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.

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.

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.

How much time do people spend on social media?

              As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in
              the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively.
              People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general.
              During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

Social Influence on Shopping

Social Survey Data from 300,000 Millennials and Gen Z Members

By Adam Halper [source]

About this dataset

This dataset offers a comprehensive look into the shopping habits of millennials and Gen Z members, including valuable insights about how their choices are influenced by social media. By exploring the responses given to survey questions related to this topic, we can gain an understanding of how these generations' interests, beliefs and desires shape their decisions when it comes to retail experiences. With 150 million survey responses from our 300,000+ millennial and Gen Z participants, we can uncover powerful insights that could help influencers, businesses and marketers more accurately target this demographic. Our data includes important information such as questions asked during the survey, segment types targeted by those questions and corresponding answers gathered with detailed counts/percentages - making this dataset incredibly useful for anyone wanting an in-depth understanding of what drives the purchasing behavior of today's youth

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For more datasets, click here.

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How to use the dataset

The first step in using this dataset is to take a look at each column: Question, Segment Type, Segment Description, Answer, Count & Percentage. The Question column will provide background on what exactly each survey question was asking - allowing you to get an overall view of what kind of topics were being surveyed in relation to millennials' shopping habits & social media influence. You will then be able to follow up with analysis based on the respective Segment Types & Descriptions given (such as income levels), which leads us into analyzing answers from both Count & Percentage columns combined - providing absolute numbers vs relative ones for further analysis (such as percentages).

Afterwards you'll need an advanced data analysis program such as SPSS or R-Studio - depending on your technical ability - though all most basic spreadsheet programs should suffice, excluding Matlab supported ones due its excessive complexity for something simple like this.. After selecting your preferred program inputting our file with all 150 million survey responses may take some time based on your computers processing capabilities but once loaded you'll be ready for endless possibilities! Now it's time get running with pulling out key insights you require utilizing various different tools found within these platforms whether it be linear regression or guided ANOVA testing which ever technique fits best should help lead navigate through uncovering deeper meaning in your ultra specific question!

As a final precaution while diving through waters filled surprises also keep note any adjustments needed potentially due overfitting or multicollinearity otherwise could cause major issues skew end results unfit requiring start whole process anew! Good luck delving deep discovering millennial behavior related digital world!

Research Ideas

• Identifying which type of segment is most responsive to engaging shopping experiences, such as influencer marketing, social media discounts and campaigns, etc.
• Analyzing the answers given to survey questions in order to understand millennial and Gen Z's opinion about social influence on their shopping habits - what do they view positively or negatively?
• Using the survey responses to uncover any interesting trends or correlations between different segments - is there a particular demographic that values or uses certain types of social influence on their shopping habits more than others?

Acknowledgements

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

License

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original.

Columns

File: WhatsgoodlyData-6.csv | Column name | Description ...

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

A global survey conducted in the third quarter of 2024 found that the main reason for using social media was to keep in touch with friends and family, with over 50.8 percent of social media users saying this was their main reason for using online networks. Overall, 39 percent of social media users said that filling spare time was their main reason for using social media platforms, whilst 34.5 percent of respondents said they used it to read news stories. Less than one in five users were on social platforms for the reason of following celebrities and influencers.

              The most popular social network

              Facebook dominates the social media landscape. The world's most popular social media platform turned 20 in February 2024, and it continues to lead the way in terms of user numbers. As of February 2025, the social network had over three billion global users. YouTube, Instagram, and WhatsApp follow, but none of these well-known brands can surpass Facebook’s audience size.
              Moreover, as of the final quarter of 2023, there were almost four billion Meta product users.

              Ever-evolving social media usage

              The utilization of social media remains largely gratuitous; however, companies have been encouraging users to become paid subscribers to reduce dependence on advertising profits. Meta Verified entices users by offering a blue verification badge and proactive account protection, among other things. X (formerly Twitter), Snapchat, and Reddit also offer users the chance to upgrade their social media accounts for a monthly free.

