebook interactions for adult US monthly active users.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.The metrics in this dataset measure users who viewed posts with links to civic news domains. The dataset contains domain-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.The metrics in this dataset measure users who viewed posts with links to civic news URLs. The dataset contains URL-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This table includes platform data for Facebook participants in the Deactivation experiment. Each row of the dataset corresponds to data from a participant’s Facebook user account. Each column contains a value, or set of values, that aggregates log data for this specific participant over a certain period of time.

These data are restricted and require an application. To apply, see SOMAR’s Application Portal and Application Guide.

This dataset contains participant-level metrics from Facebook activity data for the participants in the platform interventions conducted on Facebook as part of the U.S. 2020 Facebook and Instagram Election Study (User attributes, User connections, Time spent, Content views, Content engagement).