Description:

The "Daily Social Media Active Users" dataset provides a comprehensive and dynamic look into the digital presence and activity of global users across major social media platforms. The data was generated to simulate real-world usage patterns for 13 popular platforms, including Facebook, YouTube, WhatsApp, Instagram, WeChat, TikTok, Telegram, Snapchat, X (formerly Twitter), Pinterest, Reddit, Threads, LinkedIn, and Quora. This dataset contains 10,000 rows and includes several key fields that offer insights into user demographics, engagement, and usage habits.

Dataset Breakdown:

• Platform: The name of the social media platform where the user activity is tracked. It includes globally recognized platforms, such as Facebook, YouTube, and TikTok, that are known for their large, active user bases.

• Owner: The company or entity that owns and operates the platform. Examples include Meta for Facebook, Instagram, and WhatsApp, Google for YouTube, and ByteDance for TikTok.

• Primary Usage: This category identifies the primary function of each platform. Social media platforms differ in their primary usage, whether it's for social networking, messaging, multimedia sharing, professional networking, or more.

• Country: The geographical region where the user is located. The dataset simulates global coverage, showcasing users from diverse locations and regions. It helps in understanding how user behavior varies across different countries.

• Daily Time Spent (min): This field tracks how much time a user spends on a given platform on a daily basis, expressed in minutes. Time spent data is critical for understanding user engagement levels and the popularity of specific platforms.

• Verified Account: Indicates whether the user has a verified account. This feature mimics real-world patterns where verified users (often public figures, businesses, or influencers) have enhanced status on social media platforms.

• Date Joined: The date when the user registered or started using the platform. This data simulates user account history and can provide insights into user retention trends or platform growth over time.

Context and Use Cases:

• This synthetic dataset is designed to offer a privacy-friendly alternative for analytics, research, and machine learning purposes. Given the complexities and privacy concerns around using real user data, especially in the context of social media, this dataset offers a clean and secure way to develop, test, and fine-tune applications, models, and algorithms without the risks of handling sensitive or personal information.

Researchers, data scientists, and developers can use this dataset to:

• Model User Behavior: By analyzing patterns in daily time spent, verified status, and country of origin, users can model and predict social media engagement behavior.

• Test Analytics Tools: Social media monitoring and analytics platforms can use this dataset to simulate user activity and optimize their tools for engagement tracking, reporting, and visualization.

• Train Machine Learning Algorithms: The dataset can be used to train models for various tasks like user segmentation, recommendation systems, or churn prediction based on engagement metrics.

• Create Dashboards: This dataset can serve as the foundation for creating user-friendly dashboards that visualize user trends, platform comparisons, and engagement patterns across the globe.

• Conduct Market Research: Business intelligence teams can use the data to understand how various demographics use social media, offering valuable insights into the most engaged regions, platform preferences, and usage behaviors.

• Sources of Inspiration: This dataset is inspired by public data from industry reports, such as those from Statista, DataReportal, and other market research platforms. These sources provide insights into the global user base and usage statistics of popular social media platforms. The synthetic nature of this dataset allows for the use of realistic engagement metrics without violating any privacy concerns, making it an ideal tool for educational, analytical, and research purposes.

The structure and design of the dataset are based on real-world usage patterns and aim to represent a variety of users from different backgrounds, countries, and activity levels. This diversity makes it an ideal candidate for testing data-driven solutions and exploring social media trends.

Future Considerations:

As the social media landscape continues to evolve, this dataset can be updated or extended to include new platforms, engagement metrics, or user behaviors. Future iterations may incorporate features like post frequency, follower counts, engagement rates (likes, comments, shares), or even sentiment analysis from user-generated content.

By leveraging this dataset, analysts and data scientists can create better, more effective strategies ...

How many people use social media?

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

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

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

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

This dataset contains 600 synthetic entries simulating social media activity across three major platforms: Twitter, Reddit, and Instagram. The data was generated to analyze trends, sentiments, and user engagement patterns based on hashtags and posts. It can be useful for researchers, data analysts, and machine learning enthusiasts interested in studying social media behavior.

