As of October 2025, micro-blogging platform X (formerly Twitter) was more popular with men than women, with male audiences accounting for 64.4 percent of global users. Additionally, users between the ages of 25 and 34 were particularly active on X/Twitter, making up more than 37 percent of users worldwide. How many people use? Although X/Twitter holds its status as a mainstream social media site, it falls short in comparison to other well-known platforms in terms of user numbers. As of early 2022, X/Twitter had around 436 million monthly active users, whilst Meta’s Facebook reached almost three billion MAU. Overall, the United States is home to over 105 million X/Twitter users, making up Twitter’s largest audience base, followed by Japan, India, and the United Kingdom, respectively. How is Twitter used? X/Twitter is utilized by its audience for many different purposes. In May 2021, over 80 percent of high-volume X/Twitter users (defined as users who tweet around 20 times per month) in the United States reported using the platform for entertainment, whilst 78 percent said they used it as a way to stay informed. High-volume X/Twitter users were far more likely to use the service as a means of expressing their opinion. Furthermore, in 2022, over half of social media users in the U.S. used Twitter as a news resource.  

As of February 2025, men accounted for 63 percent of X, formerly Twitter, users in the United States. Additionally, the U.S. was home to the world's largest Twitter audience, with over 105 million users in early 2024.

The platform is male-dominated with 68.1% of all Twitter users being male. Just 31.9% of Twitter users are female.

As of February 2025, 24.5 percent of X (formerly Twitter) users were men aged between 25 and 34 years. Overall, almost 19 percent of users were men aged between 18 and 24 years. X has a high share of male users when compared to other popular social media platforms.

The US has historically been the target country for Twitter since its launch in 2006. This is the full breakdown of Twitter users by country.

This is the breakdown of Twitter users by age group.

As of February 2025, 37.5 percent of X’s (formerly Twitter) global audience was aged between 25 and 34 years. The second-largest age group demographic on the platform was represented by users aged between 18 and 24 years, with a share of 32.1 percent. Users aged less than 18 years accounted for two percent of users, while those aged 50 or older accounted for roughly 7.3 percent. X is a male-dominated platform As of January 2024, more than 60 percent of X users were male. Although all mainstream social media platforms tend to have a slightly more male-skewing audience, X stands out above Instagram, Snapchat, TikTok, and Facebook when it comes to user gender demographics. Overall, Pinterest is the only mainstream platform to have a higher share of female users. X Blue for you It is not uncommon for social media users to now have the chance to become subscribers of their chosen online networks for a monthly fee. X Blue is a subscription service from X that gives users special benefits and features. A blue verification mark, edit post functionality, fewer ads, priority ranking in chats, and longer video upload times are some of the perks offered.

These are the key Twitter user statistics that you need to know.

An anonymised dataset with 80 profile features (including age and gender) for over 80K twitter Dutch users. The method for extracting the Demographic data is explained in the paper below: https://ieeexplore.ieee.org/document/8752947.

The features of lexical diversity are extracted using the textstat_lexdiv() function from the Quanteda library in R.

[63] "ntoken"
[64] "ntype"
[65] "document"
[66] "TTR"
[67] "C"
[68] "R"
[69] "CTTR"
[70] "U"
[71] "S"
[72] "K"
[73] "I"
[74] "D"
[75] "Vm"
[76] "Maas"
[77] "lgV0"
[78] "lgeV0"

Twitter is ranked as the 12h most popular social media site in the world. The platform currently has 611 million active monthly users.

To disseminate research, scholars once relied on university media services or journal press releases, but today any academic can turn to Twitter to share their published work with a broader audience. The possibility that scholars can push their research out, rather than hope that it is pulled in, holds the potential for scholars to draw wide attention to their research. In this manuscript, we examine whether there are systematic differences in the types of scholars who most benefit from this push model. Specifically, we investigate the extent to which there are gender differences in the dissemination of research via Twitter. We carry out our analyses by tracking tweet patterns for articles published in six journals across two fields (political science and communication), and we pair this Twitter data with demographic and educational data about the authors of the published articles, as well as article citation rates. We find considerable evidence that, overall, article citations are positively correlated with tweets about the article, and we find little evidence to suggest that author gender affects the transmission of research in this new media.

One of the biggest advantages of Twitter is the speed at which information can be passed around. People use Twitter primarily to get news and for entertainment. This is the breakdown of why people use Twitter today.

Advertising makes up 89% of its total revenue and data licensing makes up about 11%.

In February 2025, X/Twitter was much more popular with male users in the Nordics than female users. In Sweden, men made up 72.1 percent of X/Twitter's audience, whilst in the Greenland, men accounted for 78.1 percent of users. Overall, Finland had the largest share of female X/Twitter users, who made up just under 41 percent of the platform's user base.

The US has the largest number of Twitter users with over a 100 million users. They account for about 16.7% of all Twitter users worldwide.

With over 611 million monthly active users, building a huge Twitter following is not an easy task. These are the top 25 accounts with the most followers on Twitter right now.

This dataset includes the identifiers of sampled Twitter users, labeled by means of crowd sourcing with respect to the personal attributes of age, gender, ethnicity, family status, education, income level, and political orientation.

Context

For a Springboard project. Potentially part of a larger project to infer demographic information based on the text that people write. And hopefully generate some sociolinguistic insights in the process. Some of the code associated with this project (including most of the code used to generate these data) is in this Github repository, but it is still a bit of a mess.

Content

The files contain the text of tweets downloaded via the Twitter API between 2019-05-21 and 2019-06-01, with a user ID and timestamp to identify each tweet, and an indicator of whether the user appeared (based on the display name) to be male or female. The tweets are limited to English, original tweets (i.e., not retweets) associated with users whose first names could be identified by the gender-guesser package as male or female. (Names are not included.) Tweets are divided into train, validation, and test sets by time and user ID. (In other words, there should be no overlap in time or user ID between the files, and the sequence from train to validation to test should be strictly forward in time.) The tweets in each file have been selected to be evenly balanced between those identified as male and female (which usually means keeping all the "female" tweets and selecting a random subset of the "male" ones. Tweets have been preprocessed (using a script copied from Timothy Renner) to remove hashtags, mentions, URLs, media, and symbols.

Acknowledgements

I thank Twitter, Kaggle, the authors and maintainers of the gender-guesser package, the users who wrote the tweets, and all the various open source people who work on the packages that make data munging possible for those who can't afford fancy software.

Inspiration

How well can we train a machine learning model to guess the gender of Twitter users based on the text of their tweets? And what can such models tell us about the gender sociolinguistics of Twitter users?

In the most recently measured period, almost 45 percent of all global Twitter employees were women. Additionally, for technical roles, 30.9 percent were women, and in leadership roles, 39 percent were women. Overall, less than one percent of employees at Twitter identified as non-binary or non-conforming.

As of February 2025, **** percent of X users identified as male, while ** percent identified as female.