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.

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 ...

As of October 2025, 6.04 billion individuals worldwide were internet users, which amounted to 73.2 percent of the global population. Of this total, 5.66 billion, or 68.7 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 2025. In the Netherlands, Norway, and Saudi Arabia, 99 percent of the population used the internet as of February 2025. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Eastern Asia was home to the largest number of online users worldwide—over 1.34 billion at the latest count. Southern Asia ranked second, with around 1.2 billion internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2024, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in African countries, with around a 10-percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller usage gap between these two genders. As of 2024, global internet usage was higher among individuals between 15 and 24 years old across all regions, with young people in Europe representing the most considerable usage penetration, 98 percent. In comparison, the worldwide average for the age group of 15 to 24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

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

This dataset was originally collected for a data science and machine learning project that aimed at investigating the potential correlation between the amount of time an individual spends on social media and the impact it has on their mental health.

The project involves conducting a survey to collect data, organizing the data, and using machine learning techniques to create a predictive model that can determine whether a person should seek professional help based on their answers to the survey questions.

This project was completed as part of a Statistics course at a university, and the team is currently in the process of writing a report and completing a paper that summarizes and discusses the findings in relation to other research on the topic.

The following is the Google Colab link to the project, done on Jupyter Notebook -

https://colab.research.google.com/drive/1p7P6lL1QUw1TtyUD1odNR4M6TVJK7IYN

The following is the GitHub Repository of the project -

https://github.com/daerkns/social-media-and-mental-health

Libraries used for the Project -

Pandas
Numpy
Matplotlib
Seaborn
Sci-kit Learn

this graphs was created in R and Ourdataworld:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F1ad74af652d524e84410babe6ac5fe61%2Fgraph1.png?generation=1711651132634613&alt=media" alt="">

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https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Ffea08aaf9fe8038659f6a081729f1bb2%2Fgraph3.gif?generation=1711651145884218&alt=media" alt="">

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Introduction:

The dawn of the internet era has heralded an unprecedented age of connectivity, transforming the way we live, communicate, and interact on a global scale. As of 2020, approximately 60% of the world's population had access to the internet, marking a significant milestone in the digital revolution. From facilitating seamless communication to enabling cross-border collaborations, the internet has become an indispensable tool in our daily lives. This essay explores the multifaceted impact of the internet across various domains, highlighting its role as a catalyst for global connectivity and innovation.

Communication and Collaboration:

One of the most profound implications of the internet is its ability to bridge geographical distances and facilitate instant communication. Platforms such as email, social media, and messaging apps have revolutionized how we interact with one another, transcending borders and time zones. Whether it's connecting with loved ones halfway across the globe or collaborating with colleagues on a project, the internet has made communication more accessible and efficient than ever before. Video conferencing tools have further enhanced remote collaboration, enabling teams to work seamlessly regardless of their physical location. As a result, businesses have embraced remote work models, unlocking new possibilities for flexibility and productivity.

Financial Inclusion and Remittances:

The internet has democratized access to financial services, empowering individuals to participate in the global economy irrespective of their location. Online banking, mobile payment apps, and digital wallets have revolutionized the way we manage our finances, offering convenience and security. Moreover, the internet has facilitated international money transfers, including remittances, which play a vital role in supporting families and economies worldwide. Platforms like PayPal, TransferWise, and Western Union have streamlined the process of sending and receiving money across borders, reducing transaction costs and increasing efficiency. This newfound accessibility to financial services has contributed to greater financial inclusion and economic empowerment, particularly in underserved communities.

Education and Knowledge Sharing:

The internet has democratized access to education, breaking down traditional barriers to learning and knowledge dissemination. Online courses, tutorials, and educational platforms have made quality education accessible to anyone with an internet connection. Whether it's acquiring new skills, pursuing higher education, or accessing resources for self-improvement, the internet offers a wealth of learning opportunities. Open educational resources (OERs) and Massive Open Online Courses (MOOCs) have revolutionized the way we approach education, fostering a culture of lifelong learning and skill development. Furthermore, online forums and communities provide avenues for knowledge sharing and collaboration, enabling individuals to learn from experts and peers across the globe. This democratization of education holds the promise of narrowing the digital divide and fostering global innovation and prosperity.