Dataset Structure The dataset includes the following columns:

Date: The date of the post, ranging across a simulated timeline. Platform: The social media platform where the post was made (Twitter, Reddit, or Instagram). Hashtag: The main hashtag associated with the post, such as #AI, #MachineLearning, or #Python. Post Content: The text of the post, crafted to simulate common social media interactions. Sentiment: The sentiment of the post, classified as Positive, Neutral, or Negative. Likes: The number of likes the post received. Shares: The number of shares or retweets the post received. Potential Use Cases Sentiment analysis: Train machine learning models to detect sentiment in text. Hashtag popularity analysis: Determine which hashtags are most commonly used or generate the most engagement. Engagement trends: Explore correlations between post sentiment and engagement metrics (likes/shares). Platform comparison: Compare user behavior across different social media platforms. Acknowledgments This dataset is fully synthetic and was generated using Python. It does not contain any real user data and is intended for educational and research purposes.

Which county has the most Facebook users?

              There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.

              Facebook – the most used social media

              Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.

              Facebook usage by device
              As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

This dataset consists of 734 entries representing social media activity and performance from a local SME (Micro, Small, and Medium Enterprise) across TikTok, Instagram, and Twitter platforms. It captures key metrics related to audience interaction and content strategy effectiveness, and is valuable for evaluating and optimizing digital marketing efforts for small businesses.

Area : Target location or customer region where the UMKM's content is directed. Category : The business content category (e.g., product promotion, education, seasonal campaign). Day : The day of the week the content was published. Month : The month the post went live. Platform : The social media platform used by the UMKM (TikTok, Instagram, or Twitter). Post Type : The format of the content posted: image, video, carousel, or text. Timestamp : The exact date and time when the content was posted. User : The username or business account that posted the content. Week : Week number within the year for time-based analysis. Year : The year the content was posted. Comments : Total number of comments received on the post. Engagement Rate : A calculated metric showing how engaging the content is (based on likes, comments, shares vs. reach/impressions). Hour : Hour of the day the post was published. Impressions : Number of times the content appeared on users' feeds. Likes : Number of likes the post received. Reach : Number of unique users who saw the content. Shares : Number of times users shared the content.

As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.

This dataset provides a comprehensive analysis of the factors influencing the credibility of information on social media among Iranian users. The research focuses on identifying the most significant factors that affect the perceived credibility of information shared on various social media platforms. The dataset includes demographic information, social media usage patterns, and ratings of various attributes related to information credibility.

Key Features

• Demographic Data: Includes age, gender, education level, study field, and university.
• Social Media Usage: Details on the number of social media memberships, active platforms, and average hours spent per day.
• Credibility Factors: Ratings on various attributes such as source trustworthiness, media structure, message accuracy, and more.
• Comprehensive Coverage: Covers multiple dimensions of social media usage and information credibility.
• User-Centric Insights: Provides insights into how users perceive and interact with information on social media.

Potential Uses

• Academic Research: Investigate the factors that influence information credibility on social media.
• Social Media Analysis: Understand user behavior and preferences on social media platforms.
• Policy Development: Inform policies related to information dissemination and credibility on social media.
• Marketing and Advertising: Tailor content strategies based on user perceptions of credibility.
• User Experience Design: Improve the design and functionality of social media platforms to enhance information credibility.

During a 2024 survey among marketers worldwide, around 86 percent reported using Facebook for marketing purposes. Instagram and LinkedIn followed, respectively mentioned by 79 and 65 percent of the respondents.

              The global social media marketing segment

              According to the same study, 59 percent of responding marketers intended to increase their organic use of YouTube for marketing purposes throughout that year. LinkedIn and Instagram followed with similar shares, rounding up the top three social media platforms attracting a planned growth in organic use among global marketers in 2024. Their main driver is increasing brand exposure and traffic, which led the ranking of benefits of social media marketing worldwide.

              Social media for B2B marketing

              Social media platform adoption rates among business-to-consumer (B2C) and business-to-business (B2B) marketers vary according to each subsegment's focus. While B2C professionals prioritize Facebook and Instagram – both run by Meta, Inc. – due to their popularity among online audiences, B2B marketers concentrate their endeavors on Microsoft-owned LinkedIn due to its goal to connect people and companies in a corporate context.

This dataset about Most Used Social Media Platforms is extracted from Flourish visualisation. If you want to know more about Flourish click here.

