According to a global survey conducted in February 2024, almost 40 percent of Facebook users paid attention to news from mainstram news outlets and mainstream journalists on the social network. Additionally, 39 percent reported paying attention to personalities, such as celebrities and influencers. Around one in four Facebook users paid attention to politicians and politican activists on the network.

As of April 2024, Facebook had an addressable ad audience reach 131.1 percent in Libya, followed by the United Arab Emirates with 120.5 percent and Mongolia with 116 percent. Additionally, the Philippines and Qatar had addressable ad audiences of 114.5 percent and 111.7 percent.

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.

As of February 2025, it was found that men between the ages of 25 and 34 years made up Facebook's largest audience, accounting for 18.5 percent of global users. Additionally, Facebook's second-largest audience base could be found with men aged 18 to 24 years. Facebook connects the world Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger, as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

Please cite the following paper when using this dataset:

N. Thakur, V. Su, M. Shao, K. Patel, H. Jeong, V. Knieling, and A. Bian “A labelled dataset for sentiment analysis of videos on YouTube, TikTok, and other sources about the 2024 outbreak of measles,” Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, USA, 29 June - 4 July 2024. (Accepted as a Late Breaking Paper, Preprint Available at: https://doi.org/10.48550/arXiv.2406.07693)

Abstract

This dataset contains the data of 4011 videos about the ongoing outbreak of measles published on 264 websites on the internet between January 1, 2024, and May 31, 2024. These websites primarily include YouTube and TikTok, which account for 48.6% and 15.2% of the videos, respectively. The remainder of the websites include Instagram and Facebook as well as the websites of various global and local news organizations. For each of these videos, the URL of the video, title of the post, description of the post, and the date of publication of the video are presented as separate attributes in the dataset. After developing this dataset, sentiment analysis (using VADER), subjectivity analysis (using TextBlob), and fine-grain sentiment analysis (using DistilRoBERTa-base) of the video titles and video descriptions were performed. This included classifying each video title and video description into (i) one of the sentiment classes i.e. positive, negative, or neutral, (ii) one of the subjectivity classes i.e. highly opinionated, neutral opinionated, or least opinionated, and (iii) one of the fine-grain sentiment classes i.e. fear, surprise, joy, sadness, anger, disgust, or neutral. These results are presented as separate attributes in the dataset for the training and testing of machine learning algorithms for performing sentiment analysis or subjectivity analysis in this field as well as for other applications. The paper associated with this dataset (please see the above-mentioned citation) also presents a list of open research questions that may be investigated using this dataset.

Currently, 2.7 billion people use at least one of the Facebook-owned social media platforms – Facebook, WhatsApp, and Instagram. Previous research investigating individual differences between users and non-users of these platforms has typically focused on one platform. However, individuals typically use a combination of Facebook-owned platforms. Therefore, we aim (1) to identify the relative prevalence of different patterns of social media use, and (2) to evaluate potential between-group differences in the distributions of age, gender, education, and Big Five personality traits. Data collection was performed using a cross-sectional design. Specifically, we administered a survey assessing participants’ demographic variables, current use of Facebook-owned platforms, and Big Five personality traits. In N = 3003 participants from the general population (60.67% females; mean age = 35.53 years, SD = 13.53), WhatsApp emerged as the most widely used application in the sample, and hence, has the strongest reach. A pattern consisting of a combined use of WhatsApp and Instagram appeared to be most prevalent among the youngest participants. Further, individuals using at least one social media platform were generally younger, more often female, and more extraverted than non-users. Small differences in Conscientiousness and Neuroticism also emerged across groups reporting different combinations of social media use. Interestingly, when examined as control variables, we found demographic characteristics partially accounted for differences in broad personality factors and facets across different patterns of social media use. Our findings are relevant to researchers carrying out their studies via social media platforms, as sample characteristics appear to be different depending on the platform used.

A Malayalam Question Answering dataset of 5,000 training samples and 5,000 testing samples was generated by translating Facebook bAbI tasks. Facebook's bAbI tasks was originally created in English, some of the languages it has been translated are French, German, Hindi, Chinese, Russian. Twenty fictitious tasks that test a system's capacity for responding to a range of themes, including text comprehension and reasoning, are included in the dataset. Five task-oriented usability questions with comparable sentence patterns are also included in the collection. The questions here range in difficulty. Every job has 1000 test samples and 1000 training samples in the dataset. we created the dataset for the proposed work by utilizing the bAbI dataset to translate the English dataset into Malayalam for five tasks (tasks 1, 4, 11, 12, and 13), represented as tasks 1 through 5. Titles such as "Single Supporting Facts," "Two Argument Relations," "Basic Coreference," "Conjunction," and "Compound Coreference" relate to the tasks. Every sample in the dataset comprises a series of statements (sometimes called stories) about people's movements around things, a question, a suitable answer. Tasks: Task 1: Single supporting fact: This task tests whether a model can identify a single important fact from a story to answer a question. The story usually contains several sentences, but only one sentence is directly useful in answering the question. Task 2: Relationships with two arguments: This task involves understanding the relationship between two entities. The model must infer relationships between pairs of objects, people or places. Task 3: Core co-reference: Co-reference resolution is the task of linking pronouns or phrases to the correct entities. In this task, the model must resolve simple pronominal references. Task 4: Conjunctions: This task tests the model's ability to understand sentences in which several actions or facts are joined by conjunctions such as "and" or "or". The model must process these linked statements to answer the questions correctly. Task 5: Compound Reference: This task is more complex because it requires the model to solve the conjunctions in the sentence with composite entities or more complex structures.

