This dataset provides detailed rankings and key metrics for 100+ social media platforms and sites in 2025. It includes information such as user base, popularity trends, and global reach. Ideal for analyzing social media growth, user engagement, and market trends. Whether you're a data scientist, marketer, or researcher, this dataset offers valuable insights into the evolving digital landscape.

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 ...

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.

Market leader Facebook was the first social network to surpass one billion registered accounts and currently sits at more than three billion monthly active users. Meta Platforms owns four of the biggest social media platforms, all with more than one billion monthly active users each: Facebook (core platform), WhatsApp, Messenger, and Instagram. In the third quarter of 2023, Facebook reported around four billion monthly core Family product users. The United States and China account for the most high-profile social platforms Most top-ranked social networks with more than 100 million users originated in the United States, but services like Chinese social networks WeChat, QQ, or video-sharing app Douyin have also garnered mainstream appeal in their respective regions due to local context and content. Douyin’s popularity has led to the platform releasing an international version of its network, TikTok. How many people use social media? The leading social networks are usually available in multiple languages and enable users to connect with friends or people across geographical, political, or economic borders. In 2025, social networking sites are estimated to reach 5.44 billion users, and these figures are still expected to grow as mobile device usage and mobile social networks increasingly gain traction in previously underserved markets.

1) Data Introduction • The Social Media Usage Dataset(Applications) features patterns and activity indicators that 1,000 users use seven major social media platforms, including Facebook, Instagram, and Twitter.

2) Data Utilization (1) Social Media Usage Dataset(Applications) has characteristics that: • This dataset provides different social media activity data for each user, including daily usage time, number of posts, number of likes received, and number of new followers. (2) Social Media Usage Dataset(Applications) can be used to: • Analysis of User Participation by Platform: You can analyze participation and popular trends by platform by comparing usage time and activity for each social media. • Establish marketing strategy: Based on user activity data, it can be used for targeted marketing, content production, and user retention strategies.

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.

Over the five years through 2025-26, industry revenue is forecast to expand at a compound annual rate of 20.3% to reach £12.5 billion. Social media platforms are integral to people's lives, offering ways to communicate, create and view content and share information. According to Ofcom, approximately 89% of UK internet users in 2023 used social media apps or sites. Teenagers and young adults are the biggest users. Advertising is the primary revenue source for social media platforms, although subscription-based services are gaining momentum as platforms seek to diversify their incomes. TikTok is the success story of the past five years, becoming the most downloaded app between 2020 and 2022, according to Apptopia. The short-form video platform has over 30 million monthly users in the UK in 2025. After Musk's takeover, X, formerly known as Twitter, adjusted its content moderation and allowed previously banned accounts to return. As a result, over 600 advertisers pulled their ads from the site because of fears their brand may be associated with malcontent. In response to falling ad revenue, X has introduced a subscription-based service which enables users to verify themselves and boosts the number of people who view their tweets. Meta-owned Facebook and Instagram have responded by introducing a similar service. In 2025, more social media platforms are using AI to boost user engagement. This improves click-through rates and drives higher advertising revenue. Industry revenue is expected to grow by 6.3% in 2025-26. Over the five years through 2030-31, social media platforms' revenue is projected to climb at an estimated 9.2% to reach £19.4 billion. Regulations relating to how data is collected, stored, and shared will force advertisers and platforms to rethink how they can target their desired demographics. The tightening of regulations will raise industry compliance costs, weighing on profit margin. Older age groups present a new revenue opportunity for social media platforms if they can bridge the gap between passive TV consumption and interactive digital engagement. Augmented Reality (AR) technology will move beyond filters to become standard for immersive product trials, interactive ads, and virtual meetups

The number of Twitter users in the United States was forecast to continuously increase between 2024 and 2028 by in total 4.3 million users (+5.32 percent). After the ninth consecutive increasing year, the Twitter user base is estimated to reach 85.08 million users and therefore a new peak in 2028. Notably, the number of Twitter users of was continuously increasing over the past years.User figures, shown here regarding the platform twitter, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Twitter users in countries like Canada and Mexico.

Dataset

This dataset was created by Jigyashu Singh Lodhi

Released under Other (specified in description)

Contents

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

This dataset provides detailed daily records of social media follower growth for multiple brands across major platforms, including engagement rates, campaign activity, ad spend, and top-performing content. It empowers marketing teams to analyze the impact of campaigns, content strategies, and paid promotions on follower growth, enabling data-driven optimization and benchmarking.