Cross-Border Social Connections:

The internet has transcended cultural and linguistic barriers, facilitating cross-border social connections and fostering a sense of global citizenship. Social media platforms have become virtual gathering spaces where people from diverse backgrounds can connect, share experiences, and engage in meaningful dialogue. Whether it's forming friendships with individuals from different countries or participating in online communities centered around shared interests, the internet has enriched our social interactions in unprecedented ways. Moreover, platforms like language exchange forums and cultural exchange programs promote intercultural understanding and empathy, bridging gaps between people of different nationalities and backgrounds. By facilitating cross-border social connections, the internet has the potential to foster a more inclusive and interconnected global comm...

Context

Social media are today a very popular way of exchanging information with other people via the Internet. It's hard not to notice that over the years new ones are created and old ones "die". The database below presents the popularity of various social networking sites since 2009, showing the percentage of their share in the social media market.

Content

The database saved in .csv form contains several columns. The first column contains the date (YYYY-MM) of the measurement period. Each subsequent column contains the percentage of share in the social media market, given as a percentage, rounded to 2 decimal places (if the share is less than 0.5%, the value 0 remains, even though it may constitute a very small percentage of the share). We have almost 180 rows, 15 years of data for monthly periods.

Source

The database comes from the Statcounter and is made available in the operation with CC BY-SA 3.0 license which allows to copy, use and disseminate data also for commercial purposes after providing the source.

According to Cognitive Market Research, the global Social Media Monitoring Tools market Size was USD 4854.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 8.00% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 1941.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.2% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1456.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.5% from 2024 to 2031.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 1116.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.0% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 242.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.4% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 97.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.7% from 2024 to 2031.
The Software/Platform category held the highest Social Media Monitoring Tools market revenue share in 2024.

Market Dynamics of Social Media Monitoring Tools Market

Key Drivers for Social Media Monitoring Tools Market

Growing cloud-based solution usage in enterprises to propel market growth

Cloud-based social media monitoring technologies provide scalable, adaptable, and affordable solutions for tracking, evaluating, and managing media material across several channels by utilizing cloud computing infrastructure. With the use of these systems, which track and analyze massive amounts of media information in real-time using sophisticated data processing, storage, and analytics capabilities, businesses may get useful insights into competition intelligence, market trends, and brand perception. Sentiment analysis, trend tracking, and influencer identification features are available in cloud-based media monitoring systems like Meltwater, Talkwalker, and Brandwatch. In light of this, the increasing acceptance of media monitoring tools to facilitate strategic decision-making and improve brand performance in the digital sphere is being driven by the expanding use of cloud-based solutions among organizations, which improve accessibility, cooperation, and scalability.

Increasing social media usage to propel market growth

The Social Media Monitoring Tools Market is expected to grow at an exponential rate due in large part to the rise in social media usage. In order to remain competitive, businesses must keep an eye on and analyze social media activities given the billions of users across platforms such as Facebook, Instagram, Twitter, and LinkedIn. With the use of these technologies, businesses can monitor industry trends, client feedback, and brand mentions instantly. There is a growing need for strong monitoring solutions as customers utilize social media more and more for reviews, recommendations, and conversations. Businesses may improve customer service, manage reputational issues, and improve marketing tactics with the help of this boom in social media interaction, which offers great data. This means that as more people use social media, the market for social media monitoring tools is expanding due to the technologies' increased usage and innovation.

Restraint Factor for the Social Media Monitoring Tools Market

Data security and privacy issues to hinder market growth

The market for social media monitoring tools is growing slowly due to concerns about data security and privacy. Adoption of these tools may be constrained by the complicated compliance requirements imposed by regulations such as the CCPA and GDPR. Concerning breaches and misuse, users become more cautious about the way their data is gathered, stored, and used. Social media monitoring tools need to have strong security measures in place to secure user data due to their gather and examine huge quantities of private and sensitive data. Some firms are discouraged from fully utilizing these tools due to the possibility of data breaches or penalties for noncompliance. In order to establish compliance, assure trust, and promote wider adoption and use of soci...

Social Media Disaster-Related Discussions

Detecting Relevant Content with Trusted Judgments

By CrowdFlower [source]

About this dataset

Welcome to the disaster tweets dataset! This collection of tweets holds a wealth of information about global disasters and their effects on people, governments, and organizations all over the world. With over 10,000 tweets collected and carefully annotated with labels of whether they reported an actual disaster or not, this dataset provides unique insight into what these events look like in terms of social media conversations.

