Important : its a 3 month gap data Starting from March 2022 to Dec 2022

Influencers are categorized by the number of followers they have on social media. They include celebrities with large followings to niche content creators with a loyal following on social-media platforms such as YouTube, Instagram, Facebook, and Twitter.Their followers range in number from hundreds of millions to 1,000. Influencers may be categorized in tiers (mega-, macro-, micro-, and nano-influencers), based on their number of followers.

Businesses pursue people who aim to lessen their consumption of advertisements, and are willing to pay their influencers more. Targeting influencers is seen as increasing marketing's reach, counteracting a growing tendency by prospective customers to ignore marketing.

Marketing researchers Kapitan and Silvera find that influencer selection extends into product personality. This product and benefit matching is key. For a shampoo, it should use an influencer with good hair. Likewise, a flashy product may use bold colors to convey its brand. If an influencer is not flashy, they will clash with the brand. Matching an influencer with the product's purpose and mood is important.

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Dataset Description: Top 100 Influencers

The dataset provides structured information about the top 100 influencers from various countries globally. Each entry represents an influencer and includes the following attributes:

• Rank: The ranking of the influencer in the top 100 list.
• Name: The name or pseudonym of the influencer.
• Follower Count: The total number of followers or subscribers the influencer has on their primary - platform(s).
• Engagement Rate: The level of interaction that the influencer's content receives from users on social media platforms, expressed as a percentage.
• Country: The geographical location or country where the influencer is based or primarily operates.
• Topic Of Influence: The niche or category in which the influencer specializes or creates content, such as fashion, beauty, technology, fitness, etc.
• Reach: The primary social media platform(s) where the influencer is active, such as Instagram, YouTube, TikTok, Twitter, etc.

Databases of highly networked individuals have been indispensable in studying narratives and influence on social media. To support studies on Twitter in India, we present a systematically categorized database of accounts of influence on Twitter in India, identified and annotated through an iterative process of friends, networks, and self-described profile information, verified manually. We built an initial set of accounts based on the friend network of a seed set of accounts based on real-world renown in various fields, and then snowballed friends of friends\" multiple times, and rank ordered individuals based on the number of in-group connections, and overall followers. We then manually classified identified accounts under the categories of entertainment, sports, business, government, institutions, journalism, civil society accounts that have independent standing outside of social media, as well as a category ofdigital first" referring to accounts that derive their primary influence from online activity. Overall, we annotated 11580 unique accounts across all categories. The database is useful studying various questions related to the role of influencers in polarisation, misinformation, extreme speech, political discourse etc.

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 ...

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

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

              How popular is Instagram?

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

              Who uses Instagram?

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

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

Gain valuable insights with our comprehensive Social Media Dataset, designed to help businesses, marketers, and analysts track trends, monitor engagement, and optimize strategies. This dataset provides structured and reliable social media data from multiple platforms.

Dataset Features

User Profiles: Access public social media profiles, including usernames, bios, follower counts, engagement metrics, and more. Ideal for audience analysis, influencer marketing, and competitive research. Posts & Content: Extract posts, captions, hashtags, media (images/videos), timestamps, and engagement metrics such as likes, shares, and comments. Useful for trend analysis, sentiment tracking, and content strategy optimization. Comments & Interactions: Analyze user interactions, including replies, mentions, and discussions. This data helps brands understand audience sentiment and engagement patterns. Hashtag & Trend Tracking: Monitor trending hashtags, topics, and viral content across platforms to stay ahead of industry trends and consumer interests.

Customizable Subsets for Specific Needs Our Social Media Dataset is fully customizable, allowing you to filter data based on platform, region, keywords, engagement levels, or specific user profiles. Whether you need a broad dataset for market research or a focused subset for brand monitoring, we tailor the dataset to your needs.

Popular Use Cases

Brand Monitoring & Reputation Management: Track brand mentions, customer feedback, and sentiment analysis to manage online reputation effectively. Influencer Marketing & Audience Analysis: Identify key influencers, analyze engagement metrics, and optimize influencer partnerships. Competitive Intelligence: Monitor competitor activity, content performance, and audience engagement to refine marketing strategies. Market Research & Consumer Insights: Analyze social media trends, customer preferences, and emerging topics to inform business decisions. AI & Predictive Analytics: Leverage structured social media data for AI-driven trend forecasting, sentiment analysis, and automated content recommendations.

Whether you're tracking brand sentiment, analyzing audience engagement, or monitoring industry trends, our Social Media Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

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.