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! 🌍

Please cite this paper when using this dataset: N. Thakur, “Mpox narrative on Instagram: A labeled multilingual dataset of Instagram posts on mpox for sentiment, hate speech, and anxiety analysis,” arXiv [cs.LG], 2024, URL: https://arxiv.org/abs/2409.05292Abstract: The world is currently experiencing an outbreak of mpox, which has been declared a Public Health Emergency of International Concern by WHO. During recent virus outbreaks, social media platforms have played a crucial role in keeping the global population informed and updated regarding various aspects of the outbreaks. As a result, in the last few years, researchers from different disciplines have focused on the development of social media datasets focusing on different virus outbreaks. No prior work in this field has focused on the development of a dataset of Instagram posts about the mpox outbreak. The work presented in this paper (stated above) aims to address this research gap. It presents this multilingual dataset of 60,127 Instagram posts about mpox, published between July 23, 2022, and September 5, 2024. This dataset contains Instagram posts about mpox in 52 languages.For each of these posts, the Post ID, Post Description, Date of publication, language, and translated version of the post (translation to English was performed using the Google Translate API) are presented as separate attributes in the dataset. After developing this dataset, sentiment analysis, hate speech detection, and anxiety or stress detection were also performed. This process included classifying each post intoone of the fine-grain sentiment classes, i.e., fear, surprise, joy, sadness, anger, disgust, or neutralhate or not hateanxiety/stress detected or no anxiety/stress detected.These results are presented as separate attributes in the dataset for the training and testing of machine learning algorithms for sentiment, hate speech, and anxiety or stress detection, as well as for other applications.The 52 distinct languages in which Instagram posts are present in the dataset are English, Portuguese, Indonesian, Spanish, Korean, French, Hindi, Finnish, Turkish, Italian, German, Tamil, Urdu, Thai, Arabic, Persian, Tagalog, Dutch, Catalan, Bengali, Marathi, Malayalam, Swahili, Afrikaans, Panjabi, Gujarati, Somali, Lithuanian, Norwegian, Estonian, Swedish, Telugu, Russian, Danish, Slovak, Japanese, Kannada, Polish, Vietnamese, Hebrew, Romanian, Nepali, Czech, Modern Greek, Albanian, Croatian, Slovenian, Bulgarian, Ukrainian, Welsh, Hungarian, and Latvian.The following is a description of the attributes present in this dataset:Post ID: Unique ID of each Instagram postPost Description: Complete description of each post in the language in which it was originally publishedDate: Date of publication in MM/DD/YYYY formatLanguage: Language of the post as detected using the Google Translate APITranslated Post Description: Translated version of the post description. All posts which were not in English were translated into English using the Google Translate API. No language translation was performed for English posts.Sentiment: Results of sentiment analysis (using the preprocessed version of the translated Post Description) where each post was classified into one of the sentiment classes: fear, surprise, joy, sadness, anger, disgust, and neutralHate: Results of hate speech detection (using the preprocessed version of the translated Post Description) where each post was classified as hate or not hateAnxiety or Stress: Results of anxiety or stress detection (using the preprocessed version of the translated Post Description) where each post was classified as stress/anxiety detected or no stress/anxiety detected.All the Instagram posts that were collected during this data mining process to develop this dataset were publicly available on Instagram and did not require a user to log in to Instagram to view the same (at the time of writing this paper).

During a 2025 survey among marketers worldwide, around 83 percent reported using Facebook for marketing purposes. Instagram and LinkedIn followed, respectively mentioned by 78 and 69 percent of the respondents. The global social media marketing segment According to the same study, 60 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 2025. 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.

These datasets consist of qualitative data collected through semi-structured in-depth interviews as well as a focus group from three different companies with seven industry experts.The data collected was to address the use of social media to enhance organisational learning and also to address the gap that exists in terms of the integration of organisational learning (OL) and social media and also address the lack of guidelines for organisations that would like to implement the use of social media to facilitate OL. The data were triangulated by comparing the results from the three companies.

Tiktok network graph with 5,638 nodes and 318,986 unique links, representing up to 790,599 weighted links between labels, using Gephi network analysis software. Source of: Peña-Fernández, Simón, Larrondo-Ureta, Ainara, & Morales-i-Gras, Jordi. (2022). Current affairs on TikTok. Virality and entertainment for digital natives. Profesional De La Información, 31(1), 1–12. https://doi.org/10.5281/zenodo.5962655 Abstract: Since its appearance in 2018, TikTok has become one of the most popular social media platforms among digital natives because of its algorithm-based engagement strategies, a policy of public accounts, and a simple, colorful, and intuitive content interface. As happened in the past with other platforms such as Facebook, Twitter, and Instagram, various media are currently seeking ways to adapt to TikTok and its particular characteristics to attract a younger audience less accustomed to the consumption of journalistic material. Against this background, the aim of this study is to identify the presence of the media and journalists on TikTok, measure the virality and engagement of the content they generate, describe the communities created around them, and identify the presence of journalistic use of these accounts. For this, 23,174 videos from 143 accounts belonging to media from 25 countries were analyzed. The results indicate that, in general, the presence and impact of the media in this social network are low and that most of their content is oriented towards the creation of user communities based on viral content and entertainment. However, albeit with a lesser presence, one can also identify accounts and messages that adapt their content to the specific characteristics of TikTok. Their virality and engagement figures illustrate that there is indeed a niche for current affairs on this social network.