This information is derived from a variety of key terms related to disaster events, such as “ablaze” and “pandemonium” which was used to gather each individual tweet for analysis. The columns for each tweet include detailed metadata about the user who posted it along with variables such as keyword relevance and location. Alongside all these attributes is the core text belonging to each individual tweet- giving you access to all sorts of stories from natural disasters, contagious disease outbreaks or conflicts between nations that can be found in one place!

So whatever you're looking for - whether it's observations about first-hand accounts or conducting research on public sentiment during a major event - this dataset offers you an invaluable source full of timely information that could potentially save lives down the line. So take your journey through this data now and embark upon discovering what devastation looks like through social media!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset contains tweets related to disaster events, including the keyword, location, text, tweetid and userid. It provides insights into how people interact with each other on social media during a disaster. Using this dataset you can gain valuable insight into the dynamics of online communication in disasters and provide an important point of reference for future disaster management initiatives.

Research Ideas

• Analyzing the effectiveness of disaster relief and humanitarian aid efforts, by mapping tweets against public data of areas affected by disasters and donations made to help those affected.
• Developing advanced statistical models to predict the magnitude and impact of an oncoming natural disaster using keyword analysis in social media posts related to past disasters.
• Creating text-based classifiers to accurately detect disaster-related tweets in real-time, allowing emergency services providers early warning signs before a potential event occurs

Acknowledgements

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

License

Unknown License - Please check the dataset description for more information.

Columns

File: socialmedia-disaster-tweets-DFE.csv | Column name | Description | |:-----------------------|:-----------------------------------------------------------------------------------| | _golden | A boolean value indicating whether the tweet is a golden tweet or not. (Boolean) | | _unit_state | The state of the tweet (e.g. finalized, judged, etc.). (String) | | _trusted_judgments | The number of trusted judgments for the tweet. (Integer) | | _last_judgment_at | The date and time of the last judgment for the tweet. (DateTime) | | choose_one | The label assigned to the tweet (e.g. relevant, not relevant, etc.). (String) | | choose_one_gold | The gold label assigned to the tweet (e.g. relevant, not relevant, etc.). (String) | | keyword | The keyword associated with the tweet. (String) | | location | The location associated with the tweet. (String) | | text | The text content of the tweet. (String) |

Acknowledgements

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

Twitter is ranked as the 12h most popular social media site in the world. The platform currently has 611 million active monthly users.

Context

With roughly 2.89 billion monthly active users as of the second quarter of 2021, Facebook is the biggest social network worldwide. In the third quarter of 2012, the number of active Facebook users surpassed one billion, making it the first social network ever to do so. Active users are those who have logged into Facebook during the past 30 days. During the first quarter of 2021, the company stated that 3.51 billion people were using at least one of the company's core products (Facebook, WhatsApp, Instagram, or Messenger) each month.

Content

This data was collected by Facebook and was released in July 2021.

At 2:13 a.m., Ellie turned off her phone after endlessly scrolling through Instagram Reels. This wasn’t the first time she traded sleep for screen time, and like millions of others, she would wake up tired, groggy, and mentally foggy. In 2025, this silent epidemic of sleep disruption linked to social...

NEW UPDATE:

Show your skills off in the Social Media Extremism Challenge @ https://www.kaggle.com/competitions/social-media-extremism-detection-challenge! Try your luck at tackling this challenging classification problem! After the competition is completed, we will be adding 200+ hand-labelled entries to this dataset so stay tuned!

We would like to thank Assistant Professor Leilani H. Gilpin (UC Santa Cruz) and the AIEA Lab for their guidance and support in the development of this dataset. —*Aditya Suresh, Anthony Lu, Vishnu Iyer*

About this data: Social media has seen an increasing rise in the quantity and intensity of extremist content throughout various different services. With cases such as the various different white supremacist movements across the world, recruitment for terrorist organizations through affiliated accounts, and a general sense of hate emerging through the modern era of polarization, it becomes increasingly vital to be able to recognize these patterns and adequately combat the harms of extremism digitally on a global scale.