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 social media content dataset is simulate realistic influencer posts across multiple popular platforms, reflecting diverse content types, sponsorship details, audience demographics, and engagement metrics. The dataset contains over 52,000 rows representing individual content posts generated over the past two years. It includes a balanced distribution of sponsored and non-sponsored content, with detailed disclosure information to support transparency studies and analyses. The variety of platforms, languages, content categories, and audience demographics makes this dataset ideal for exploring influencer marketing dynamics, content performance analytics, disclosure practices, and audience segmentation in social media research.

Dataset Features

id: Unique identifier for each content post (starting from 1).

platform: The social media platform where the content was posted. Values: YouTube, TikTok, Instagram, Bilibili, RedNote.

content_id: Unique ID for each content piece (e.g., content_0, content_1, …).

creator_id: Unique identifier for the content creator, cycling through 5000 distinct creators.

creator_name: Username of the content creator.

content_url: URL pointing to the content.

content_type: Format of the content. Values: video, image, text, mixed.

content_category: The main theme or niche of the content. Values: beauty, lifestyle, tech.

post_date: Timestamp of the post, randomly distributed over the past two years.

language: Language of the content, with probabilities favoring English. Values: English, Chinese, Spanish, Hindi, Japanese.

content_length: Length of the content in seconds (for video) or word count (for text), varying by content type.

content_description: Textual description or caption of the content.

hashtags: A comma-separated string of hashtags used in the post (0 to 5 tags).

views: Number of views (simulated via a Poisson distribution).

likes: Number of likes received.

shares: Number of shares.

comments_count: Count of comments on the post.

comments_text: Aggregated text of comments (0 to 5 comments concatenated).

follower_count: Number of followers the creator had at the time of posting.

is_sponsored: Boolean indicating whether the post is sponsored.

disclosure_type: Disclosure type regarding sponsorship for sponsored posts. Values: explicit, implicit, none (non-sponsored always 'none').

sponsor_name: Name of the sponsoring company if sponsored, else 'Not sponsors'.

sponsor_category: Sponsorship industry category. Values: cosmetics, electronics, fashion, food, gaming, travel or 'Not sponsors'.

disclosure_location: Where sponsorship disclosure appears in the post. Values: video, caption, hashtags, none (non-sponsored always 'none').

audience_age_distribution: Predominant age group of the audience. Values: 13-18, 19-25, 26-35, 36-50, 50+.

audience_gender_distribution: Predominant gender of the audience. Values: male, female, non-binary, unknown.

audience_location: Primary geographic location of the audience. Values: USA, China, India, Japan, Brazil, Germany, UK, Russia.

Instagram’s most popular post

              As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
              After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.

              Instagram’s most popular accounts

              As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.

              Instagram influencers

              In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.

              Instagram around the globe

              Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.

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 global social media penetration rate in was forecast to continuously increase between 2024 and 2028 by in total 11.6 (+18.19 percent). After the ninth consecutive increasing year, the penetration rate is estimated to reach 75.31 and therefore a new peak in 2028. Notably, the social media penetration rate of was continuously increasing over the past years.

This dataset captures the pulse of viral social media trends across TikTok, Instagram, Twitter, and YouTube. It provides insights into the most popular hashtags, content types, and user engagement levels, offering a comprehensive view of how trends unfold across platforms. With regional data and influencer-driven content, this dataset is perfect for:

• Trend analysis 🔍
• Sentiment modeling 💭
• Understanding influencer marketing 📈

Dive in to explore what makes content go viral, the behaviors that drive engagement, and how trends evolve on a global scale! 🌍

During a January 2024 global survey among marketers, nearly 60 percent reported plans to increase their organic use of YouTube for marketing purposes in the following 12 months. LinkedIn and Instagram followed, respectively mentioned by 57 and 56 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.

This dataset contains anonymized YouTube comment data associated with the 2019 online controversy known as Dramageddon, involving beauty influencers James Charles, Tati Westbrook, and Jeffree Star. The dataset was created for research on online hostility, cancel culture, and competitive communication dynamics among influencers.

The dataset includes public user comments collected from 14 YouTube videos posted during May–June 2019, including primary source videos from the influencers involved and reaction videos from commentary channels. A total of ~15,000 comments were collected using the YouTube Data API v3. All comments are anonymized and contain no personally identifiable information.

Each comment record is enriched with metadata and derived variables, including: - Sentiment score (range −1 to +1) - Toxicity score (probability 0–1) - Cancel behavior classification (cold, cool, hot) - Moral language category - Engagement metrics (likes, reply depth) - Time of posting - Video-level metadata (creator, phase of controversy)

This dataset supports research in computational social science, communication studies, digital sociology, and platform governance. It has been used in studies on cancel culture, moral contagion, algorithmic amplification, and influencer reputation dynamics. This dataset contains only publicly available YouTube comments retrieved in accordance with the YouTube Terms of Service. All usernames, channel IDs, and profile references were hashed or removed during preprocessing to ensure anonymization. No attempts were made to identify or contact any YouTube users. The dataset is provided strictly for research purposes. Users must agree to comply with ethical guidelines for internet research (AoIR 2019) and cite the dataset appropriately.

