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 ...

A supplement to "OphthalWeChat: Dataset and Benchmark for Multimodal Visual Question-Answering in Ophthalmology".📄 Dataset DisclaimerDataset Title: OphthalWeChatLicense: CC BY-NC 4.01. Source of DataThis dataset does not contain any actual image files. All entries are curated from publicly available posts on WeChat Official Accounts, and consist solely of image URLs and associated WeChat IDs. The dataset serves as an index to facilitate academic research and does not host, store, or redistribute any original visual content.2. Copyright and Intellectual PropertyAll referenced content remains the intellectual property of the original authors and the WeChat platform. This dataset makes no claim of ownership over any linked material. The collection and indexing of these links follow the principles of fair use for non-commercial, academic research purposes only.3. Usage RestrictionsThis dataset is provided strictly for non-commercial research and academic use.Commercial use of any kind—including model training, product development, or monetized applications—is explicitly prohibited.Users are solely responsible for ensuring that their use of the dataset and any linked content complies with the terms of service of WeChat and with all applicable copyright and data protection laws.4. User ResponsibilityBy using this dataset, you agree to the following:You will not attempt to reproduce any image content unless explicitly permitted by the original content provider.You will not redistribute the dataset or its indexed links for any commercial purpose.You will acknowledge the original sources and cite this dataset appropriately in any research output.You accept full legal responsibility for any downstream use of the dataset.5. Content Removal RequestsIf you are the rightful owner of content linked in this dataset and believe your rights have been infringed, please contact us for immediate removal of the relevant entries.Contact Email: xupusheng977@163.comWe are committed to responding promptly and respectfully to all legitimate requests.6. Legal DisclaimerWe reserve the right to update or modify this disclaimer at any time. The creators of this dataset accept no liability for any legal or ethical issues arising from third-party use. By accessing or using this dataset, you agree to be bound by the terms outlined above.

This study adopted a questionnaire design. We commissioned two leading WeChat public accounts (social media-based media outlets) that primarily target scientists – iScientist (WeChat ID: IamaScientist) and Fanpu (the Chinese name of the public account, which can be literally translated to “Returning to theoretical purity”, WeChat ID: fanpu2019) – to distribute the online questionnaire from February 19, 2020, when China was still suffering COVID-19 and the pandemic was beginning to spread in other places around the world. Public accounts on WeChat are social media channels that are widely adopted across China. With 1.112 billion monthly active users in the first quarter of 2019, WeChat is China's largest social media platform(Statista, 2020). Both iScientist and Fanpu had more than 100,000 subscribers on WeChat, mainly scientists, engineers, and doctoral students. The advertisement for the survey and the link to the questionnaire were posted in Chinese by the two publications and distributed in iScientist’s weekly E-newsletters among its registered readers (Fanpu didn’t provide E-newsletters), with the title highlighting that the survey focused on scientists’ communication behaviors. The questionnaire was distributed through both Qualtrics.com, an international survey platform (used initially out of concern about potential censorship in China at the onset of the pandemic), and Wjx.cn, a leading Chinese survey site. Data from the two platforms were combined into a single sample. The survey was anonymous, and the introduction clearly stated that participation was voluntary, that completion of the survey implied consent, and that respondents could withdraw at any time. Respondents who completed the questionnaire were offered a complimentary electronic book on science communication skills. The survey remained open for four weeks and was closed after sufficient data had been collected (856 completed questionnaires). We first excluded respondents who spent too little time completing the survey (≤300 seconds), and obtained a total of 802 valid questionnaires. Although the survey invitation specified that we were recruiting scientists—referring, in the Chinese context, primarily to natural science researchers—some ineligible participants still responded. We therefore screened out humanities and social science researchers, as well as non-research professionals (e.g., executives at research institutions), who numbered 44, accounting for about 5.5% of valid respondents, because their perspectives on emergency communication may differ substantially from those of natural scientists. The final dataset included 758 valid responses, with over 300 collected via Qualtrics.com and more than 450 via Wjx.cn. The questionnaire is detailed in the Supplementary material.

In 2024, Google ranked as the most valuable media and entertainment brand worldwide, with a brand value of 683 billion U.S. dollars. Facebook ranked second, valued at around 167 billion dollars. Part of the Tencent Group, WeChat and v.qq.com (Tencent Video) had a brand value of 56 billion and 17.5 billion dollars, respectively.