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.

During a 2024 survey, 77 percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just 23 percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis.

              Social media: trust and consumption

              Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than 35 percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than 50 percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media.

              What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis.
              Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers.
              Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

              Instagram’s Global Audience

              As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
              As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.

              Who is winning over the generations?

              Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.

Gen Z and Millennials are the biggest social media users of all age groups.

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.

The results might surprise you when looking at internet users that are active on social media in each country.

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.

56.8% of the world’s total population is active on social media.

Facebook and YouTube are still the most used social media platforms today.

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

The results of which gender uses which platforms are in.

Dataset Details

This dataset contains a rich collection of popular slang terms and acronyms used primarily by Generation Z. It includes detailed descriptions of each term, its context of use, and practical examples that demonstrate how the slang is used in real-life conversations. The dataset is designed to capture the unique and evolving language patterns of GenZ, reflecting their communication style in digital spaces such as social media, text messaging, and online forums. Each… See the full description on the dataset page: https://huggingface.co/datasets/MLBtrio/genz-slang-dataset.

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.

During a 2024 survey among marketers worldwide, around 86 percent reported using Facebook for marketing purposes. Instagram and LinkedIn followed, respectively mentioned by 79 and 65 percent of the respondents.

              The global social media marketing segment

              According to the same study, 59 percent of responding marketers intended to increase their organic use of YouTube for marketing purposes throughout that year. LinkedIn and Instagram followed with similar shares, rounding up the top three social media platforms attracting a planned growth in organic use among global marketers in 2024. Their main driver is increasing brand exposure and traffic, which led the ranking of benefits of social media marketing worldwide.

              Social media for B2B marketing

              Social media platform adoption rates among business-to-consumer (B2C) and business-to-business (B2B) marketers vary according to each subsegment's focus. While B2C professionals prioritize Facebook and Instagram – both run by Meta, Inc. – due to their popularity among online audiences, B2B marketers concentrate their endeavors on Microsoft-owned LinkedIn due to its goal to connect people and companies in a corporate context.

Regional use of social media has a significant effect on the male and female social media statistics.