David Stillwell delivers the third keynote talk at Better Science through Better Data 2019 (#SciData19) - his talk is entitled 'Getting Big Data: Social Scientists Must Strive To Be Autonomous From Corporate Charity'. The video recording, presentation slides and live scribe illustrations are included.David is a Lecturer in Big Data Analytics and Quantitative Social Science at Cambridge University’s Judge Business School. David's research uses big data to understand psychology. He has published papers using social media data from millions of consenting individuals to show that the computer can predict a user's personality as accurately as their spouse can. This research has important public policy implications. How should consumers' data be used to target them? Should regulators step in, and if so how? David has spoken at workshops at the EU Parliament and to UK government regulators.David has also published research using various big data sources such as from credit card data and textual data to show that spending money on products that match one's personality leads to greater life satisfaction, that people tend to date others whose personality is similar, and that people who swear seem to be more honest.

The global mega data center market is experiencing robust growth, driven by the exponential increase in data generation from various sources, including cloud computing, the Internet of Things (IoT), and big data analytics. The market's Compound Annual Growth Rate (CAGR) is expected to remain strong throughout the forecast period (2025-2033), fueled by increasing digitalization across industries and the rising demand for high-performance computing capabilities. Key drivers include the need for enhanced data security, scalability, and energy efficiency, leading organizations to invest in larger, more sophisticated mega data center facilities. The market is segmented by type (e.g., hyperscale, colocation) and application (e.g., cloud computing, enterprise IT), with hyperscale data centers dominating the market share due to their ability to handle massive volumes of data. Leading companies like Apple, Facebook, Google, Microsoft, and others are making significant investments in expanding their global mega data center footprint to meet the growing demand, leading to a highly competitive landscape. Geographic expansion, particularly in regions with favorable regulatory environments and access to renewable energy sources, presents significant growth opportunities. While high capital expenditure and operational costs pose challenges, the long-term benefits of improved efficiency and scalability outweigh these restraints, ensuring continued market expansion. Despite these positive trends, the market faces certain constraints. These include the increasing complexity of managing mega data centers, the need for specialized expertise, and the growing concerns regarding energy consumption and environmental impact. Addressing these challenges through technological advancements in areas such as energy-efficient cooling systems and sustainable infrastructure will be critical for the sustained growth of the mega data center market. Furthermore, stringent regulations related to data privacy and security will continue to shape the market landscape, compelling companies to invest heavily in cybersecurity measures. Overall, the forecast suggests continued strong growth for the global mega data center market, driven by technological innovation, increasing data volumes, and the need for robust, scalable data infrastructure across diverse industries. However, navigating regulatory landscapes and addressing environmental concerns will play a crucial role in determining the long-term trajectory of this rapidly evolving sector.

Which county has the most Facebook users? There are more than 383 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 196.9 million, 122.3 million, and 111.65 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.

Visual analytics: Exposing the past, understanding the present, and looking to the future Dan Ariely, founder of The Center for Advanced Hindsight once posted on Facebook, “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it...” This is especially true in Higher Education as much of the work being done to organize, connect, and analyze big data is happening in the for profit sector. This multimedia presentation (video, photos, and text) has three goals. (1) Discuss how the field visual analytics is tackling the problem of analyzing big data. (2) Explore when visual analytics is superior and inferior to typical statistics. (3) Tactics and tools for Institutional Researchers to use in their everyday work to change data into actionable intelligence.

the dataset is collected from social media such as facebook and telegram. the dataset is further processed. the collection are D1_org: this dataset is neither stemed nor stopword are remove: D1_sf: in this dataset stopwords are removed but not stemmed and in D3_stemed datset is stemmed and stopwords are removed. stemming is done using hornmorpho developed by Michael Gesser( available at https://github.com/hltdi/HornMorpho) all datasets are normalized and free from noise such as punctuation marks and emojs.

United States FB: saar: FIN: NAFA: Loans: Long Term data was reported at 522.887 USD bn in Mar 2018. This records a decrease from the previous number of 711.510 USD bn for Dec 2017. United States FB: saar: FIN: NAFA: Loans: Long Term data is updated quarterly, averaging 102.319 USD bn from Dec 1951 (Median) to Mar 2018, with 266 observations. The data reached an all-time high of 1,647.756 USD bn in Mar 2006 and a record low of -476.403 USD bn in Mar 2010. United States FB: saar: FIN: NAFA: Loans: Long Term data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.AB078: Integrated Macroeconomic Accounts: Financial Business.

