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Global Social Networking Services market size 2025 was XX Million. Social Networking Services Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.
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Global Social Media Platforms market size is expected to reach $3317.86 billion by 2029 at 34.8%, segmented as by social networking, general social networks (facebook, linkedin), niche social networks
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The global social networking services (SNS) market is experiencing robust growth, driven by increasing internet and smartphone penetration, particularly in emerging economies. The market, estimated at $200 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated $700 billion by 2033. This expansion is fueled by several key trends, including the rise of short-form video platforms like TikTok and YouTube, the increasing integration of social media with e-commerce, and the ongoing development of sophisticated algorithms that personalize user experiences. The market segmentation reveals significant opportunities across diverse application areas, such as photo sharing, video streaming, online music, and business networking. While the general social networking services segment currently dominates, specialized platforms catering to niche interests show strong growth potential. Key players like Facebook, Twitter, Tencent, and TikTok are fiercely competitive, driving innovation and market consolidation. Geographic growth is largely concentrated in Asia-Pacific and other rapidly developing regions, though North America and Europe remain substantial markets. However, challenges exist, including data privacy concerns, the spread of misinformation, and increasing regulatory scrutiny, which could potentially restrain market growth to some degree. The competitive landscape is highly dynamic, with established players continuously adapting to emerging trends and new entrants vying for market share. The increasing demand for interactive and personalized social media experiences is pushing innovation in areas such as augmented reality (AR) and virtual reality (VR) integration, creating new avenues for growth. Furthermore, the integration of social networking services with other digital platforms, like e-commerce and online gaming, creates synergistic opportunities. The market's future growth hinges on addressing the concerns surrounding data security, misinformation, and ethical considerations, while simultaneously capitalizing on the evolving technological landscape and the increasing demand for connectedness. Understanding the evolving user preferences and leveraging advanced analytics will be crucial for success in this competitive market.
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.
As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.
Teens and social media
As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.
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I’ve compiled a list of the latest social media user statistics showing just how big social media has become and where it’s likely to go in the future.
Which county has the most Facebook users?
There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.
Facebook – the most used social media
Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.
Facebook usage by device
As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.
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Participants for this study were recruited from three general elective courses in a university in Shandong Province. Participants were required to complete four questionnaire measurements, each approximately one month (4 weeks) apart. The initial measurement involved 198 participants, with a few students dropping out during the following three measurements. Ultimately, only data from participants who completed all four measurements were retained, resulting in a total of 194 participants. Descriptive statistics were computed using SPSS 18.0, while cross-lagged model analysis was performed using Amos 24.0.
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Global ad spend were expected to reach over $134 billion in 2022. This means that it has increased by over 17% yearly.
As of September 2023, YouTube as the most popular social media platform for global users, with 97 percent of respondents reporting to use the popular video platform. YouTube was also the most popular social media among Gen Z users, with 96 percent of respondents in this age group reporting to have used the video platform as of the examined period. Facebook's usage kept steady among among the general digital population, with around eight in 10 reporting to have used the platform. In comparison, the social media's popularity was in free fall among gen Z users with only four in 10 among those surveyed reporting to engage with the Meta-powered platform.
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Gowalla is a location-based social networking website where users share their locations by checking-in. The friendship network is undirected and was collected using their public API, and consists of 196,591 nodes and 950,327 edges. We have collected a total of 6,442,890 check-ins of these users over the period of Feb. 2009 - Oct. 2010.
Brightkite was once a location-based social networking service provider where users shared their locations by checking-in. The friendship network was collected using their public API, and consists of 58,228 nodes and 214,078 edges. The network is originally directed but we have constructed a network with undirected edges when there is a friendship in both ways. We have also collected a total of 4,491,143 checkins of these users over the period of Apr. 2008 - Oct. 2010.
Stanford Network Analysis Platform (SNAP) is a general purpose, high performance system for analysis and manipulation of large networks. Graphs consists of nodes and directed/undirected/multiple edges between the graph nodes. Networks are graphs with data on nodes and/or edges of the network.
The core SNAP library is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. Besides scalability to large graphs, an additional strength of SNAP is that nodes, edges and attributes in a graph or a network can be changed dynamically during the computation.
SNAP was originally developed by Jure Leskovec in the course of his PhD studies. The first release was made available in Nov, 2009. SNAP uses a general purpose STL (Standard Template Library)-like library GLib developed at Jozef Stefan Institute. SNAP and GLib are being actively developed and used in numerous academic and industrial projects.
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IntroductionAdolescents are in the transitional stage from childhood to adulthood, a critical period for individual physical and mental development. With the rapid development of the Internet, social networking has become an integral part of adolescents’ daily lives. However, the information that adolescents are exposed to on social networks is often processed and embellished, which may cause them to become physically dissatisfied and lead to emotional problems, such as depression. We investigated the chain-mediating effects of self-objectification and body satisfaction on the relationship between social network use and depression.MethodsWe utilized questionnaire data of 2025 adolescents from two secondary schools and one high school in China.ResultsOur results demonstrated that (1) there are obvious sex differences in the intensity of social network use and active and passive social network use among adolescents, with usage higher among girls than for boys; (2) self-objectification and body satisfaction play a mediating role in the relationship between the intensity of social network use and adolescent depression, as well as the presence of chain-mediating roles; and (3) self-objectification and body satisfaction play an intermediary role in the relationship between active and passive social network use and adolescent depression; there is further a chain intermediary role. The findings suggest that social network use affects adolescents’ depression through self-objectification and body satisfaction, which is not only manifested in the general use intensity of social networks but also in their active and passive use modes of social networks.ConclusionThis study provides theoretical support for the causes and mechanisms behind the influence of social network use on adolescent depression and has practical implications for the prevention and intervention of adolescent emotional problems.
