As of December 2022, X/Twitter's audience accounted for over *** million monthly active users worldwide. This figure was projected to ******** to approximately *** million by 2024, a ******* of around **** percent compared to 2022.

Social network X/Twitter is particularly popular in the United States, and as of February 2025, the microblogging service had an audience reach of 103.9 million users in the country. Japan and the India were ranked second and third with more than 70 million and 25 million users respectively. Global Twitter usage As of the second quarter of 2021, X/Twitter had 206 million monetizable daily active users worldwide. The most-followed Twitter accounts include figures such as Elon Musk, Justin Bieber and former U.S. president Barack Obama. X/Twitter and politics X/Twitter has become an increasingly relevant tool in domestic and international politics. The platform has become a way to promote policies and interact with citizens and other officials, and most world leaders and foreign ministries have an official Twitter account. Former U.S. president Donald Trump used to be a prolific Twitter user before the platform permanently suspended his account in January 2021. During an August 2018 survey, 61 percent of respondents stated that Trump's use of Twitter as President of the United States was inappropriate.

This is the breakdown of Twitter users by age group.

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.

As of February 2025, micro-blogging platform X (formerly Twitter) was more popular with men than women, with male audiences accounting for 63.7 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.  

These Twitter user statistics will give you the complete story of where Twitter is at today and what the future looks like for the social media company.

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.

Demographic data prediction is powered by Demografy AI that extracts demographic data from names with 100% coverage, accuracy preview before purchase and GDPR-compliance.

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We collected the data of a Twitter user using Tweepy to access the Twitter API. We crawled the list of each user account’s followers. Twitter allowed a request of a maximum of 200 tweets per time window and because of limitations of the Twitter API, we could only make a request every 15 minutes. Next, we obtained the most recent tweets of each user in the study. We extracted the most common hashtags used in the sample tweets and crawled the most recent 50 tweets that contained each hashtag and tweets that mentioned a particular user, for example ’@username.’ Initially, we chose 101 user accounts and documented the attributes of each user’s account (number of followers, a list of followers, and the recent tweets of each follower).

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.

Information represented through conventional text may fall short of capturing the attention and promoting engagement with today’s digital audience. Transforming text into visual tools, such as infographics, has emerged as a simplified method of delivering information to attract a broader audience and enhance information dissemination. The first step to evaluate the potential value of infographics is to quantify their appeal and engagement rates over conventional text. This retrospective pilot analysis sought to evaluate the difference between engagement rates for tweets containing an of infographic compared to tweets containing a link to a peer-reviewed journal article. A total of 752 tweets were published within the study period; of these, 40 tweets met inclusion criteria. When engagement rates were compared, there was an increase in median engagement rates for tweets containing an infographic compared to a tweet linked to a peer-reviewed article at 10.97% (IQR 3.47%) and 5.33% (IQR 3.17%), respectively. This pilot study provides insight on the potential impact for infographics to enhance engagement rate, which may subsequently correlate with an increase in audience reach and readership. Prospective studies are needed to validate the utility of infographics in promoting scholarship publicity, learner engagement, and as a transferable pedagogical tool to educate medical practitioners.

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.

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

This is the dataset for the article "A Predictive Method to Improve the Effectiveness of Twitter Communication in a Cultural Heritage Scenario".

Abstract:

Museums are embracing social technologies in the attempt to broaden their audience and to engage people. Although social communication seems an easy task, media managers know how hard it is to reach millions of people with a simple message. Indeed, millions of posts are competing every day to get visibility in terms of likes and shares and very little research focused on museums communication to identify best practices. In this paper, we focus on Twitter and we propose a novel method that exploits interpretable machine learning techniques to: (a) predict whether a tweet will likely be appreciated by Twitter users or not; (b) present simple suggestions that will help enhancing the message and increasing the probability of its success. Using a real-world dataset of around 40,000 tweets written by 23 world famous museums, we show that our proposed method allows identifying tweet features that are more likely to influence the tweet success.

Code to run a selection of experiments is available at https://github.com/rmartoglia/predict-twitter-ch

Dataset structure

The dataset contains the dataset used in the experiments of the above research paper. Only the extracted features for the museum tweet threads (and not the message full text) are provided and needed for the analyses.

We selected 23 well known world spread art museums and grouped them into five groups: G1 (museums with at least three million of followers); G2 (museums with more than one million of followers); G3 (museums with more than 400,000 followers); G4 (museums with more that 200,000 followers); G5 (Italian museums). From these museums, we analyzed ca. 40,000 tweets, with a number varying from 5k ca. to 11k ca. for each museum group, depending on the number of museums in each group.