Uncapped_bottle

## Overview

Uncapped_bottle is a dataset for instance segmentation tasks - it contains Liquid_vap annotations for 395 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The global data compression software market is experiencing robust growth, projected to reach a market size of $2566.8 million in 2025. While the provided CAGR is missing, considering the rapid advancements in data generation and storage needs across sectors like IT & Telecommunications, Media & Entertainment, and the increasing demand for efficient data management, a conservative estimate of a 15% CAGR from 2025 to 2033 seems reasonable. This suggests substantial market expansion in the coming years. Key drivers include the exponential growth of data volumes from various sources, the need for faster data transmission speeds, reduced storage costs, and enhanced data security. Trends like cloud computing, the Internet of Things (IoT), and big data analytics further fuel this market expansion, necessitating efficient data compression techniques. However, constraints such as the complexity of implementing compression algorithms and potential compatibility issues across different systems present challenges. Market segmentation reveals significant opportunities in lossless and lossy compression technologies across diverse applications. The strong presence of established players like Google Corporation and Facebook, alongside specialized software vendors, indicates a competitive yet dynamic market landscape. The North American market currently holds a significant share, driven by technological advancements and high adoption rates, but rapid growth is anticipated in the Asia Pacific region due to increasing digitalization. The market’s future trajectory is shaped by several factors. The continued adoption of cloud-based solutions and the increasing reliance on edge computing will create a greater need for efficient data compression. Furthermore, advancements in AI and machine learning are leading to the development of more sophisticated compression algorithms, optimizing performance and minimizing data loss. The emergence of new applications, particularly in sectors like genomics and advanced manufacturing, will further fuel market growth. Companies are focusing on developing innovative solutions that address the unique challenges of various industries, emphasizing interoperability and scalability. This focus on adaptability and advanced features will define the competitive landscape and drive future market expansion.

[Keywords] Market include Apple, Affirm, China Unicom, AWS, Amdocs

United States FB: Balance Sheet: Assets: FA: Loan: Long Term data was reported at 14,445.863 USD bn in Mar 2018. This records an increase from the previous number of 14,356.211 USD bn for Dec 2017. United States FB: Balance Sheet: Assets: FA: Loan: Long Term data is updated quarterly, averaging 1,807.469 USD bn from Dec 1951 (Median) to Mar 2018, with 266 observations. The data reached an all-time high of 14,445.863 USD bn in Mar 2018 and a record low of 61.315 USD bn in Dec 1951. United States FB: Balance Sheet: Assets: FA: Loan: Long Term data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.AB078: Integrated Macroeconomic Accounts: Financial Business.

Czech Republic Average Consumer Price: FB: Long Grain Rice data was reported at 36.210 CZK/kg in Dec 2018. This records a decrease from the previous number of 36.450 CZK/kg for Nov 2018. Czech Republic Average Consumer Price: FB: Long Grain Rice data is updated monthly, averaging 35.665 CZK/kg from Jan 2011 (Median) to Dec 2018, with 96 observations. The data reached an all-time high of 36.960 CZK/kg in Nov 2016 and a record low of 31.990 CZK/kg in Jan 2011. Czech Republic Average Consumer Price: FB: Long Grain Rice data remains active status in CEIC and is reported by Czech Statistical Office. The data is categorized under Global Database’s Czech Republic – Table CZ.P004: Average Consumer Food and Beverage Prices: Monthly.

United States Foreign LT Sec: UH: FB: Africa: Botswana data was reported at 1.000 USD mn in Dec 2014. This stayed constant from the previous number of 1.000 USD mn for Nov 2014. United States Foreign LT Sec: UH: FB: Africa: Botswana data is updated monthly, averaging 1.000 USD mn from Dec 2011 (Median) to Dec 2014, with 37 observations. The data reached an all-time high of 1.000 USD mn in Dec 2014 and a record low of 0.000 USD mn in Nov 2012. United States Foreign LT Sec: UH: FB: Africa: Botswana data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.Z046: Foreign Long Term Securities by US Holders: By Country.

United States Foreign LT Sec: UH: FB: Other Countries data was reported at 130.783 USD bn in Apr 2018. This records a decrease from the previous number of 132.656 USD bn for Mar 2018. United States Foreign LT Sec: UH: FB: Other Countries data is updated monthly, averaging 141.967 USD bn from Dec 2011 (Median) to Apr 2018, with 77 observations. The data reached an all-time high of 168.252 USD bn in Oct 2012 and a record low of 124.630 USD bn in Dec 2016. United States Foreign LT Sec: UH: FB: Other Countries data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.Z046: Foreign Long Term Securities by US Holders: By Country.