The number of Twitter users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 0.9 million users (+5.1 percent). After the ninth consecutive increasing year, the Twitter user base is estimated to reach 18.55 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).

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.

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.

The undertaking of several studies of political phenomena in social media mandates the operationalization of the notion of political stance of users and contents involved. Relevant examples include the study of segregation and polarization online, the study of political diversity in content diets in social media, or AI explainability. While many research designs rely on operationalizations best suited for the US setting, few allow addressing more general design, in which users and content might take stances on multiple ideology and issue dimensions, going beyond traditional Liberal-Conservative or Left-Right scales. To advance the study of more general online ecosystems, we present a dataset of X/Twitter population of users in the French political Twittersphere and web domains embedded in a political space spanned by dimensions measuring attitudes towards immigration, the EU, liberal values, elites and institutions, nationalism and the environment. We provide several benchmarks validating the positions of these entities (based on both, LLM and human annotations), and discuss several applications for this dataset.

Utilize our Twitter dataset for diverse applications to enrich business strategies and market insights. Analyzing this dataset provides a comprehensive understanding of social media trends, empowering organizations to refine their communication and marketing strategies. Access the entire dataset or customize a subset to fit your needs. Popular use cases include market research to identify trending topics and hashtags, AI training by reviewing factors such as tweet content, retweets, and user interactions for predictive analytics, and trend forecasting by examining correlations between specific themes and user engagement to uncover emerging social media preferences.

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.

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

This is a version 2 dataset of paired OpenAlex author IDs (https://docs.openalex.org/about-the-data/author) and Twitter (now X) user IDs

Major update in this version

Following the significant update to OpenAlex's author identification system, the scholars on Twitter dataset, which previously linked Twitter IDs to OpenAlex author IDs, immediately became outdated. This called for a new approach to re-establish these links, as the absence of new Twitter data made it impossible to replicate the original method of matching Twitter profiles with scholarly authors. To navigate this challenge, a bridge was constructed between the June 2022 snapshot of the OpenAlex database—used in the original matching process—and the most recent snapshot from February 2024. This bridge utilized OpenAlex works IDs and DOIs to match authors in both datasets by their shared publications and identical primary names. When a connection was established between two authors with the same name, the new OpenAlex author ID was assigned to the corresponding Twitter ID. When direct matches based on primary names were not found, an attempt was made to establish connections by matching the names from June 2022 with any corresponding alternative names found in the 2024 dataset. This method ensured continuity of identity through the system update, adapting the strategy to link profiles across the temporal divide created by the database's overhaul.

Our efficient method for re-establishing links between author IDs and Twitter profiles has been notably successful, managing to rematch 432,417 (88%) OpenAlex author IDs. This effort successfully restored connections for 388,968 unique Twitter users, which represents 92% of the original dataset. Of these, 375,316 were matched using their primary names, and 57,101 through alternative names. The simplicity and quick execution of this approach led to exceptionally favourable results, with a minimal loss of only 8% of the original Twitter-linked scholarly accounts.

The dataset includes 432,417 unique author_ids and 388,968 unique tweeter_ids forming 462,427 unique author-tweeter pairs.

File descriptions

• authors_tweeters_2024_02.csv is the actual dataset of author IDs paired with tweeter IDs. The "alternative" column indicates if the match was made with the primary name (0) or an alternate name (1).
• mapping_tweeters_2022_2024.csv contains the relationship made between the 2022 author IDs and the 2024 author IDs, including the names.

How to cite

When using the dataset, please cite the following article providing details about the matching process:

During the first half of 2024, there were a total of ****** data requests for X (formerly Twittter) account information from governments with ***** of these were requested by the United States government. A further ***** were requested by the Japanese government, while ***** were requested by the European Union. Overall, ***** percent of these requests resulted in data being disclosed to the relevant authorities.

The number of Twitter users in the United States was forecast to continuously increase between 2024 and 2028 by in total 4.3 million users (+5.32 percent). After the ninth consecutive increasing year, the Twitter user base is estimated to reach 85.08 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 Canada and Mexico.

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.

The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, 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 and count multiple accounts by persons only once.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).

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.

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.