A global survey conducted in the third quarter of 2024 found that the main reason for using social media was to keep in touch with friends and family, with over 50.8 percent of social media users saying this was their main reason for using online networks. Overall, 39 percent of social media users said that filling spare time was their main reason for using social media platforms, whilst 34.5 percent of respondents said they used it to read news stories. Less than one in five users were on social platforms for the reason of following celebrities and influencers.

              The most popular social network

              Facebook dominates the social media landscape. The world's most popular social media platform turned 20 in February 2024, and it continues to lead the way in terms of user numbers. As of February 2025, the social network had over three billion global users. YouTube, Instagram, and WhatsApp follow, but none of these well-known brands can surpass Facebook’s audience size.
              Moreover, as of the final quarter of 2023, there were almost four billion Meta product users.

              Ever-evolving social media usage

              The utilization of social media remains largely gratuitous; however, companies have been encouraging users to become paid subscribers to reduce dependence on advertising profits. Meta Verified entices users by offering a blue verification badge and proactive account protection, among other things. X (formerly Twitter), Snapchat, and Reddit also offer users the chance to upgrade their social media accounts for a monthly free.

Publisher Name: Eurostat

This data is gathered by Eurostat and is available in European Commission online for free. you can check it out by this link.

European Union is the covered area in this data set and covers from 2013 to 2021 and is a 44456 * 11 dataset.

This Data Set is containing Social media use by type, internet advertising and size class of enterprise.

This data identifies by isoc_cismt.

Dataset Description

Dataset Overview

This dataset encompasses a meticulously compiled collection of 2000 posts from the official International Cricket Council (ICC) Facebook page. Each entry captures the dynamic interactions of cricket enthusiasts around the globe, presenting a unique opportunity to explore the trends, sentiments, and patterns within the cricket community. The data was ethically mined today, ensuring up-to-date insights into the latest discussions and opinions circulating among ICC followers.

Data Science Applications

The breadth and depth of this dataset offer a fertile ground for a variety of data science projects, including but not limited to: - Sentiment Analysis: Gauge the emotional tone and sentiment of the global cricket community towards events, matches, and players. - Trend Analysis: Identify emerging trends in discussions, such as rising popularity of players or reactions to cricketing events. - Engagement Analysis: Understand what type of content generates the most engagement in terms of likes, shares, and comments. - Network Analysis: Explore the social dynamics and influence patterns within the cricket fan community. - Natural Language Processing (NLP): Employ advanced NLP techniques to extract insights, themes, and patterns from textual content.

Column Descriptors

The dataset is structured into four key columns: - Comments: Number of comments on each post, reflecting the level of interaction and discussion each topic generates. - Likes: Number of likes on each post, indicating the overall popularity and approval from the community. - Shares: Number of shares for each post, showing the extent to which content is circulated beyond the immediate audience. - Text: The textual content of the post, providing rich qualitative data for textual analysis and insight generation.

Ethically Mined Data

This dataset was ethically mined with strict adherence to privacy and data use policies, ensuring that all information was collected in a manner that respects user privacy and platform guidelines. No personal user data was collected or used in the creation of this dataset.

Acknowledgements

We extend our gratitude to the International Cricket Council (ICC) and Facebook for fostering an engaging and vibrant community where fans from around the world can share their passion for cricket. Their platforms not only bring fans closer to the game but also provide valuable data that can be used to enhance our understanding of sports communities and fan engagement.

This dataset serves as an invaluable resource for data scientists, researchers, and cricket enthusiasts alike, offering insights into the global conversation surrounding one of the world's most beloved sports.

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

              Social media: trust and consumption

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

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

This data set belongs to:Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L., & Valkenburg, P. M. (2020). The effect of social media on well-being differs from adolescent to adolescent. Scientific Reports. doi:10.1038/s41598-020-67727-7The design, sampling and analysis plan of the study are available on the Open Science Framework (OSF) at https://osf.io/nhks2.For more information, please contact the authors at i.beyens@uva.nl or info@project-awesome.nl.

This database is comprised of 951 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 509 males (54%) and 442 females (46%). Their ages ranged from 12 to 16 years (M = 13.69, SD = 0.72). Seven participants did not report their age. The majority were born in Australia (N = 849, 89%). The next most common countries of birth were China (N = 24, 2.5%), the UK (N = 23, 2.4%), and the USA (N = 9, 0.9%). Data were drawn from students at five Australian independent secondary schools.

