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.

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

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.

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, 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.

This is the breakdown of Twitter users by age group.

This dataset contains statistics related to the Unleashed Twitter account (@SAUnleashed). Unleashed is an open data competition, an initiative of the Office for Digital Government, Department of the Premier and Cabinet. The data is used to monitor the level of engagement activity with the audience, and make the communication effective in regards to the event.

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

Introduction

X Statistics (Twitter): X, previously referred to as Twitter, is the platform where the first tweet was posted by Jack Dorsey (the CEO of Twitter) on March 21, 2006. It took a total of 3 years, 2 months, and 1 day to achieve the significant milestone of one billion tweets on the platform.

Twitter became a publicly traded company in November 2013. Its user engagement increased a year later, with daily tweets increasing from 20,000 to 60,000 during the South by Southwest conference. Since that time, it has changed into a primary venue for users to share their daily experiences, discuss their interests, and connect with individuals globally. At that point, Twitter had approximately 200 million users.

Elon Musk acquired Twitter for $44 billion to change it into a private entity. Following this acquisition, multiple changes have occurred, including the rebranding to X. Currently, X ranks among the top six social networking applications in the United States, boasting over 500 million users worldwide.

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.

Due to the relevance of the COVID-19 global pandemic, we are releasing our dataset of tweets acquired from the Twitter Stream related to COVID-19 chatter. The first 9 weeks of data (from January 1st, 2020 to March 11th, 2020) contain very low tweet counts as we filtered other data we were collecting for other research purposes, however, one can see the dramatic increase as the awareness for the virus spread. Dedicated data gathering started from March 11th to March 29th which yielded over 4 million tweets a day.

The data collected from the stream captures all languages, but the higher prevalence are: English, Spanish, and French. We release all tweets and retweets on the full_dataset.tsv file (70,569,368 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (13,535,912 unique tweets). There are several practical reasons for us to leave the retweets, tracing important tweets and their dissemination is one of them. For NLP tasks we provide the top 1000 frequent terms in frequent_terms.csv, the top 1000 bigrams in frequent_bigrams.csv, and the top 1000 trigrams in frequent_trigrams.csv. Some general statistics per day are included for both datasets in the statistics-full_dataset.tsv and statistics-full_dataset-clean.tsv files.

More details can be found (and will be updated faster at: https://github.com/thepanacealab/covid19_twitter)

As always, the tweets distributed here are only tweet identifiers (with date and time added) due to the terms and conditions of Twitter to re-distribute Twitter data. The need to be hydrated to be used.

At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of interest to the platform's future buyers, but also of high relevance to the Computational Social Science research community. For example, how many active users does the platform have? What percentage of accounts on the site are bots? And, what are the dominating topics and sub-topical spheres on the platform? In a globally coordinated effort of 80 scholars to shed light on these questions, and to offer a dataset that will equip other researchers to do the same, we have collected 375 million tweets published within a 24-hour time period starting on September 21, 2022. To the best of our knowledge, this is the first complete 24-hour Twitter dataset that is available for the research community. With it, the present work aims to accomplish two goals. First, we seek to answer the aforementioned questions and provide descriptive metrics about Twitter that can serve as references for other researchers. Second, we create a baseline dataset for future research that can be used to study the potential impact of the platform's ownership change.

Due to the relevance of the COVID-19 global pandemic, we are releasing our dataset of tweets acquired from the Twitter Stream related to COVID-19 chatter. The first 9 weeks of data (from January 1st, 2020 to March 11th, 2020) contain very low tweet counts as we filtered other data we were collecting for other research purposes, however, one can see the dramatic increase as the awareness for the virus spread. Dedicated data gathering started from March 11th to March 22nd which yielded over 4 million tweets a day.

The data collected from the stream captures all languages, but the higher prevalence are: English, Spanish, and French. We release all tweets and retweets on the full_dataset.tsv file (40,823,816 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (7,479,940 unique tweets). There are several practical reasons for us to leave the retweets, tracing important tweets and their dissemination is one of them. For NLP tasks we provide the top 1000 frequent terms in frequent_terms.csv, the top 1000 bigrams in frequent_bigrams.csv, and the top 1000 trigrams in frequent_trigrams.csv. Some general statistics per day are included for both datasets in the statistics-full_dataset.tsv and statistics-full_dataset-clean.tsv files.

More details can be found (and will be updated faster at: https://github.com/thepanacealab/covid19_twitter)

As always, the tweets distributed here are only tweet identifiers (with date and time added) due to the terms and conditions of Twitter to re-distribute Twitter data. The need to be hydrated to be used.

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

Utilize our Tweets dataset for a range of applications to enhance business strategies and market insights. Analyzing this dataset offers a comprehensive view of social media dynamics, empowering organizations to optimize their communication and marketing strategies. Access the full dataset or select specific data points tailored to your needs. Popular use cases include sentiment analysis to gauge public opinion and brand perception, competitor analysis by examining engagement and sentiment around rival brands, and crisis management through real-time tracking of tweet sentiment and influential voices during critical events.

Twitter is a social news website. It can be viewed as a hybrid of email, instant messaging and sms messaging all rolled into one neat and simple package. It s a new and easy way to discover the latest news related to subjects you care about. |Attribute|Value| |-|-| |Number of Nodes: |11316811| |Number of Edges: |85331846| |Missing Values? |no| |Source:| N/A| ##Data Set Information: 1. nodes.csv — it s the file of all the users. This file works as a dictionary of all the users in this data set. It s useful for fast reference. It contains all the node ids used in the dataset 2. edges.csv — this is the friendship/followership network among the users. The friends/followers are represented using edges. Edges are directed. Here is an example. 1,2 This means user with id "1" is followering user with id "2". ##Attribute Information: Twitter is a social news website. It can be viewed as a hybrid of email, instant messaging and sms messaging all rolled into one ne

How many people use X/Twitter?

As of the first quarter of 2019, X/Twitter averaged 330 million monthly active users, a decline from its all-time high of 336 MAU in the first quarter of 2018. As of the first quarter of 2019, the company switched its user reporting metric to monetizable daily active users (mDAU).

X/Twitter

X/Twitter is a social networking and microblogging service, enabling registered users to read and post short messages called tweets. X/Twitter messages are limited to 280 characters and users are also able to upload photos or short videos. Tweets are posted to a publicly available profile or can be sent as direct messages to other users.

Part of the social platform’s appeal is the ability of users to follow any other user with a public profile, enabling users to interact with celebrities who regularly post on the social media site. Currently, the most-followed person on Twitter is singer Katy Perry with more than 107 million followers. Twitter has also become an important communications channel for governments and heads of state – U.S. President Donald Trump was the most-followed world leader on Twitter, followed by Pope Francis and Indian Prime Minister Narendra Modi.

Despite the widespread usage among the rich and famous, the decline in active users has not been impressing investors as the platform is largely reliant on delivering advertising to users in order to generate revenues. Twitter’s company revenue in 2018 amounted to three billion U.S. dollars, up from 2.44 billion in the preceding fiscal year. Twitter was only recently able to report a positive annual result for the first time, when the company generated 1.2 billion U.S. dollars in net income in 2018.

In early 2025, something fascinating happened at a small community center in suburban Ohio. A town hall meeting about local road closures suddenly went viral, not because of the topic, but because a 74-year-old attendee live-tweeted the entire event using her iPad. Within hours, her posts racked up thousands of...

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.