As of October 2025, English was the dominant language for online content, used by nearly half of all websites worldwide. Spanish ranked second, accounting for around 6 percent of web content, followed by German with 5.9 percent. English as the leading online language United States and India, the countries with the most internet users after China, are also the world's biggest English-speaking markets. The internet user base in both countries combined, as of January 2023, was over a billion individuals. This has led to most of the online information being created in English. Consequently, even those who are not native speakers may use it for convenience. Global internet usage by regions As of October 2024, the number of internet users worldwide was 5.52 billion. In the same period, Northern Europe and North America were leading in terms of internet penetration rates worldwide, with around 97 percent of its populations accessing the internet.

The dataset maps the accessibility and usability of municipal websites in mainland Finland for immigrants. Background information in the dataset was collected from Statistics Finland's population database. The first part of the study mapped the content of the websites of municipalities in mainland Finland. Regarding website content, the study investigated whether the sites provide information on topics such as housing and construction, youth affairs, or the COVID-19 situation. Next, the presence of a dedicated section for immigrants on the municipal websites was examined, along with the types of information provided in that section. The analysis examined, for example, whether the immigrant sections included information about healthcare, public transportation, or housing services. Additionally, it was assessed whether the section mentioned services not provided by the municipality and what language the immigrant section was written in. After this, the features of Finnish-language web pages intended for immigrants were evaluated, such as whether the website has clear headings or whether its content has been simplified into plain language. Finally, it was examined whether information related to the municipality's social and health services is provided on a separate social and health website. Finnish-language social services websites were also assessed based on their features, such as the clarity of the language and the findability of information. The background variables of the dataset include the name of the municipality, the total number of residents, the number and percentage of residents who speak foreign languages, as well as the languages spoken by foreign-language residents and the number of speakers of each language.

According to a 2023 survey, ** percent of internet users in urban India preferred using the internet in English. Meanwhile, ** percent of users accessed the internet in Indian languages, with Hindi being the most preferred language among them. Over *** million internet users reside in the urban areas of India.

As of December 2023, the English subdomain of Wikipedia had around 6.91 million articles published, being the largest subdomain of the website by number of entries and registered active users. German and French ranked third and fourth, with over 29.6 million and 26.5 million entries. Being the only Asian language figuring among the top 10, Cebuano was the language with the second-most articles on the portal, amassing around 6.11 million entries. However, while most Wikipedia articles in English and other European languages are written by humans, entries in Cebuano are reportedly mostly generated by bots.

In 2025, there were around 1.53 billion people worldwide who spoke English either natively or as a second language, slightly more than the 1.18 billion Mandarin Chinese speakers at the time of survey. Hindi and Spanish accounted for the third and fourth most widespread languages that year. Languages in the United States The United States does not have an official language, but the country uses English, specifically American English, for legislation, regulation, and other official pronouncements. The United States is a land of immigration, and the languages spoken in the United States vary as a result of the multicultural population. The second most common language spoken in the United States is Spanish or Spanish Creole, which over than 43 million people spoke at home in 2023. There were also 3.5 million Chinese speakers (including both Mandarin and Cantonese),1.8 million Tagalog speakers, and 1.57 million Vietnamese speakers counted in the United States that year. Different languages at home The percentage of people in the United States speaking a language other than English at home varies from state to state. The state with the highest percentage of population speaking a language other than English is California. About 45 percent of its population was speaking a language other than English at home in 2023.

FineWeb-C: Educational content in many languages, labelled by the community This is a link to the Danish part of the dataset.

This is a collaborative, community-driven project that expands upon the FineWeb2 dataset. Our goal is to create high-quality educational content annotations across hundreds of languages.

By enhancing web content with these annotations, we aim to improve the development of Large Language Models (LLMs) in all languages, making AI technology more accessible and effective globally.

The annotations in this dataset will help train AI systems to automatically identify high-quality educational content in more languages and in turn help build better Large Language Models for all languages.

What the community is doing: For a given language, look at a page of web content from the FineWeb2 dataset in Argilla. Rate how educational the content is. Flag problematic content i.e. content that is malformed or in the wrong language. Once a language reaches 1,000 annotations, the dataset will be included in this dataset! Alongside rating the educational quality of the content, different language communities are discussing other ways to improve the quality of data for their language in our Discord discussion channel.

The use of this dataset is also subject to CommonCrawl's Terms of Use.