On behalf of the Press and Information Office of the Federal Government, the opinion research institute Kantar conducted a target group survey of the ´Generation Z´. For this purpose, 1,022 people between the ages of 14 and 24 were surveyed online between 05 and 18 July 2021. The focus of the survey was on the values and orientation of the generation, their situation in the pandemic, political interest and information behaviour as well as political and social attitudes. In order to map the influence of the corona pandemic on the attitudes and social image of Generation Z, the results of this survey were compared with a survey from 2019. Current life circumstances: life satisfaction; highest school-leaving qualification of father and mother; material situation: frequency of renunciation for financial reasons; source of money (from own work, from parents, from state support, from elsewhere); primary source of money; negative effects of the Corona crisis on personal income; organisation of distance learning (communication via a digital learning platform, via video conference, via e-mail, via messenger/chats such as e.g. WhatsApp, via a cloud, by telephone, by post or by other means); agreement with statements on the situation in schools/colleges (I was able to concentrate well on my tasks at home, I missed direct contact with my classmates/ fellow students, my grades deteriorated during the pandemic, distance learning at my school/college worked well, I had insufficient equipment to follow lessons, the accessibility of teachers was very good even in times of distance learning, learning became more strenuous for me during the pandemic); opinion on the future recognition of school, university or professional degrees made during the Corona pandemic; leisure activities during the pandemic (less sport since the beginning of the pandemic than before, relationships with friends have deteriorated during the pandemic, significantly more time on the internet since the beginning of the pandemic than before, started a new hobby during the pandemic); vaccination status; likelihood of Corona vaccination. 2. Values and attitudes: personally most important life goals (e.g. self-discovery, independence, enjoying life, career, etc.); importance of various aspects for pursuing a profession (secure job, adequate income, interesting work that is fun, compatibility of private life and profession (work-life balance), career opportunities, responsibility, opportunities for further training and development); comparison of values : comparison of values Corona: extensive collection of data for infection protection vs. data protection, especially young vs. especially old people have suffered from the pandemic, pandemic as a chance for change vs. after the pandemic back to the usual normality, comparison of values State: debts in favour of education and infrastructure not a problem vs. always a burden for future generations, active role of the state for important future tasks such as climate protection and educational justice vs. leaving a passive role and shaping of the future to society and the economy, orienting politics towards future generations vs. protecting the interests of those who have already made a contribution to society, comparison of lifestyle values: conscious renunciation in favour of sustainability vs. doing what I feel like doing, doing without in favour of health vs. having fun in the foreground, self-realisation vs. putting aside one´s own needs in favour of one´s personal environment, today´s generation has completely different values than the generation before it vs. in principle very similar values as the generation before it). 3. Media and information: interest in politics; points of contact with politics in everyday life (e.g. media consumption, when using social networks, in personal conversations with friends and family, at work, at school or university, in public spaces, in leisure time/hobbies); being informed about politics; most frequently used sources of political information (media) (e.g. news programmes on TV, talk shows on TV, websites of public institutions and authorities, etc.). e.g. news programmes on TV, talk shows on TV, websites of public institutions and authorities, satire programmes on TV, etc.); change in political information behaviour in the Corona pandemic. 4. Politics and society: satisfaction with democracy; opinion on democracy as an idea; need for reform of politics in Germany; most important political problems in Germany (open); satisfaction with the work of the federal government; trust in institutions (judiciary, environmental and aid organisations such as Greenpeace or Amnesty International, public health authorities such as the Robert Koch Institute, federal government, Bundestag, police, churches, school/university); perception of social lines of conflict (between rich and poor, employers and employees, young and old, foreigners and Germans, East Germans and West Germans, women and men, people in the city and people in the countryside); attitudes towards Corona (politicians take young people´s concerns seriously, young people received sufficient financial support from the state during the pandemic, young people´s needs were not taken into account enough by politicians during the Corona pandemic, the Corona pandemic will affect my generation´s future opportunities in the long term, my generation will benefit significantly from the awakening after the Corona pandemic, the Corona crisis has changed my perspective on many things in life, young people´s career opportunities have deteriorated as a result of the pandemic); agreement with various statements on Corona vaccination (children and young people aged 12 and over should also be vaccinated against Corona, young people currently have to wait too long for a vaccination appointment, vaccination prioritisation should have been lifted earlier, vaccination of young people against Corona is not necessary, there should be compulsory vaccination for schoolchildren, I personally feel that Corona vaccinations in Germany are treated fairly); currently appropriate measures to support children and young people (open). 5. Future perspectives: assessment of personal future opportunities; assessment of the future opportunities of one´s own generation in Germany; future vision of politics: agreement with various statements (a council of randomly selected citizens should be created to draw up political recommendations for the federal government, voting in elections should be possible via app, the voting age in federal elections should be lowered to 16, the population should be represented in the Bundestag by means of quotas, the population should vote directly on important political issues by referendum). Demography: age; sex; federal state; current attendance at school, college or university; type of educational institution currently attended; highest level of education attained to date; employment; subjective class classification; housing situation; household size; party sympathies; migration background. Additionally coded was: serial number; city size; weighting factor. Im Auftrag des Presse- und Informationsamt der Bundesregierung hat das Meinungsforschungsinstitut Kantar eine Zielgruppenbefragung der „Generation Z“ durchgeführt. Dazu wurden im Zeitraum vom 05. – 18. Juli 2021 1.022 Personen zwischen 14 und 24 Jahren online befragt. Die Schwerpunkte der Befragung lagen auf den Werten und Orientierung der Generation, ihrer Situation in der Pandemie, dem politischen Interesse und Informationsverhalten sowie auf den politischen und gesellschaftlichen Einstellungen. Um den Einfluss der Coronapandemie auf die Einstellungen und das Gesellschaftsbild der Generation Z abzubilden, wurden die Ergebnisse dieser Befragung mit einer Befragung aus dem Jahr 2019 verglichen. Aktuelle Lebensumstände: Lebenszufriedenheit; höchster Schulabschluss von Vater und Mutter; materielle Situation: Häufigkeit des Verzichts aus finanziellen Gründen; Geldquelle (aus eigener Arbeit, von den Eltern, aus staatlicher Unterstützung, von woanders her); primäre Geldquelle; negative Auswirkungen der Corona-Krise auf das persönliche Einkommen; Organisation des Fernunterrichts (Kommunikation über eine digitale Lernplattform, per Videokonferenz, per E-Mail, per Messenger/Chats wie z.B. WhatsApp, über eine Cloud, per Telefon, per Post oder auf sonstige Weise); Zustimmung zu Aussagen zur Situation in Schulen/ an Hochschulen (ich konnte mich zu Hause gut auf meine Aufgaben konzentrieren, der direkte Kontakt zu meinen Mitschüler/innen/ Kommilitonen/innen hat mir gefehlt, meine Noten sind während der Pandemie schlechter geworden, der Fernunterricht an meiner Schule/ Hochschule hat gut funktioniert, ich hatte nur ungenügende Ausstattung zur Verfügung, um dem Unterricht folgen zu können, die Erreichbarkeit der Lehrkräfte war auch in Zeiten des Fernunterrichts sehr gut, das Lernen ist für mich während der Pandemie anstrengender geworden); Meinung zur künftigen Anerkennung von Schul-, Universitäts- oder Berufsabschlüssen, die während der Corona-Pandemie gemacht wurden; Freizeitgestaltung während der Pandemie (seit Beginn der Pandemie weniger Sport als davor, Beziehungen zu Freunden haben sich in der Pandemie verschlechtert, seit Beginn der Pandemie deutlich mehr Zeit im Internet als davor, in der Pandemie ein neues Hobby begonnen); Impfstatus; Wahrscheinlichkeit einer Corona-Impfung. 2. Werte und Einstellungen: persönlich wichtigste Lebensziele (z.B. Selbstfindung, Unabhängigkeit, Leben genießen, Karriere, etc.); Wichtigkeit verschiedener Aspekte für die Ausübung eines Berufs (sicherer Arbeitsplatz, angemessenes Einkommen, interessante Arbeit, die Spaß macht, Vereinbarkeit von Privatleben und Beruf (Work-Life-Balance), Karrieremöglichkeiten, Verantwortung, Weiterbildungs- und Entwicklungsmöglichkeiten); Gegenüberstellung von Werten :