Citations: Our dataset would not have been possible without the aid of an already preexisting dataset found on Kaggle, Version 1 of "Hate Speech Detection curated Dataset🤬" by Alban Nyantudre in 2023. The link can be found here: https://www.kaggle.com/datasets/waalbannyantudre/hate-speech-detection-curated-dataset/data. Accessed in 2025, it was truly essential to our work. With over 400,000 messages of real, cleaned posts, we would not have been able to source and label our data points without this crucial resource.

Classification: Our team hand labelled nearly 3,000 pieces of data from our sourced database of posts, filtering every on of them into a blanket tag of "EXTREMIST" and "NON_EXTREMIST." As many messages digitally utilize context in order to spread harmful rhetoric, we followed a general rule of classifying terms as extremist so long as they "provoked harm to a person or a group of people, whether it be through advocacy for violence, discrimination, or other hurtful sentiments, based off of a characteristic of the group."

Value of the data: This dataset can be utilized to create extremist sentiment analysis systems and machine learning algorithms, as it reflects on current linguistics, as stated by the source material for the data points themselves. In addition, it can be used as a benchmark for comparing with other extremism datasets and other extremist sentiment analysis systems.

Potential Errors: Although we feel very confident in our own labeling ability, a possibility of potentially wrong data points does exist due to the fact that these data points lack quantifiable identifiers and as such human errors are possible within the data. We do not believe this to occur often, but in full transparency is an issue that we endeavor to resolve in subsequent updates.

In 2008, the average human attention span was 12 seconds. Fast forward to 2025, and many studies suggest it's now hovering around 8 seconds, shorter than that of a goldfish. It’s no coincidence that during this same period, social media platforms surged to dominate how we consume content. Whether you're...

According to Cognitive Market Research, the global Social Commerce Market size was USD 769485.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 32.20% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 307794.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 30.4% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 230845.56 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 176981.60 million in 2024 and will grow at a compound annual growth rate (CAGR) of 34.2% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 38474.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 31.6% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 15389.70 million in 2024 and will grow at a compound annual growth rate (CAGR) of 31.9% from 2024 to 2031.
The business to consumer (B2C) held the highest Social Commerce Market revenue share in 2024.

Market Dynamics of Social Commerce Market

Key Drivers for Social Commerce Market

The rise of social media is driving the growth of social commerce: The growth of social commerce is heavily influenced by the rise of social media and its increased usage on mobile devices. Social media platforms such as Facebook, Instagram, TikTok and WhatsApp have become major hubs for online shoppers. Customers are more likely to find and buy products directly from social media platforms than from traditional e-commerce websites since they spend more time on these channels.

For instance,

 5.24 billion use social media worldwide, as of January, 2025.Facebook remains to be the leading social media platform with over 3 billion monthly active users, followed by YouTube with 2.5 billion and Instagram with 2 billion monthly active users.
90% of consumers rely on social media to keep up with trends and cultural moments and nearly half of them interact with brands more often on social media platforms. 

(Source: https://backlinko.com/social-media-users)

https://sproutsocial.com/insights/social-media-statistics/#social-media-usage-statistics)

Advancements in Technology to Propel Market Growth: The Social Commerce Market has witnessed steady growth, driven by advancements in technology. Mobile technology has advanced significantly over the last ten years, and smartphones are now an essential part of people's everyday lives. Users are increasingly choosing to shop straight from their smartphones because to improved smartphone capabilities and internet connectivity, which has expanded mobile commerce. Additionally, more people are using smartphones due to rising disposable incomes, which ultimately enhances the social commerce market value environment.

Key Restraint for the Social Commerce Market

Growing concerns around data privacy restrict market growth: Concerns regarding privacy are hindering the expansion of social commerce, as individuals are reluctant to disclose financial or personal information on various platforms. The apprehension surrounding data breaches and potential misuse diminishes trust and affects transaction volumes. It is imperative for companies to implement secure and transparent practices in order to maintain user confidence and adhere to the growing data protection regulations globally.

Key Trends for the Social Commerce Market

The Emergence of Live Shopping and Influencer Commerce: Live shopping and promotions led by influencers are revolutionizing social media platforms into dynamic marketplaces. Consumers are increasingly placing their trust in the product reviews and recommendations provided by creators, which enhances both engagement and conversion rates. This phenomenon is particularly evident on TikTok and Instagram, where influencers conduct interactive shopping events that are directly connected to in-app purchasing.