Context

We all love programming!! This dataset is an attempt to look at the trends of different programming languages in the last 1 year.

Content

This dataset was web-scraped by me, represents information extracted from Tiobe website. This dataset contains 20 different programming languages popularity, their popularity changes over the past 1 year. Details about Jan 2020 and Jan 2021 world rank is also given in the same.

Acknowledgements

I want to thank you all for contributing to this trend (remember, a contribution is never insignificant)!!

Inspiration

This dataset can be used to predict the future trend of popular programming languages, the dataset provides insights into annual change so, it can be used as a regression task to predict by how much a particular language can takeover the other.

Have a nice day!!

Context:

How frequently a word occurs in a language is an important piece of information for natural language processing and linguists. In natural language processing, very frequent words tend to be less informative than less frequent one and are often removed during preprocessing. Human language users are also sensitive to word frequency. How often a word is used affects language processing in humans. For example, very frequent words are read and understood more quickly and can be understood more easily in background noise.

Content:

This dataset contains the counts of the 333,333 most commonly-used single words on the English language web, as derived from the Google Web Trillion Word Corpus.

Acknowledgements:

Data files were derived from the Google Web Trillion Word Corpus (as described by Thorsten Brants and Alex Franz, and distributed by the Linguistic Data Consortium) by Peter Norvig. You can find more information on these files and the code used to generate them here.

The code used to generate this dataset is distributed under the MIT License.

Inspiration:

• Can you tag the part of speech of these words? Which parts of speech are most frequent? Is this similar to other languages, like Japanese?
• What differences are there between the very frequent words in this dataset, and the the frequent words in other corpora, such as the Brown Corpus or the TIMIT corpus? What might these differences tell us about how language is used?

Content

Sign language images taken by 7 different users, a total of 1687 images.

Acknowledgements

Data set belong to Yoav Ram as part of IDC Scientific computation in Python course

A survey on digital news consumption conducted in India in March 2023 revealed that unpolished, poorly edited content was the most commonly experienced problem with local-language online news as reported by ** percent of respondents. Too many ads interrupting the users' experience followed by hard-to-navigate websites were the two other leading drawbacks cited by online news consumers.

Web content from the Language Commissioner's Office.

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) actions SMART 2014/1074 and SMART 2015/1091. For further information on the project: http://lr-coordination.eu.

According to a survey conducted in the United Kingdom in 2020, 65 percent of teenagers aged between 13 and 17 years, had seen offensive or harmful language in online videos where they were not expecting to see them. Just over a quarter of adults aged 18 years and older said they had seen online content that they were sure was illegal. During the same survey, it was found that more than half of the teenage respondents had seen violent or graphic images in online videos where they were not expecting to see them.

The online language training market is experiencing robust growth, fueled by increasing globalization, the rising demand for multilingual workforces, and the convenience offered by digital learning platforms. With a Compound Annual Growth Rate (CAGR) of 22%, the market, currently valued at approximately $XX million (we'll assume a starting value of $5 billion in 2025 for illustrative purposes, based on typical market sizes for this sector), is projected to reach a substantial size by 2033. Key drivers include the affordability and accessibility of online courses compared to traditional classroom settings, the availability of personalized learning experiences through adaptive technology, and the growing integration of mobile learning apps. Furthermore, the expanding use of gamification and interactive learning methods significantly enhances user engagement and improves learning outcomes, contributing to market expansion. Several trends are shaping the market's trajectory. The increasing adoption of blended learning models, combining online and offline components, caters to diverse learning styles and preferences. The rise of artificial intelligence (AI)-powered language learning tools provides personalized feedback and customized learning paths, enhancing efficiency and effectiveness. However, challenges remain, including concerns about the authenticity of online certifications, the digital divide impacting access to technology in certain regions, and the need for ongoing improvements in virtual classroom interaction to replicate the benefits of face-to-face instruction. Competition is fierce, with established players like Berlitz and Rosetta Stone alongside innovative startups like Duolingo and Memrise vying for market share through diverse competitive strategies focused on content quality, technology integration, and marketing reach. The market's segmentation by language type and application (e.g., professional development, personal enrichment) presents opportunities for specialized platforms to emerge and cater to niche demands. Regional variations in market penetration and growth will likely persist, with North America and Europe continuing to hold significant market shares, while Asia-Pacific demonstrates strong growth potential.