Dataset Description

Dataset Overview

This dataset encompasses a meticulously compiled collection of 2000 posts from the official International Cricket Council (ICC) Facebook page. Each entry captures the dynamic interactions of cricket enthusiasts around the globe, presenting a unique opportunity to explore the trends, sentiments, and patterns within the cricket community. The data was ethically mined today, ensuring up-to-date insights into the latest discussions and opinions circulating among ICC followers.

Data Science Applications

The breadth and depth of this dataset offer a fertile ground for a variety of data science projects, including but not limited to: - Sentiment Analysis: Gauge the emotional tone and sentiment of the global cricket community towards events, matches, and players. - Trend Analysis: Identify emerging trends in discussions, such as rising popularity of players or reactions to cricketing events. - Engagement Analysis: Understand what type of content generates the most engagement in terms of likes, shares, and comments. - Network Analysis: Explore the social dynamics and influence patterns within the cricket fan community. - Natural Language Processing (NLP): Employ advanced NLP techniques to extract insights, themes, and patterns from textual content.

Column Descriptors

The dataset is structured into four key columns: - Comments: Number of comments on each post, reflecting the level of interaction and discussion each topic generates. - Likes: Number of likes on each post, indicating the overall popularity and approval from the community. - Shares: Number of shares for each post, showing the extent to which content is circulated beyond the immediate audience. - Text: The textual content of the post, providing rich qualitative data for textual analysis and insight generation.

Ethically Mined Data

This dataset was ethically mined with strict adherence to privacy and data use policies, ensuring that all information was collected in a manner that respects user privacy and platform guidelines. No personal user data was collected or used in the creation of this dataset.

Acknowledgements

We extend our gratitude to the International Cricket Council (ICC) and Facebook for fostering an engaging and vibrant community where fans from around the world can share their passion for cricket. Their platforms not only bring fans closer to the game but also provide valuable data that can be used to enhance our understanding of sports communities and fan engagement.

This dataset serves as an invaluable resource for data scientists, researchers, and cricket enthusiasts alike, offering insights into the global conversation surrounding one of the world's most beloved sports.

this graphs was created in R and Ourdataworld:

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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...

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.

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.

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.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Ff0d45220cad473000b1e59942548dd45%2Fanimated_bubble_chart.gif?generation=1705615116968842&alt=media" alt="">This comprehensive football dataset, derived primarily from Transfermarkt, serves as a valuable resource for football enthusiasts, offering structured information on competitions, clubs, and players. With over 60,000 games across major global competitions, the dataset delves into the performance metrics of 400+ clubs and detailed statistics for more than 30,000 players.

Structured in CSV files, each with unique IDs, users can seamlessly join datasets to perform in-depth analyses. The dataset encompasses market values, historical valuations, and detailed player statistics, including physical attributes, contract statuses, and individual performances. A specialized Python-based web scraper ensures consistent updates, with data meticulously processed through Python scripts and SQL databases.

To use the dataset effectively, users are encouraged to understand the relevant files, join datasets using unique IDs, and leverage compatible software tools like Python's pandas or R's ggplot2 for analysis. The guide emphasizes the potential for fantasy football predictions, tracking player value over time, assessing market value versus performance, and exploring the impact of cards on match outcomes.

Research ideas include player performance analysis for fantasy football or recruitment purposes, studying market value trends for economic insights, evaluating club performance for strategic decision-making, developing predictive models for match outcomes, and conducting social network analysis to understand interactions among clubs and players.

Acknowledging the dataset's unknown license, users are encouraged to credit the original authors, particularly David Cereijo, if used in research. The dataset's dedication to accessibility is evident through active discussions on GitHub for improvements and bug fixes.

