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...

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.

According to a survey conducted in March 2023, 40 percent of X (formerly Twitter) users reported it was extremely or very likely that they would still be using the platform in a year's time. Overall, 35 percent said it was somewhat likely, and one-quarter of respondents stated it was not very likely, or not likely at all.

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.

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.

This is the breakdown of Twitter users by age group.

According to a survey conducted in March 2023, 69 percent of female X/Twitter users had taken a break from the platform for several weeks or more in the past 12 months, compared to 54 percent of male users. Overall 46 percent of male users reported they had not taken a break from X/Twitter within the past year.

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

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

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.

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.

During the first half of 2024 there were 34,497 pieces of content removed from X due to personal privacy violations, which include the publishing or sharing of other people's private information. These types of violations are also known as doxxing. Overall, 30,450 of these pieces of content were reported manually by users of the platform.

Between February and July 2024, there were an average of 67 million active logged in users of X (formerly Twitter) in the European Union. Overall, there were 38.9 million logged out guests, amounting to a total of 105.9 million average monthly active recipients of the service (AMARS). In the EU, for the measured time period, the average monthly active recipients of X peaked between February and July 2023, reaching over 112 million.

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

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.

Tweets scraped will all possible datapoints provided by twitter in each tweet. For data extraction or scraping contact me on telegram - @akaseobhw

All datapoints present for each tweet.

Each entry in the dataset represents a tweet along with various attributes such as the tweet's ID, URL, text content, retweet count, reply count, like count, quote count, view count, creation date, language, and more. Additionally, there are details about the tweet's author, including their username, profile URL, follower count, following count, profile picture, cover picture, description, location, creation date, and more.

Here's a brief description of the key fields present in each tweet entry:

• type: Indicates the type of data, in this case, it's a tweet.
• id: Unique identifier for the tweet.
• url: URL of the tweet.
• twitterUrl: Twitter URL of the tweet.
• text: Text content of the tweet.
• retweetCount: Number of retweets.
• replyCount: Number of replies.
• likeCount: Number of likes (favorites).
• quoteCount: Number of times the tweet has been quoted.
• viewCount: Number of views.
• createdAt: Date and time when the tweet was created.
• lang: Language of the tweet.
• quoteId: ID of the quoted tweet, if this tweet is a quote.
• bookmarkCount: Number of times the tweet has been bookmarked.
• isReply: Indicates whether the tweet is a reply to another tweet.
• author: Information about the author of the tweet.
  • userName: Username of the author.
  • url: URL of the author's profile.
  • followers: Number of followers of the author.
  • following: Number of accounts the author is following.
  • profilePicture: URL of the author's profile picture.
  • coverPicture: URL of the author's cover picture.
  • description: Description or bio of the author.
  • location: Location of the author.
  • createdAt: Date and time when the author's account was created.
• entities: Entities present in the tweet, such as hashtags, symbols, URLs, and user mentions.
• isRetweet: Indicates whether the tweet is a retweet.
• isQuote: Indicates whether the tweet is a quote.
• quote: Information about the quoted tweet, if this tweet is a quote.
• media: Information about any media (such as images or videos) attached to the tweet.

This dataset can be analyzed to gain insights into trends, sentiments, and user behavior on Twitter. You can use Python libraries like pandas to load this dataset and perform various analyses and visualizations.

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.

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.

In 2024, accounts on X (formerly Twitter) posted an average of 3.55 times per week, down from 5.73 times per week in 2023. In October 2022, Elon Musk acquired Twitter for 44 billion US dollars.

This dataset comprises a set of Twitter accounts in Singapore that are used for social bot profiling research conducted by the Living Analytics Research Centre (LARC) at Singapore Management University (SMU). Here a bot is defined as a Twitter account that generates contents and/or interacts with other users automatically (at least according to human judgment). In this research, Twitter bots have been categorized into three major types:

Broadcast bot. This bot aims at disseminating information to general audience by providing, e.g., benign links to news, blogs or sites. Such bot is often managed by an organization or a group of people (e.g., bloggers). Consumption bot. The main purpose of this bot is to aggregate contents from various sources and/or provide update services (e.g., horoscope reading, weather update) for personal consumption or use. Spam bot. This type of bots posts malicious contents (e.g., to trick people by hijacking certain account or redirecting them to malicious sites), or promotes harmless but invalid/irrelevant contents aggressively.

This categorization is general enough to cater for new, emerging types of bot (e.g., chatbots can be viewed as a special type of broadcast bots). The dataset was collected from 1 January to 30 April 2014 via the Twitter REST and streaming APIs. Starting from popular seed users (i.e., users having many followers), their follow, retweet, and user mention links were crawled. The data collection proceeds by adding those followers/followees, retweet sources, and mentioned users who state Singapore in their profile location. Using this procedure, a total of 159,724 accounts have been collected. To identify bots, the first step is to check active accounts who tweeted at least 15 times within the month of April 2014. These accounts were then manually checked and labelled, of which 589 bots were found. As many more human users are expected in the Twitter population, the remaining accounts were randomly sampled and manually checked. With this, 1,024 human accounts were identified. In total, this results in 1,613 labelled accounts. Related Publication: R. J. Oentaryo, A. Murdopo, P. K. Prasetyo, and E.-P. Lim. (2016). On profiling bots in social media. Proceedings of the International Conference on Social Informatics (SocInfo’16), 92-109. Bellevue, WA. https://doi.org/10.1007/978-3-319-47880-7_6