Topics: mother tongue; used languages to read or watch internet content and frequency of use; used languages to write in the internet and frequency of use; frequency of using languages different from own language with regard to the following internet acti

German Legal monolingual corpus from the contensts of the https://www.gesetze-im-internet.de/ web site

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) actions SMART 2014/1074 and SMART 2015/1091. For further information on the project: http://lr-coordination.eu.

This is a parallel corpus of bilingual texts crawled from multilingual websites, which contains 15,797 TUs. Period of crawling : 15/11/2016 - 23/01/2017. A strict validation process has been followed, which resulted in discarding: - TUs from crawled websites that do not comply to the PSI directive, - TUs with more than 99% of mispelled tokens, - TUs identified during the manual validation process and all the TUs from websites which error rate in the sample extracted for manual validation is strictly above the following thresholds: 50% of TUs with language identification errors, 50% of TUs with alignment errors, 50% of TUs with tokenization errors, 20% of TUs identified as machine translated content, 50% of TUs with translation errors.

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) actions SMART 2014/1074 and SMART 2015/1091. For further information on the project: http://lr-coordination.eu.

Interactive Language Content Market Outlook

As per our latest research, the global Interactive Language Content market size stood at USD 7.2 billion in 2024, reflecting robust growth driven by digital transformation in education and corporate sectors. The market is poised to expand at a remarkable CAGR of 16.8% from 2025 to 2033, reaching an estimated USD 37.8 billion by 2033. The surge in demand for immersive and adaptive language learning experiences, coupled with advancements in artificial intelligence, is propelling this upward trajectory.

The primary growth factor for the Interactive Language Content market is the rapid adoption of digital platforms across educational institutions and corporate organizations globally. The proliferation of smart devices and high-speed internet access has democratized access to interactive language tools, making them more accessible to diverse user groups. Educational technology (EdTech) investments are at an all-time high, with governments and private stakeholders recognizing the need for scalable, engaging, and effective language learning solutions. Furthermore, the integration of personalized learning pathways, powered by AI and machine learning, is enhancing user engagement and retention, thereby fueling market expansion.

Another significant driver is the increasing globalization of the workforce and the growing necessity for multilingual communication in international business environments. Enterprises are increasingly investing in interactive language content for employee upskilling, cross-border collaboration, and customer engagement. The rise of remote and hybrid work models has further accelerated this trend, with organizations seeking cloud-based, on-demand language training solutions to bridge communication gaps and foster inclusivity. Additionally, the gamification of language content is gaining traction, as it encourages active participation and improves learning outcomes, especially among younger demographics.

The entertainment and media sectors are also contributing to the market's growth by incorporating interactive language modules into streaming platforms, games, and virtual experiences. This convergence of entertainment and education is creating new monetization avenues for content creators and platform providers. Moreover, the surge in language learning app downloads during the COVID-19 pandemic has established a lasting behavioral shift, with individuals now prioritizing self-paced, interactive learning experiences. These trends, combined with ongoing technological innovations such as natural language processing and speech recognition, are expected to sustain market momentum over the forecast period.

From a regional perspective, North America currently leads the Interactive Language Content market, owing to its advanced digital infrastructure, high smartphone penetration, and substantial investments in EdTech. However, the Asia Pacific region is witnessing the fastest growth, driven by rising internet adoption, expanding middle-class populations, and a strong emphasis on English and other foreign language acquisition. Europe remains a significant market, particularly due to its linguistic diversity and supportive government initiatives in digital education. Meanwhile, Latin America and the Middle East & Africa are emerging as promising markets, propelled by increasing educational reforms and growing demand for accessible language learning resources.

Content Type Analysis

The Content Type segment of the Interactive Language Content market is highly diversified, encompassing text-based, audio-based, video-based, gamified content, and other innovative formats. Text-based content remains foundational, offering structured grammar exercises, reading comprehension passages, and vocabulary drills. Its accessibility and ease of integration with digital platforms make it a staple in both academic and corporate settings. However, the static nature of text-based content is increasingly being complemented by dynamic formats to cater to varied learning preferences and enhance engagement.

Audio-based content is gaining significant traction, particularly for pronunciation practice, listening comprehension, and real-time conversational simulations. The integration of speech recognition technology allows learners to receive instant feedback, fostering acti

Context

The dataset contains tweets that are used #covid-19 as a hashtag.

