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.

This statistic shows a ranking of the estimated number of Twitter users in 2020 in Asia, differentiated by country. The user numbers 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 more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

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.

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.

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

Social media companies are starting to offer users the option to subscribe to their platforms in exchange for monthly fees. Until recently, social media has been predominantly free to use, with tech companies relying on advertising as their main revenue generator. However, advertising revenues have been dropping following the COVID-induced boom. As of September, Meta Verified is the most costly of the subscription services, setting users back almost 15 U.S. dollars per month on iOS or Android for the standard subscription. Twitter Blue costs between three and 40 U.S. dollars per month and ensures users will receive the blue check mark, and have the ability to edit tweets and have NFT profile pictures.

In 2024, posts on X (formerly Twitter) generated an average of 31.46 likes, down from 37.82 likes in 2023. Mentions and reposts also declines year-over-year, and in 2024, the average post on the platform received 1.56 likes and 8.47 mentions.

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

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.

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.

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.

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.

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.

In 2024, X (formerly Twitter) posts had an average of 3.4 replies, up from an average of 1.64 replies in 2023. Elon Musk's X account is the profile with the most followers on the platform.

Tweet IDs from political Twitter, March 2020 This dataset contains the Twitter tweet IDs used in a study investigating the extent to which problematic information is present in the most engaged-with content in political and issue spaces on Twitter in the run-up to the 2020 US elections. These tweets were returned from running in DMI-TCAT a curated list of queries for political candidates, political parties and social issues, incorporating politician-specific, party-specific and issue-specific keywords and hashtags. The shared URLs dataset was collected during a three-week timeframe (March 2-22, 2020, or around Super Tuesday) and contains only the tweet IDs that contain a URL.

This is the Twitter Parliamentarian Database: a database consisting of parliamentarian names, parties and twitter ids from the following countries: Austria, Belgium, France, Denmark, Spain, Finland, Germany, Greece, Italy, Malta, Poland, Netherlands, United Kingdom, Ireland, Sweden, New Zealand, Turkey, United States, Canada, Australia, Iceland, Norway, Switzerland, Luxembourg, Latvia and Slovenia. In addition, the database includes the European Parliament.The tweet ids from the politicans' tweets have been collected from September 2017 - 31 October 2019 (all_tweet_ids.csv). In compliance with Twitter's policy, we only store tweet ids, which can be re-hydrated into full tweets using existing tools. More information on how to use the database can be found in the readme.txt.It is recommended that you use the .csv files to work with the data, rather than the SQL tables. Information on the relations in the SQL database can be found in the Database codebook.pdf.Update:The tweet ids for 2021 have been added as '2021.csv'Update #2:The tweet ids for 2020 have been added as '2020.csv'The last party table has been added as 'parties_2021_04_28.csv'The last members table has been added as 'members_2021_04_28.csv'

The current dataset contains Tweet IDs for tweets mentioning "COVID" (e.g., COVID-19, COVID19) and shared between March and July of 2020.Sampling Method: hourly requests sent to Twitter Search API using Social Feed Manager, an open source software that harvests social media data and related content from Twitter and other platforms.NOTE: 1) In accordance with Twitter API Terms, only Tweet IDs are provided as part of this dataset. 2) To recollect tweets based on the list of Tweet IDs contained in these datasets, you will need to use tweet 'rehydration' programs like Hydrator (https://github.com/DocNow/hydrator) or Python library Twarc (https://github.com/DocNow/twarc). 3) This dataset, like most datasets collected via the Twitter Search API, is a sample of the available tweets on this topic and is not meant to be comprehensive. Some COVID-related tweets might not be included in the dataset either because the tweets were collected using a standardized but intermittent (hourly) sampling protocol or because tweets used hashtags/keywords other than COVID (e.g., Coronavirus or #nCoV). 4) To broaden this sample, consider comparing/merging this dataset with other COVID-19 related public datasets such as: https://github.com/thepanacealab/covid19_twitter https://ieee-dataport.org/open-access/corona-virus-covid-19-tweets-dataset https://github.com/echen102/COVID-19-TweetIDs