In conclusion, this football dataset offers a wealth of information, empowering users to explore diverse analyses and research ideas, bridging the gap between structured data and the dynamic world of football.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13364933%2F23694fae55e2e76299358693ba6f32b9%2Flv-share.jpg?generation=1684843825246772&alt=media" alt=""> ➡️ There are total 3 datasets containing valuable information. ➡️ Understand people's fame and behavior's on a dating app platform. | Column Name | Description | |---------------------|------------------------------| | Age | The age of the user. | | Number of Users | The total number of users. | | Percent Want Chats | Percentage of users who want chats. | | Percent Want Friends| Percentage of users who want friendships. | | Percent Want Dates | Percentage of users who want romantic dates. | | Mean Kisses Received| Average number of kisses received by users. | | Mean Visits Received| Average number of profile visits received by users. | | Mean Followers | Average number of followers for each user. | | Mean Languages Known| Average number of languages known by users. | | Total Want Chats | Total count of users interested in chats. | | Total Want Friends | Total count of users looking for friendships. | | Total Want Dates | Total count of users seeking romantic dates. | | Total Kisses Received| Overall count of kisses received by users. | | Total Visits Received| Overall count of profile visits received by users. | | Total Followers | Overall count of followers for all users. | | Total Languages Spoken| Total count of languages spoken by all users. |

SUMMARY

When Dating apps like Tinder were becoming viral, people wanted to have the best profile in order to get more matches and more potential encounters. Unlike other previous dating platforms, those new ones emphasized on the mutuality of attraction before allowing any two people to get in touch and chat. This made it all the more important to create the best profile in order to get the best first impression.

Parallel to that, we Humans have always been in awe before charismatic and inspiring people. The more charismatic people tend to be followed and listened to by more people. Through their metrics such as the number of friends/followers, social networks give some ways of "measuring" the potential charisma of some people.

In regard to all that, one can then think:

what makes a great user profile ? how to make the best first impression in order to get more matches (and ultimately find love, or new friendships) ? what makes a person charismatic ? how do charismatic people present themselves ? In order to try and understand those different social questions, I decided to create a dataset of user profile informations using the social network Lovoo when it came out. By using different methodologies, I was able to gather user profile data, as well as some usually unavailable metrics (such as the number of profile visits).

Content

The dataset contains user profile infos of users of the website Lovoo.

The dataset was gathered during spring 2015 (april, may). At that time, Lovoo was expanding in european countries (among others), while Tinder was trending both in America and in Europe. At that time the iOS version of the Lovoo app was in version 3.

Accessory image data The dataset references pictures (field pictureId) of user profiles. These pictures are also available for a fraction of users but have not been uploaded and should be asked separately.

The idea when gathering the profile pictures was to determine whether some correlations could be identified between a profile picture and the reputation or success of a given profile. Since first impression matters, a sound hypothesis to make is that the profile picture might have a great influence on the number of profile visits, matches and so on. Do not forget that only a fraction of a user's profile is seen when browsing through a list of users.

https://s1.dmcdn.net/v/BnWkG1M7WuJDq2PKP/x480

Details about collection methodology In order to gather the data, I developed a set of tools that would save the data while browsing through profiles and doing searches. Because of this approach (and the constraints that forced me to develop this approach) I could only gather user profiles that were recommended by Lovoo's algorithm for 2 profiles I created for this purpose occasion (male, open to friends & chats & dates). That is why there are only female users in the dataset. Another work could be done to fetch similar data for both genders or other age ranges.

Regarding the number of user profiles It turned out that the recommendation algorithm always seemed to output the same set of user profiles. This meant Lovoo's algorithm was probably heavily relying on settings like location (to recommend more people nearby than people in different places or countries) and maybe cookies. This diminished the number of different user profiles that would be pr...

E-commerce via social networks (hereinafter referred to as S-commerce) - the integration between social networks (Facebook, Zalo, TikTok) and e-commerce is becoming a strong development trend in online shopping. Through these platforms, users can directly interact, share and shop for products and services. This form helps businesses connect more closely with customers through social interaction, recommendations and reviews, thereby influencing consumers' purchasing decisions. The dataset examines factors influencing social commerce adoption among Vietnamese Generation Z university students, focusing on the roles of technology perceptions, social participation, and trust in platforms in shaping purchase intention and actual usage behavior.