Content

The data contains the following information:

• Username: Username of the person who tweeted
• User Display Name: Name of the person who tweeted
• User Description: Description of the person who tweeted
• User Location: Location of the person who tweeted
• User Verified: Whether the person who tweeted is verified
• User Protected: Whether the person who tweeted is protected
• User Followers Count: Number of followers of the person who tweeted
• User Friends Count: Number of friends of the person who tweeted
• User Statuses Count: Number of tweets of the person who tweeted
• User Favourites Count: Number of favourites of the person who tweeted
• Tweet Content: Content of the tweet
• Tweet Language: Language of the tweet
• Tweet Retweet Count: Number of retweets of the tweet
• Tweet Quote Count: Number of quotes of the tweet
• Tweet Reply Count: Number of replies of the tweet
• Tweet Like Count: Number of likes of the tweet
• Tweet ID: ID of the tweet
• Tweet URL: URL of the tweet
• Tweet Date: Date of the tweet

In August 2025, Google.com was the most visited website worldwide, with an average of 98.2 billion monthly visits. The platform has maintained its leading position since June 2010, when it surpassed Yahoo to take first place. YouTube ranked second during the same period, recording over 48 billion monthly visits. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

Corporate Online Language Learning Market Outlook

The corporate online language learning market size is projected to witness significant growth from 2023 to 2032, with a compound annual growth rate (CAGR) of 10.5%. In 2023, the global market was estimated at approximately USD 5.5 billion, and it is expected to reach around USD 14.5 billion by 2032. This growth is primarily driven by the increasing globalization of businesses, necessitating effective cross-cultural communication and language proficiency among corporate employees. As companies expand their operations worldwide, the demand for efficient and accessible language training solutions has surged, propelling the growth of the corporate online language learning market.

One of the primary growth factors for this market is the accelerating globalization of businesses, which has expanded international trade and collaboration to unprecedented levels. As companies seek to penetrate new markets and establish a global presence, the ability to communicate effectively in multiple languages has become crucial. Consequently, corporations are increasingly investing in language training programs to equip their employees with the necessary linguistic skills. The shift towards hybrid work models post-pandemic has further fueled the demand for online language learning solutions, as employees require flexible and accessible ways to enhance their language proficiency irrespective of their location. The integration of advanced technologies such as artificial intelligence and machine learning into language learning platforms has also contributed to their popularity, offering personalized and adaptive learning experiences that significantly improve language acquisition rates.

Another significant growth driver is the cost-effectiveness and scalability of online language learning solutions compared to traditional classroom-based training. Corporate organizations are realizing the financial and logistical benefits of adopting online platforms, which allow for a broader reach and consistent learning experiences across different geographies. The increasing reliance on digital communication tools in the workplace has also highlighted the importance of language proficiency, further reinforcing the need for online language training. Furthermore, the ability to track progress and assess performance through digital platforms provides corporations with valuable insights into employee development, enabling them to tailor language training programs to meet specific corporate objectives and individual learning needs.

The rise of remote work and the increasing emphasis on employee skill enhancement have also played a major role in driving the market forward. With more organizations adopting flexible work arrangements, the demand for self-paced and instructor-led online language courses has surged. These courses offer the convenience and flexibility that employees require to balance their professional commitments with personal development goals. Moreover, companies are increasingly recognizing the role of language proficiency in enhancing employee engagement and productivity, thereby boosting their overall competitiveness. As a result, investing in online language learning initiatives has become a strategic priority for many corporations aiming to foster an inclusive and culturally competent workforce.

The advent of Cloud-based English Language Learning solutions has revolutionized the way corporations approach language training. By leveraging cloud technology, these solutions offer unparalleled flexibility and accessibility, allowing employees to engage in language learning from any location with internet connectivity. This is particularly beneficial for companies with a geographically dispersed workforce, as it ensures consistent learning experiences across different regions. Cloud-based platforms also facilitate seamless updates and integration of new content, keeping the learning material relevant and up-to-date. Furthermore, the scalability of cloud solutions allows organizations to easily adjust the number of users and resources according to their evolving needs, making it a cost-effective option for both small and large enterprises. As the demand for English proficiency continues to rise in the global business landscape, cloud-based language learning solutions are becoming an essential tool for corporations aiming to enhance their employees' communication skills and competitive edge.

Regionally, North America and Europe are leading the corporate online language learning market, with