How much time do people spend on social media? As of 2025, the average daily social media usage of internet users worldwide amounted to 141 minutes per day, down from 143 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 3 hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just 2 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.
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Which countries spent the most and least time on social media?
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Background: Problematic smartphone use (PSU) has been associated with screen time in general, but little is known about the effect of different screen-based activities. We examined the associations of self-reported time spent on overall and specific screen-based activities with PSU and its addictive symptoms in Hong Kong Chinese adults.Methods: We analyzed data from 562 smartphone owners (56.5% female; 82.1% aged 25–64 years) in a population-based telephone survey in 2017. PSU was measured using Smartphone Addiction Scale-Short Version (range 10–60) which includes symptoms of daily-life disturbance, withdrawal, cyberspace-oriented relationship, overuse, and tolerance. Screen time was self-reported as average hours per day spent on the internet, online book/newspaper/magazine, online video, and social networking sites (SNS). Multivariable linear regression analyzed the associations of self-reported screen time with PSU severity and symptoms. Interaction effects of sex, age group, educational attainment, and monthly household income were examined.Results: Self-reported time spent on overall screen-based activities was associated with PSU severity (β = 1.35, 95% CI 0.15, 2.55) and withdrawal and overuse symptoms, after adjusting for sociodemographic and health-related variables. Independent association was observed for self-reported SNS time with PSU severity (β = 1.42, 95% CI 0.35, 2.49) and symptoms of withdrawal and cyberspace-oriented relationship, after mutually adjusting for time on other activities. The strongest association between self-reported SNS time and PSU severity was observed in younger than older adults (β = 4.36, 95% CI 2.58, 6.13; P for interaction = 0.004).Conclusions: The independent association of self-reported SNS time with PSU and core addictive symptoms highlighted the addiction potential of SNS use, particularly in younger users.
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These are the key social media statistics that you need to know.
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This work focuses on the efficiency of the knowledge distillation approach in generating a lightweight yet powerful BERT-based model for natural language processing (NLP) applications. After the model creation, we applied the resulting model, LastBERT, to a real-world task—classifying severity levels of Attention Deficit Hyperactivity Disorder (ADHD)-related concerns from social media text data. Referring to LastBERT, a customized student BERT model, we significantly lowered model parameters from 110 million BERT base to 29 million-resulting in a model approximately 73.64% smaller. On the General Language Understanding Evaluation (GLUE) benchmark, comprising paraphrase identification, sentiment analysis, and text classification, the student model maintained strong performance across many tasks despite this reduction. The model was also used on a real-world ADHD dataset with an accuracy of 85%, F1 score of 85%, precision of 85%, and recall of 85%. When compared to DistilBERT (66 million parameters) and ClinicalBERT (110 million parameters), LastBERT demonstrated comparable performance, with DistilBERT slightly outperforming it at 87%, and ClinicalBERT achieving 86% across the same metrics. These findings highlight the LastBERT model’s capacity to classify degrees of ADHD severity properly, so it offers a useful tool for mental health professionals to assess and comprehend material produced by users on social networking platforms. The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. Especially using readily available computational tools like Google Colab and Kaggle Notebooks. This study shows the accessibility and usefulness of advanced NLP methods in pragmatic world applications.
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Based on the Health Belief Model (HBM), this study examined what messages about COVID-19 were presented on the World Health Organization (WHO)’s Facebook posts, and evaluated WHO’s health promotion strategies by examining the public engagement and sentiment stimulated by different health promotion constructs. One issue with previous studies on HBM and social networking sites is that many researchers considered positive "online engagements" as evidence of "effective health promotion". However, online engagement measures such as shares and comments cannot reflect the sentiment’s valence. Another limitation in previous studies is that they often failed to differentiate between sentiments towards health measures and sentiments towards the disease. We utilized Facebook’s emojis to explore the public’s distinct sentiments towards the WHO’s COVID-19-related health measures and sentiments towards COVID-19. We used content analysis to examine the all the COVID-19-related Facebook posts published by the WHO in 2020, the first year of the pandemic when the COVID-19 vaccines were not generally available to the public. In general, the use of HBM constructs was successful in capturing users’ attention and generating engagement. However, regarding the effect of the use of HBM constructs on the beliefs in COVID-19-related health measures, the results were complex. The mentioning of the beliefs about a disease (perceived susceptibility and severity) tend to induce people’s negative sentiments. The mentioning of ways to increase self-efficacy and cues to actions significantly reduced people’s online engagements and sentiment (either positive or negative). Benefits only stimulated users’ negative reactions while barriers could not stimulate any reactions. Video and text posts generally attracted more Facebook engagement than image and text posts, while text-only posts generally received the least Facebook engagement. We demonstrated that certain health promotion strategies can backfire and even induce negative reactions. Policymakers should be alert to this phenomenon when mentioning certain constructs during health promotions.
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Social media addiction statistics show that over 210 million people worldwide suffer from social media addiction.
This statistic shows the results of a survey conducted by Cint on the distribution of social media used in France in 2016 and 2018. In 2017, ***** percent of respondents stated that they use Facebook.
Although the proportion of respondents saying they used Facebook decreased, the overall number of Facebook users in France is expected to reach ***** million people by 2022, an increase of **** million users from 2015.
The penetration rate of social media services in France was highest among 18-24 year olds. ** percent of respondents in this age group reported using social media services, dropping to ** percent of respondents among those aged 25-39 years. Among the general French population, ** percent of respondents reported using social media in any form during 2016, up from just ** percent in 2010.
Globally, Facebook is by far the most popular social networking platform, with ***** billion active users. WhatsApp - also owned by Facebook - is second with *** billion active users, ahead of YouTube's *** billion active users.
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Global Social Networking Services market size 2025 was XX Million. Social Networking Services Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.