Despite a tumultuous 2018, Facebook is still the top social network in the United States, with 169.76 million mobile users accessing the Facebook app in September 2019. The company’s other properties Instagram and Facebook Messenger ranked second and third with 121 and 106 million users respectively. Cambridge Analytica scandal 2018 The biggest social media company in the world had a difficult 2018. The platform has long been accused of enabling the spread of fake news during the 2016 election and beyond. One of the first and biggest negative Facebook stories of 2018 was the Cambridge Analytica scandal, which unfolded from March 2018. The Guardian, The Observer, and The New York Times simultaneously reported on political data firm Cambridge Analytica harvesting data of millions of Facebook users worldwide without their knowledge before the 2016 election, which led to Facebook CEO Mark Zuckerberg having to testify before Congress in April 2018. Facebook usage behavior changes Due to the revelations about Facebook and the company’s treatment of private user data, many U.S. users are planning to use the social network much less and to be much more careful about what they post . During an April 2018 survey, only 20 percent of respondents stated that their Facebook usage has not changed, and they were planning on continuing to use the social platform as much as they always had in the past.

The number of Reddit users in the United States was forecast to continuously increase between 2024 and 2028 by in total 10.3 million users (+5.21 percent). After the ninth consecutive increasing year, the Reddit user base is estimated to reach 208.12 million users and therefore a new peak in 2028. Notably, the number of Reddit users of was continuously increasing over the past years.User figures, shown here with regards to the platform reddit, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once. Reddit users encompass both users that are logged in and those that are not.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Reddit users in countries like Mexico and Canada.

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Social Media Analytics Market Size 2025-2029

The social media analytics market size is forecast to increase by USD 21.2 billion, at a CAGR of 35.2% between 2024 and 2029.

The market is experiencing significant growth, driven by the expanding availability and complexity of social media data. Businesses increasingly recognize the value of social media insights to inform marketing strategies, enhance customer engagement, and gauge brand reputation. In response, social media platforms continue to roll out advanced targeting options, enabling more precise audience segmentation and personalized messaging. However, the surging use of social media data also presents challenges. Interpreting unstructured data from various sources remains a formidable task, requiring sophisticated analytics tools and expertise.
Companies must navigate these complexities to effectively harness the power of social media analytics and stay competitive in today's digital landscape. To succeed, organizations need to invest in advanced analytics solutions, cultivate data literacy skills, and establish clear data governance policies. By addressing these challenges, businesses can unlock valuable insights from social media data and capitalize on emerging opportunities in this dynamic market.

What will be the Size of the Social Media Analytics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, offering valuable insights for businesses across various sectors. Hashtag tracking and sentiment classification help organizations understand public perception and engagement with their brand. Engagement metrics, share of voice, and trend analysis algorithms provide valuable data for brand reputation management and customer journey mapping. Social media ROI, influencer marketing metrics, and sentiment scoring offer insights into the effectiveness of advertising campaigns. User behavior patterns, predictive modeling, and anomaly detection enable businesses to anticipate trends and respond to crises in real-time. Social media listening, lead generation attribution, influencer identification, and customer satisfaction scores provide actionable insights for community management and crisis communication management.

Data visualization dashboards and social listening tools facilitate effective audience segmentation and conversational AI. Reach forecasting, content performance, keyword analysis, and campaign effectiveness metrics offer valuable insights for optimizing social media strategies. Platform-specific insights enable businesses to tailor their approach to each social media channel. According to recent market research, the market is expected to grow by over 15% annually, reflecting the increasing importance of social media data for businesses. For instance, a retail company used social media listening tools to monitor customer conversations and identified a trend in customer complaints about product packaging. The company responded by redesigning the packaging, resulting in a 12% increase in sales.

This example highlights the potential impact of social media analytics on business performance.

How is this Social Media Analytics Industry segmented?

The social media analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Retail
  Government
  Media and entertainment
  Travel
  Others


Application

  Sales and marketing management
  Customer experience management
  Competitive intelligence
  Risk management
  Public safety and law enforcement


Deployment

  On-premises
  Cloud


Type

  Predictive analytics
  Prescriptive analytics
  Descriptive analytics
  Diagnostics analytics


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By End-user Insights

The retail segment is estimated to witness significant growth during the forecast period.

Social media analytics plays a pivotal role in retail marketing, enabling businesses to track and analyze customer engagement, sentiment, and trends in real-time. Tools such as hashtag tracking, sentiment classification, and engagement metrics help retailers understand their audience's preferences and behavior patterns. Share of voice and trend analysis algorithms provide insights into market dynamics and brand reputation management. Customer journey mapping and social media ROI measurement allow businesses to optimize their marketing strategies and improve sales. Influencer marketing metrics, sentiment scoring, and advertising campai

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...