Databases of highly networked individuals have been indispensable in studying narratives and influence on social media. To support studies on Twitter in India, we present a systematically categorized database of accounts of influence on Twitter in India, identified and annotated through an iterative process of friends, networks, and self-described profile information, verified manually. We built an initial set of accounts based on the friend network of a seed set of accounts based on real-world renown in various fields, and then snowballed friends of friends\" multiple times, and rank ordered individuals based on the number of in-group connections, and overall followers. We then manually classified identified accounts under the categories of entertainment, sports, business, government, institutions, journalism, civil society accounts that have independent standing outside of social media, as well as a category ofdigital first" referring to accounts that derive their primary influence from online activity. Overall, we annotated 11580 unique accounts across all categories. The database is useful studying various questions related to the role of influencers in polarisation, misinformation, extreme speech, political discourse etc.

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.

Charli D'Amelio's Tweets

Measuring Popularity and Impact of Social Influencers on Twitter

By Twitter [source]

About this dataset

The Charli D'Amelio's Tweets D’Amelio Twitter Activity dataset is the perfect research tool for any researcher wishing to investigate the power of social media influencers - and specifically, the monumental rise of Charli D'Amelio's Tweets D'Amelio. It features valuable insights into follower engagement such as likes, replies, retweets, and impact on other accounts – with 13 data-rich columns in total. Followers are able to gain a comprehensive understanding of how this iconic star has molded conversations around her presence. Through interactivity and engaging content, explore an unprecedented look at the social media success story that is Charli D'Amelio's Tweets D'Amelio!

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How to use the dataset

The Charli D'Amelio's Tweets D’Amelio Twitter Activity dataset offers valuable insight into the social media presence of one of the most famous influencers on the platform. Here’s a step-by-step guide to get started:

Research Ideas

• Measuring effectiveness of influencer campaigns: The dataset can be used to measure the impact that various social media influencers have on a brand’s sales, website traffic, and customer engagement metrics by analyzing their respective Twitter activity.
• Analyzing trends in user engagement: By plotting the data from this dataset over time, one can monitor changes in user engagement and start to uncover trending topics or conversations related to Charli D'Amelio's Tweets D’Amelio’s tweets.
• Identifying key influencers: By examining which users have had the most interaction with Charli D'Amelio's Tweets tweets (likes, replies, retweets), one can identify her biggest fans and most influential followers who may be key targets for any given influencer campaign or discussion related to her content

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Twitter.

About this Dataset

Influencer marketing campaigns: Brands can use the contact data of Indian content creators to reach out to them for influencer marketing campaigns. Influencers can create content for the brand, promote it on their social media channels, and help increase brand awareness and engagement.

Product reviews and sponsorships: Companies can use the contact data of Indian content creators to send them their products for review or to sponsor their content. This can help increase brand exposure and generate positive word-of-mouth for the product.

Brand partnerships and collaborations: Brands can use the contact data of Indian content creators to collaborate with them on brand partnerships. This can include creating co-branded content, sponsored posts, or joint events.

Content creation services: Companies can use the contact data of Indian content creators to hire them for content creation services. This can include creating social media posts, blog articles, videos, or other types of content.

Market research: Companies can use the contact data of Indian content creators to conduct market research. They can ask influencers to participate in surveys or focus groups to get insights into their target audience's preferences and behaviors.

Overall, the contact data of Indian content creators can be a valuable resource for companies and brands looking to leverage the power of influencer marketing and content creation.

Category

Social Media Audiences

Keywords

contact,influencers,marketing,sponsorship,collaboration

Row Count

2779

Price

$500.00

Privacy vs. Social Capital: Social Media PII Disclosure Analyses

This data was collected and analyzed as part of a study on PII disclosures in social media conversations with special attention to influencer characteristics in the interactions in the dissertation titled Privacy vs. Social Capital: Examining Information Disclosure Patterns within Social Media Influencer Networks and the research paper titled Unveiling Influencer-Driven Personal Data Sharing in Social Media Discourse.

Each study phase is different, with X (Twitter) data used in the pilot analysis and Reddit data used in the main study. Both folders will have the analyzed_posts and cluster summary csv files broken down by collection (either based on trend or collection date).

Note: Raw data is not made available in these datasets due to the nature of the study and to protect the original authors.

Notable Data Elements

Post Data

Cluster Data