AI-Enhanced Personalization and Intelligent Chatbots: Social commerce platforms are utilizing artificial intelligence to offer tailored product suggestions and efficient customer support. Intelligent chatbots deliver immediate assistance, thereby enhan...

📊 About the Dataset

This dataset explores the influence of AI-generated content across various industries, including journalism, social media, entertainment, and marketing. It provides insights into public sentiment, engagement trends, economic impact, and regulatory responses over time.

With AI-generated content becoming increasingly prevalent, this dataset serves as a valuable resource for data analysts, business strategists, and machine learning researchers to study trends, detect biases, and predict future AI adoption patterns.

💡 This dataset is perfect for AI adoption analysis, industry forecasting, and ethical AI research!

Social media are widely used by young people (YP), but how YP with language disorders use social media for social interaction remains insufficiently studied. This article provides an overview of the research on social media use by YP with language disorders. A scoping review was conducted, guided by a five-stage framework. Ten databases were searched (CENTRAL, CINAHL, ERIC, LLBA, Medline, PsychINFO, Scopus, speechBITE, Web of Science, ProQuest Dissertations & Theses Global). Chaining searches of papers identified for inclusion were conducted. After screening 199 unique papers, 44 were included. Findings revealed that YP with language disorders use social media less compared to typically developing peers; their profile of communication difficulties may impact the types of social media with which they engage. Although intervention studies are limited, the results offer encouraging findings regarding the positive impact of support for use of social media. Barriers and facilitators for social media use are identified. YP with language disorders use social media for social purposes. However, co-designed research into what YP with language disorders perceive their social media needs to be is urgently needed. How to support YP with language disorders to use social media is subject to future investigation. Young people with language disorders are likely using a range of social media to support their social participation, but they use social media less than typically developing peers.The types of social media young people with language disorders choose to engage with may be impacted by their language/literacy difficulties.There is preliminary evidence that intervention to support the use of social media by young people with language disorders is beneficial, but more research is required to identify the components to include in social media use training programs.To support the access to and use of social media by young people with language disorders, healthcare professionals may need to collaborate with parents and schools. Young people with language disorders are likely using a range of social media to support their social participation, but they use social media less than typically developing peers. The types of social media young people with language disorders choose to engage with may be impacted by their language/literacy difficulties. There is preliminary evidence that intervention to support the use of social media by young people with language disorders is beneficial, but more research is required to identify the components to include in social media use training programs. To support the access to and use of social media by young people with language disorders, healthcare professionals may need to collaborate with parents and schools.

The dataset contains detailed information on some of the most popular English media channels on Youtube. From channel overview to statistics of the top 50 videos of each channel, here is a description of all the columns of the two datasets.

Mainstream Media Statistics

1. channelName: name of the channel on Youtube
2. id: The channel ID in Youtube
3. subscribers: subscriber count (up till 14/7/2023)
4. total views: total views of all the videos of the channel (up till 14/7/2023)
5. total videos: total number of videos of the channel (up till 14/7/2023)
6. created date: The date where the channel is created
7. description: description of the channel in their description page
8. playlistId: The id of the channel's video list

Top50_viewed_video_from_each_channels

1. Video Id: The ID of the video on Youtube
2. Channel Title: The channel name of the video
3. Title: Title of the video
4. publishedAt: When the video is published
5. categoryId: The category ID of Youtube (You may reference at https://mixedanalytics.com/blog/list-of-youtube-video-category-ids/)
6. description: The description of the video
7. viewCount: The total number of views of that video (up till 14/7/2023)
8. likeCount: The total number of likes of that video (up till 14/7/2023)
9. commentCount: The total number of comments of that video (up till 14/7/2023)
10. duration: The duration of that video

Inspirations

Data is scraped using Youtube API, feel free to use the data as long as it copes with the term of uses of Youtube. Something you can do with the dataset may be to analysis what news are of people's interest or to watch some of the most viewed news in the world to stay close with the society.

Context

As part of a capstone project, we wanted to compare what social media users are talking about to what's going on in the world to see if and how social media users care about news events. We scraped data from Twitter, Reddit, reliable news sources, and Google Trending Topics.