-**Motivation:** On various Social Media platforms, people tend to use the informal way to communicate, or write posts and comments: their local dialects. In Africa, more than 1500 dialects and languages exist. While being so diverse and rich, Arabic language and particularly Arabic dialects, are still under represented and not yet fully exploited. Arabizi is a term describing a system of writing Arabic using English characters. This term comes from two words “arabi” (Arabic) and “Engliszi” (English). Arabizi is the representation of Arabic sounds using Latin letters and numbers to replace the non existing equivalent ones. Particularly in Tunisia, this way of writing was introduced as ”Tunizi”. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F11399696%2F55a8562b118fc4d877b6dc3c60c34782%2FTUNIZI%20example%20-%20Copie.jpg?generation=1703292391903003&alt=media" alt=""> Tunizi example comments and their Modern Standard Arabic (MSA) and English translations.

-**About this Dataset :** This is a large common-crawl-based Tunisian Arabizi dialectal dataset dedicated for Sentiment Analysis. The dataset consists of a total of 100k comments (about movies, politic, sport, etc.) annotated manually by Tunisian native speakers as Positive, Negative, and Neutral.

-**Value of this Data :** The authors introduced this large Tunizi dataset built for the sentiment analysis task, in order to help Tunisian and other researchers interested in the Natural Language Processing (NLP) field. This dataset can be also used for other NLP subtasks such as dialect identification, named entities recognition, etc...

-**How the data were acquired:**
According to the article authors, because of the lack of available Tunisian dialect data (books, wikipedia, etc.), they used a Common Crawl-based dataset extracted from social media. It is collected from comments on various social networks. The chosen posts included sports, politics, comedy, TV shows, TV series, arts and Tunisian music videos such that the dataset is representative and contains different types of ages, background, writing, etc. This data does not include any confidential information since it is collected from comments on public Social Media posts. However, negative comments may include offensive or insulting content. This dataset relates directly to people from different regions, different ages and different genders. A filter was applied to ensure that only Latin based comments are included. The extracted data was preprocessed by removing links, emoji symbols, and ponctuations|

Header & Thumbnail Image : Credits @VectorStock

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.

Please cite the following paper when using this dataset:

N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2

Abstract

The world is currently facing an outbreak of the monkeypox virus, and confirmed cases have been reported from 28 countries. Following a recent “emergency meeting”, the World Health Organization is considering whether the outbreak should be assessed as a “potential public health emergency of international concern” or PHEIC, as was done for the COVID-19 and Ebola outbreaks in the past. During this time, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, an open-access dataset of Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

Data Description

The dataset consists of a total of 102,452 tweet IDs of the same number of tweets about monkeypox that were posted on Twitter from 7^th May 2022 to 26^th June 2022 (the most recent date at the time of dataset upload). The Tweet IDs are presented in 5 different .txt files based on the timelines of the associated tweets. The following table provides the details of these dataset files.

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used. For hydrating this dataset the Hydrator application (link to download and a step-by-step tutorial on how to use Hydrator) may be used.

Success.ai’s Consumer Behavior Data for Consumer Goods & Electronics Industry Leaders in Asia, the US, and Europe offers a robust dataset designed to empower businesses with actionable insights into global consumer trends and professional profiles. Covering executives, product managers, marketers, and other professionals in the consumer goods and electronics sectors, this dataset includes verified contact information, professional histories, and geographic business data.

With access to over 700 million verified global profiles and firmographic data from leading companies, Success.ai ensures your outreach, market analysis, and strategic planning efforts are powered by accurate, continuously updated, and GDPR-compliant data. Backed by our Best Price Guarantee, this solution is ideal for businesses aiming to navigate and lead in these fast-paced industries.

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1. Verified Contact Data for Precision Engagement

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   • Includes profiles from key markets in Asia, the US, and Europe, covering regions such as China, India, Germany, and the United States.
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Data Highlights:

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Key Features of the Dataset:

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2. Advanced Filters for Precision Campaigns

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Why Choose Success.ai?

1. Best Price Guarantee
   • Access premium-quality consumer behavior data at competitive prices, ensuring maximum ROI for your outreach, research, and ma...