Over the last ten years, social media has become a crucial data source for businesses and researchers, providing a space where people can express their opinions and emotions. To analyze this data and classify emotions and their polarity in texts, natural language processing (NLP) techniques such as emotion analysis (EA) and sentiment analysis (SA) are employed. However, the effectiveness of these tasks using machine learning (ML) and deep learning (DL) methods depends on large labeled datasets, which are scarce in languages like Spanish. To address this challenge, researchers use data augmentation (DA) techniques to artificially expand small datasets. This study aims to investigate whether DA techniques can improve classification results using ML and DL algorithms for sentiment and emotion analysis of Spanish texts. Various text manipulation techniques were applied, including transformations, paraphrasing (back-translation), and text generation using generative adversarial networks, to small datasets such as song lyrics, social media comments, headlines from national newspapers in Chile, and survey responses from higher education students. The findings show that the Convolutional Neural Network (CNN) classifier achieved the most significant improvement, with an 18% increase using the Generative Adversarial Networks for Sentiment Text (SentiGan) on the Aggressiveness (Seriousness) dataset. Additionally, the same classifier model showed an 11% improvement using the Easy Data Augmentation (EDA) on the Gender-Based Violence dataset. The performance of the Bidirectional Encoder Representations from Transformers (BETO) also improved by 10% on the back-translation augmented version of the October 18 dataset, and by 4% on the EDA augmented version of the Teaching survey dataset. These results suggest that data augmentation techniques enhance performance by transforming text and adapting it to the specific characteristics of the dataset. Through experimentation with various augmentation techniques, this research provides valuable insights into the analysis of subjectivity in Spanish texts and offers guidance for selecting algorithms and techniques based on dataset features.