Content

This data set includes nine tables: Twitter, news, Google Trending Topics, and six popular subreddits (news, worldnews, upliftingnews, sports, politics, television).

Twitter: trending topic, date trending, sentiment analysis scores, most common word associated with the trend, most common pairs of words associated with the trend.

News: headlines (collected from BBC News, USA Today, and the Washington Post), date the article was posted.

Google Trending Topics: trending topic, date trending.

Subreddits: post title, time, date, score (upvotes - downvotes), number of comments.

Acknowledgements

This data was collected as part of a semester project in the Capstone in Social Network Analytics at Virginia Tech, Spring 2017, taught by Siddharth Krishnan. The data was collected over a period of eight days in April 2017.

Inspiration

What do social media users care about, and in what ways do they care? What may they not know about? What types of trends appear most on each social media platform? Are people who get the majority of their news from social media able to get an accurate and comprehensive idea of what is going on? How can algorithms such as Twitter’s trending topics algorithm influence and shape what users talk about, read, and react to?

According to Cognitive Market Research, the global Online Advertising market size was USD 236.90 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 15.7% from 2024 to 2031. Market Dynamics of Online Advertising Market

Key Drivers for Online Advertising Market

Increasing internet and smartphone penetration is driving growth in the online advertising market

One of the most significant drivers of growth in the online advertising market is increasing internet penetration and the rising usage of mobile phones, due to growing digital dependency. With over 7 billion people worldwide using mobile phones, smartphones have become an essential part of daily life. This surge in mobile connectivity has transformed consumer behavior with individuals increasingly relying on smartphones for daily activities like shopping, entertainment and financial transactions. The convenience and portability of mobile devices have them a preferred medium for tapping into digital services which has led businesses to adopt mobile-first strategies to engage with consumers. This shift has led to an increase in mobile ad spending. Advertisers are no focusing on campaigns designed for smaller screens and shorter attention spans to reach a wider audience.

Advertisers are responding to this trend with mobile-first strategies, using vertical format videos, personalized in-app ads and location-based targeting to maximize engagement. The combination of high-screen time, constant connectivity, and real time data access makes mobile advertising one of the most effective tools in the global online advertising market.

Social Media Influence is fueling growth for online advertising

Social media platforms have become prominent channels of advertising, allowing business to reach specific target audiences and promote their products and services. Social media platforms such as Facebook, Instagram, Twitter have become major hubs for online advertising.

The rise of in-app advertising across these platforms with the growing popularity of video and interactive ad formats has further fueled the market growth. Such advertising also leverages data to optimize targeting and engagement, leading to more effective campaigns. Paid ads now dominate social feeds.

Key Restraints in the Market

Data privacy concerns to hinder growth in online advertising market

Mobile phones and other internet using devices have become a personal hub for information. With the increasing amount of sensitive data stored on these devices, privacy concerns have emerged as one of the most pressing issues. These concerns significantly hinder online advertising by leading to consumer distrust, ad avoidance and increased regulations that impact the effectiveness and reach of ad campaigns.

Consumers are becoming more aware of how their data is being collected and used under the context of online advertising, making them actively avoid interacting with ads and uninstalling apps they believe violate their privacy. This has also led to widespread adoption of ad-blocking technologies. This trend is largely driven by the growing desire to protect personal data. However, the same has had implications on advertisers. Regulatory development, such as the California Consumer Privacy Act, amid these concerns further add to the challenges faced by the mobile industry market. Strict data privacy laws have been implemented worldwide against the collection and use of consumer data for targeted advertising.

Opportunity

Adoption of AI as an opportunity in the mobile advertising industry

The adoption of artificial intelligence (AI) presents an opportunity for the online advertising segment by enhancing various tasks such as, campaign optimization audience targeting, creative component generation and so much more. AI-powered tools are automating tasks, enabling precise targeting and more personalized user experience, ultimately leading to effective and efficient advertising

For instance, AI powered creatives and copy ideation and generation are a game-changer in the mobile advertising landscape. The integration of AI into ad creation helps streamline the process along with enabling advertisers to conduct thorough testing. Introduction of the Online Advertising Market

Online advertising, otherwise known as digital marketing is a form of marketing that uses internet or online channels to promote products and services. It involves the creation ...