The data contains item responses for the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. The Social media question asked about frequency of use with the question “How often do you use social media?”. The response options ranged from constantly to once a week or less. Items measuring Fear of Missing Out were included and incorporated the following five questions based on the APS Stress and Wellbeing in Australia Survey (APS, 2015). These were “When I have a good time it is important for me to share the details online; I am afraid that I will miss out on something if I don’t stay connected to my online social networks; I feel worried and uncomfortable when I can’t access my social media accounts; I find it difficult to relax or sleep after spending time on social networking sites; I feel my brain burnout with the constant connectivity of social media. Internal consistency for this measure was α = .81. Self compassion was measured using the 12-item short-form of the Self-Compassion Scale (SCS-SF; Raes et al., 2011).

The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels.

References:

Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. _{https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4}

Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. _{https://doi.org/10.1002/cpp.702}

Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. _{https://doi.org/10.1016/S0005-7967(98)00034-5}

This dataset covers aspects of online politics in 25 democracies: 15 relatively old established European democracies (Austria, Belgium, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Sweden, Switzerland, United Kingdom); five non-European veteran democracies (Australia, Canada, Israel, Japan, New Zealand); two early (Portugal, Spain) and three late (Czech Republic, Hungary, Poland) third-wave (young) European democracies. The research population includes, in each country, parties that won 4% or more of the votes in two consecutive elections before April 2019 (a total of 141 parties and 145 leaders). The dataset includes external party level information such as performance in the last national elections, governmental status, party age, populism affiliation and leadership selection method. It also includes information related to the party leaders such as their term in leadership office and other formal positions. In addition it includes information about online activity mainly on the consumption (user related activities) of the parties and their leaders in Facebook and Twitter two of the most used social media platforms for political purposes.

The Reddit Subreddit Dataset by Dataplex offers a comprehensive and detailed view of Reddit’s vast ecosystem, now enhanced with appended AI-generated columns that provide additional insights and categorization. This dataset includes data from over 2.1 million subreddits, making it an invaluable resource for a wide range of analytical applications, from social media analysis to market research.

Dataset Overview:

This dataset includes detailed information on subreddit activities, user interactions, post frequency, comment data, and more. The inclusion of AI-generated columns adds an extra layer of analysis, offering sentiment analysis, topic categorization, and predictive insights that help users better understand the dynamics of each subreddit.

2.1 Million Subreddits with Enhanced AI Insights: The dataset covers over 2.1 million subreddits and now includes AI-enhanced columns that provide: - Sentiment Analysis: AI-driven sentiment scores for posts and comments, allowing users to gauge community mood and reactions. - Topic Categorization: Automated categorization of subreddit content into relevant topics, making it easier to filter and analyze specific types of discussions. - Predictive Insights: AI models that predict trends, content virality, and user engagement, helping users anticipate future developments within subreddits.

Sourced Directly from Reddit:

All social media data in this dataset is sourced directly from Reddit, ensuring accuracy and authenticity. The dataset is updated regularly, reflecting the latest trends and user interactions on the platform. This ensures that users have access to the most current and relevant data for their analyses.

Key Features:

• Subreddit Metrics: Detailed data on subreddit activity, including the number of posts, comments, votes, and user participation.
• User Engagement: Insights into how users interact with content, including comment threads, upvotes/downvotes, and participation rates.
• Trending Topics: Track emerging trends and viral content across the platform, helping you stay ahead of the curve in understanding social media dynamics.
• AI-Enhanced Analysis: Utilize AI-generated columns for sentiment analysis, topic categorization, and predictive insights, providing a deeper understanding of the data.

Use Cases:

• Social Media Analysis: Researchers and analysts can use this dataset to study online behavior, track the spread of information, and understand how content resonates with different audiences.
• Market Research: Marketers can leverage the dataset to identify target audiences, understand consumer preferences, and tailor campaigns to specific communities.
• Content Strategy: Content creators and strategists can use insights from the dataset to craft content that aligns with trending topics and user interests, maximizing engagement.
• Academic Research: Academics can explore the dynamics of online communities, studying everything from the spread of misinformation to the formation of online subcultures.