Overview
The Controllable Multimodal Feedback Synthesis (CMFeed) Dataset is designed to enable the generation of sentiment-controlled feedback from multimodal inputs, including text and images. This dataset can be used to train feedback synthesis models in both uncontrolled and sentiment-controlled manners. Serving a crucial role in advancing research, the CMFeed dataset supports the development of human-like feedback synthesis, a novel task defined by the dataset's authors. Additionally, the corresponding feedback synthesis models and benchmark results are presented in the associated code and research publication.

Task Uniqueness: The task of controllable multimodal feedback synthesis is unique, distinct from LLMs and tasks like VisDial, and not addressed by multi-modal LLMs. LLMs often exhibit errors and hallucinations, as evidenced by their auto-regressive and black-box nature, which can obscure the influence of different modalities on the generated responses [Ref1; Ref2]. Our approach includes an interpretability mechanism, as detailed in the supplementary material of the corresponding research publication, demonstrating how metadata and multimodal features shape responses and learn sentiments. This controllability and interpretability aim to inspire new methodologies in related fields.

Data Collection and Annotation
Data was collected by crawling Facebook posts from major news outlets, adhering to ethical and legal standards. The comments were annotated using four sentiment analysis models: FLAIR, SentimentR, RoBERTa, and DistilBERT. Facebook was chosen for dataset construction because of the following factors:
• Facebook was chosen for data collection because it uniquely provides metadata such as news article link, post shares, post reaction, comment like, comment rank, comment reaction rank, and relevance scores, not available on other platforms.
• Facebook is the most used social media platform, with 3.07 billion monthly users, compared to 550 million Twitter and 500 million Reddit users. [Ref]
• Facebook is popular across all age groups (18-29, 30-49, 50-64, 65+), with at least 58% usage, compared to 6% for Twitter and 3% for Reddit. [Ref]. Trends are similar for gender, race, ethnicity, income, education, community, and political affiliation [Ref]
• The male-to-female user ratio on Facebook is 56.3% to 43.7%; on Twitter, it's 66.72% to 23.28%; Reddit does not report this data. [Ref]

Filtering Process: To ensure high-quality and reliable data, the dataset underwent two levels of filtering:
a) Model Agreement Filtering: Retained only comments where at least three out of the four models agreed on the sentiment.
b) Probability Range Safety Margin: Comments with a sentiment probability between 0.49 and 0.51, indicating low confidence in sentiment classification, were excluded.
After filtering, 4,512 samples were marked as XX. Though these samples have been released for the reader's understanding, they were not used in training the feedback synthesis model proposed in the corresponding research paper.

Dataset Description
• Total Samples: 61,734
• Total Samples Annotated: 57,222 after filtering.
• Total Posts: 3,646
• Average Likes per Post: 65.1
• Average Likes per Comment: 10.5
• Average Length of News Text: 655 words
• Average Number of Images per Post: 3.7

Components of the Dataset
The dataset comprises two main components:
• CMFeed.csv File: Contains metadata, comment, and reaction details related to each post.
• Images Folder: Contains folders with images corresponding to each post.

Data Format and Fields of the CSV File
The dataset is structured in CMFeed.csv file along with corresponding images in related folders. This CSV file includes the following fields:
• Id: Unique identifier
• Post: The heading of the news article.
• News_text: The text of the news article.
• News_link: URL link to the original news article.
• News_Images: A path to the folder containing images related to the post.
• Post_shares: Number of times the post has been shared.
• Post_reaction: A JSON object capturing reactions (like, love, etc.) to the post and their counts.
• Comment: Text of the user comment.
• Comment_like: Number of likes on the comment.
• Comment_reaction_rank: A JSON object detailing the type and count of reactions the comment received.
• Comment_link: URL link to the original comment on Facebook.
• Comment_rank: Rank of the comment based on engagement and relevance.
• Score: Sentiment score computed based on the consensus of sentiment analysis models.
• Agreement: Indicates the consensus level among the sentiment models, ranging from -4 (all negative) to 4 (all positive). 3 negative and 1 positive will result into -2 and 3 positives and 1 negative will result into +2.
• Sentiment_class: Categorizes the sentiment of the comment into 1 (positive) or 0 (negative).