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

The number of Twitter users in France was forecast to continuously increase between 2024 and 2028 by in total *** million users (+**** percent). After the ninth consecutive increasing year, the Twitter user base is estimated to reach ***** 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 *** 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 Luxembourg and Netherlands.

*** Fake News on Twitter ***

These 5 datasets are the results of an empirical study on the spreading process of newly fake news on Twitter. Particularly, we have focused on those fake news which have given rise to a truth spreading simultaneously against them. The story of each fake news is as follow:

1- FN1: A Muslim waitress refused to seat a church group at a restaurant, claiming "religious freedom" allowed her to do so.

2- FN2: Actor Denzel Washington said electing President Trump saved the U.S. from becoming an "Orwellian police state."

3- FN3: Joy Behar of "The View" sent a crass tweet about a fatal fire in Trump Tower.

4- FN4: The animated children's program 'VeggieTales' introduced a cannabis character in August 2018.

5- FN5: In September 2018, the University of Alabama football program ended its uniform contract with Nike, in response to Nike's endorsement deal with Colin Kaepernick.

The data collection has been done in two stages that each provided a new dataset: 1- attaining Dataset of Diffusion (DD) that includes information of fake news/truth tweets and retweets 2- Query of neighbors for spreaders of tweets that provides us with Dataset of Graph (DG).

DD

DD for each fake news story is an excel file, named FNx_DD where x is the number of fake news, and has the following structure:

The structure of excel files for each dataset is as follow:

Each row belongs to one captured tweet/retweet related to the rumor, and each column of the dataset presents a specific information about the tweet/retweet. These columns from left to right present the following information about the tweet/retweet:

User ID (user who has posted the current tweet/retweet)

The description sentence in the profile of the user who has published the tweet/retweet

The number of published tweet/retweet by the user at the time of posting the current tweet/retweet

Date and time of creation of the account by which the current tweet/retweet has been posted

Language of the tweet/retweet

Number of followers

Number of followings (friends)

Date and time of posting the current tweet/retweet

Number of like (favorite) the current tweet had been acquired before crawling it

Number of times the current tweet had been retweeted before crawling it

Is there any other tweet inside of the current tweet/retweet (for example this happens when the current tweet is a quote or reply or retweet)

The source (OS) of device by which the current tweet/retweet was posted

Tweet/Retweet ID

Retweet ID (if the post is a retweet then this feature gives the ID of the tweet that is retweeted by the current post)

Quote ID (if the post is a quote then this feature gives the ID of the tweet that is quoted by the current post)

Reply ID (if the post is a reply then this feature gives the ID of the tweet that is replied by the current post)

Frequency of tweet occurrences which means the number of times the current tweet is repeated in the dataset (for example the number of times that a tweet exists in the dataset in the form of retweet posted by others)

State of the tweet which can be one of the following forms (achieved by an agreement between the annotators):

r : The tweet/retweet is a fake news post

a : The tweet/retweet is a truth post

q : The tweet/retweet is a question about the fake news, however neither confirm nor deny it

n : The tweet/retweet is not related to the fake news (even though it contains the queries related to the rumor, but does not refer to the given fake news)

DG

DG for each fake news contains two files:

A file in graph format (.graph) which includes the information of graph such as who is linked to whom. (This file named FNx_DG.graph, where x is the number of fake news)

A file in Jsonl format (.jsonl) which includes the real user IDs of nodes in the graph file. (This file named FNx_Labels.jsonl, where x is the number of fake news)

Because in the graph file, the label of each node is the number of its entrance in the graph. For example if node with user ID 12345637 be the first node which has been entered into the graph file then its label in the graph is 0 and its real ID (12345637) would be at the row number 1 (because the row number 0 belongs to column labels) in the jsonl file and so on other node IDs would be at the next rows of the file (each row corresponds to 1 user id). Therefore, if we want to know for example what the user id of node 200 (labeled 200 in the graph) is, then in jsonl file we should look at row number 202.

The user IDs of spreaders in DG (those who have had a post in DD) would be available in DD to get extra information about them and their tweet/retweet. The other user IDs in DG are the neighbors of these spreaders and might not exist in DD.

As of February 2025, approximately 34.2 percent of X (formerly Twitter) users in the United Kingdom (UK) were women. By comparison, male users on the social network accounted for 65.8 percent of total users.