Content features: these are the features that can be drawn form the content of the tweet itself. We further divide such features in the following two categories:

– Countable: these features have a value ranging into different intervals. We take into consideration: the number of hashtags (i.e., words preceded by #) in the tweet, the number of URLs (i.e., links to external resources), the number of images (e.g., photos and graphical emoticons), the number of mentions (i.e., twitter accounts preceded by @), the length of the tweet;

– On-Off : these features have binary values in {0, 1}. We observe whether the tweet has exclamation marks, question marks, person names, place names, organization names, other names. Moreover, we also take into consideration the tweet topic density: assuming that the involved topics correspond to the hashtags mentioned in the text, we define a tweet as dense of topics if the number of hashtags it contains is greater than a given threshold, set to 5. Finally, we observe the tweet sentiment that might be present (positive or negative) or not (neutral).

Context features: these features are not drawn form the content of the tweet itself and might give a larger picture of the context in which the tweet was sent. Namely, we take into consideration the part of the day in which the tweet was sent (morning, afternoon, evening and night respectively from 5:00am to 11:59am, from 12:00pm to 5:59pm, from 6:00pm to 10:59pm and from 11pm to 4:59am), and a boolean feature indicating whether the tweet is a retweet or not.

User features: these features are proper of the user that sent the tweet, and are the same for all the tweets of this user. Namely we consider the name of the museum and the number of followers of the user.

As of September 2023, it was found that 42 percent of adults in the United States aged between 18 and 29 years used X (formerly Twitter). This age group was the microblogging service’s biggest audience in the United States, followed by a 27 percent usage reach among 30 to 49-year-olds. X users in the United StatesAs of the first quarter of 2019, Twitter had 68 million monthly active users in the United States. In the fourth quarter of 2020, the number of monetizable daily active Twitter users in the country amounted to 37 million. As of January 2021, 61.6 percent of U.S. Twitter audiences were male and 38.4 percent were female. According to a February 2019 survey of social media users in the United States, Twitter was the most popular social network for news consumption. X usage in the United StatesTwitter is popular among users looking to catch up and chime in on current and trending topics and live-tweet about events and media. Live-tweeting television series or sporting events is a popular user activity and in 2018, the most popular television series based on average number of Twitter interactions per episode was ABC’s ‘The Bachelor’. In terms of global sporting events, it does not get much bigger than the Olympic Games. During the Winter Olympics in PyeongChang 2018, Twitter accounted for 50 percent of stakeholder posts during the Winter.

This dataset is a collection of scraped public twitter updates used in coordination with an academic project to study the geolocation data related to twittering. From the explanatory PDF in the dataset collection: We provide both training set and test set (collected from September 2009 to January 2010) in the paper You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users in CIKM 2010. The training set contains 115,886 Twitter users and 3,844,612 updates from the users. All the locations of the users are self-labeled in United States in city-level granularity. The test set contains 5,136 Twitter users and 5,156,047 tweets from the users. All the locations of users are uploaded from their smart phones with the form of "UT: Latitude,Longitude". Please cite the following paper when using the dataset. Z. Cheng, J. Caverlee, and K. Lee. You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users. In Proceeding of the 19th ACM Conference on Information and Knowledge Management (CIKM), Toronto, Oct 2010. (Bibtex)

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.

The global number of Twitter users in was forecast to continuously increase between 2024 and 2028 by in total 74.3 million users (+17.32 percent). After the ninth consecutive increasing year, the Twitter user base is estimated to reach 503.42 million users and therefore a new peak in 2028. Notably, the number of Twitter users of was continuously increasing over the past years.User figures, shown here regarding the platform twitter, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Twitter users in countries like South America and the Americas.

This dataset comprises a set of information cascades generated by Singapore Twitter users. Here a cascade is defined as a set of tweets about the same topic.

This dataset was collected via the Twitter REST and streaming APIs in the following way. Starting from popular seed users (i.e., users having many followers), we crawled their follow, retweet, and user mention links. We then added those followers/followees, retweet sources, and mentioned users who state Singapore in their profile location. With this, we have a total of 184,794 Twitter user accounts. Then tweets are crawled from these users from 1 April to 31 August 2012. In all, we got 32,479,134 tweets.

To identify cascades, we extracted all the URL links and hashtags from the above tweets. And these URL links and hashtags are considered as the identities of cascades. In other words, all the tweets which contain the same URL link (or the same hashtag) represent a cascade. Mathematically, a cascade is represented as a set of user-timestamp pairs. Figure 1 provides an example, i.e. cascade C = {< u1, t1 >, < u2, t2 >, < u1, t3 >, < u3, t4 >, < u4, t5 >}.