More Considerations During Dataset Construction
We thoroughly considered issues such as the choice of social media platform for data collection, bias and generalizability of the data, selection of news handles/websites, ethical protocols, privacy and potential misuse before beginning data collection. While achieving completely unbiased and fair data is unattainable, we endeavored to minimize biases and ensure as much generalizability as possible. Building on these considerations, we made the following decisions about data sources and handling to ensure the integrity and utility of the dataset:

• Why not merge data from different social media platforms? We chose not to merge data from platforms such as Reddit and Twitter with Facebook due to the lack of comprehensive metadata, clear ethical guidelines, and control mechanisms—such as who can comment and whether users' anonymity is maintained—on these platforms other than Facebook. These factors are critical for our analysis. Our focus on Facebook alone was crucial to ensure consistency in data quality and format.

• Choice of four news handles: We selected four news handles—BBC News, Sky News, Fox News, and NY Daily News—to ensure diversity and comprehensive regional coverage. These news outlets were chosen for their distinct regional focuses and editorial perspectives: BBC News is known for its global coverage with a centrist view, Sky News offers geographically targeted and politically varied content learning center/right in the UK/EU/US, Fox News is recognized for its right-leaning content in the US, and NY Daily News provides left-leaning coverage in New York. Many other news handles such as NDTV, The Hindu, Xinhua, and SCMP are also large-scale but may contain information in regional languages such as Indian and Chinese, hence, they have not been selected. This selection ensures a broad spectrum of political discourse and audience engagement.

• Dataset Generalizability and Bias: With 3.07 billion of the total 5 billion social media users, the extensive user base of Facebook, reflective of broader social media engagement patterns, ensures that the insights gained are applicable across various platforms, reducing bias and strengthening the generalizability of our findings. Additionally, the geographic and political diversity of these news sources, ranging from local (NY Daily News) to international (BBC News), and spanning political spectra from left (NY Daily News) to right (Fox News), ensures a balanced representation of global and political viewpoints in our dataset. This approach not only mitigates regional and ideological biases but also enriches the dataset with a wide array of perspectives, further solidifying the robustness and applicability of our research.

• Dataset size and diversity: Facebook prohibits the automatic scraping of its users' personal data. In compliance with this policy, we manually scraped publicly available data. This labor-intensive process requiring around 800 hours of manual effort, limited our data volume but allowed for precise selection. We followed ethical protocols for scraping Facebook data , selecting 1000 posts from each of the four news handles to enhance diversity and reduce bias. Initially, 4000 posts were collected; after preprocessing (detailed in Section 3.1), 3646 posts remained. We then processed all associated comments, resulting in a total of 61734 comments. This manual method ensures adherence to Facebook’s policies and the integrity of our dataset.

Ethical considerations, data privacy and misuse prevention
The data collection adheres to Facebook’s ethical guidelines [<a href="https://developers.facebook.com/terms/"

In this post, I'll give you all the social media addiction statistics you need to be aware of to moderate your social media use.

Social media companies are starting to offer users the option to subscribe to their platforms in exchange for monthly fees. Until recently, social media has been predominantly free to use, with tech companies relying on advertising as their main revenue generator. However, advertising revenues have been dropping following the COVID-induced boom. As of July 2023, Meta Verified is the most costly of the subscription services, setting users back almost 15 U.S. dollars per month on iOS or Android. Twitter Blue costs between eight and 11 U.S. dollars per month and ensures users will receive the blue check mark, and have the ability to edit tweets and have NFT profile pictures. Snapchat+, drawing in four million users as of the second quarter of 2023, boasts a Story re-watch function, custom app icons, and a Snapchat+ badge.