Data Quality and Reliability:

The Reddit Subreddit Dataset emphasizes data quality and reliability. Each record is carefully compiled from Reddit’s vast database, ensuring that the information is both accurate and up-to-date. The AI-generated columns further enhance the dataset's value, providing automated insights that help users quickly identify key trends and sentiments.

Integration and Usability:

The dataset is provided in a format that is compatible with most data analysis tools and platforms, making it easy to integrate into existing workflows. Users can quickly import, analyze, and utilize the data for various applications, from market research to academic studies.

User-Friendly Structure and Metadata:

The data is organized for easy navigation and analysis, with metadata files included to help users identify relevant subreddits and data points. The AI-enhanced columns are clearly labeled and structured, allowing users to efficiently incorporate these insights into their analyses.

Ideal For:

• Data Analysts: Conduct in-depth analyses of subreddit trends, user engagement, and content virality. The dataset’s extensive coverage and AI-enhanced insights make it an invaluable tool for data-driven research.
• Marketers: Use the dataset to better understand your target audience, tailor campaigns to specific interests, and track the effectiveness of marketing efforts across Reddit.
• Researchers: Explore the social dynamics of online communities, analyze the spread of ideas and information, and study the impact of digital media on public discourse, all while leveraging AI-generated insights.

This dataset is an essential resource for anyone looking to understand the intricacies of Reddit's vast ecosystem, offering the data and AI-enhanced insights needed to drive informed decisions and strategies across various fields. Whether you’re tracking emerging trends, analyzing user behavior, or conduc...

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.

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.

**Description

To ensure the relevance and recency of the collected data, we further narrowed our dataset by limiting the publication years to the period spanning from 2010 to 2023. This restriction aimed to capture the most contemporary and pertinent research in social media surveillance.

After this limitation, the dataset consisted of 927 academic publications. This meticulous search and selection process laid the foundation for our systematic and bibliometric analysis, allowing us to comprehensively examine the scholarly discourse surrounding social media surveillance, identify key themes, and assess the intellectual structure of the field from 2010 to 2023.

The dataset comprises 927 academic publications spanning from 2010 to 2023, focusing on social media surveillance. Below is a description of the dataset columns:

Authors: Names of the authors who contributed to the publication. Author full names: Full names of the authors with their respective author IDs. Author(s) ID: Unique identifiers assigned to each author. Title: Title of the publication. Year: Year of publication. Source title: Name of the journal, book, or conference where the publication appeared. Volume: Volume number of the source. Issue: Issue number of the source. Art. No.: Article number within the source. Page start: Starting page number of the publication. Page end: Ending page number of the publication. Page count: Total number of pages of the publication. Cited by: Number of times the publication has been cited by other works. DOI: Digital Object Identifier for the publication. Link: URL link to access the publication. Affiliations: Institutions or organizations associated with the authors. Authors with affiliations: Authors listed with their respective affiliations. Abstract: Summary of the publication. Author Keywords: Keywords provided by the authors. Index Keywords: Keywords assigned by indexing services. Molecular Sequence Numbers: Identifiers for molecular sequences mentioned. Chemicals/CAS: Chemical Abstracts Service numbers for chemicals mentioned. Tradenames: Trade names of products or chemicals mentioned. Manufacturers: Manufacturers of products or chemicals mentioned. Funding Details: Information about the funding sources. Funding Texts: Detailed text describing the funding sources. References: List of references cited in the publication. Correspondence Address: Contact address for correspondence with authors. Editors: Names of the editors of the publication. Publisher: Name of the publisher. Sponsors: Sponsors of the publication or research. Conference name: Name of the conference where the paper was presented. Conference date: Date of the conference. Conference location: Location of the conference. Conference code: Code associated with the conference. ISSN: International Standard Serial Number for the source. ISBN: International Standard Book Number for the source. CODEN: Six-character code used to identify periodicals. PubMed ID: Identifier for publications indexed in PubMed. Language of Original Document: Language in which the publication was written. Abbreviated Source Title: Abbreviated title of the source. Document Type: Type of document (e.g., article, book chapter). Publication Stage: Stage of publication (e.g., final, in press). Open Access: Open access status of the publication. Source: Database source of the publication (e.g., Scopus). EID: Electronic Identifier for the publication.