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 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.

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

This dataset was used in the manuscript "Scaling laws and dynamics of hashtags on Twitter"..

The Twitter data was obtained from a sample of 10% of all public tweets, provided by the Twitter streaming application programming interface. We extracted the hashtags from each tweet and counted how many times they were used in different time intervals. Time intervals of three different lengths were used: days, hours, and minutes. The tweets were published between November 1st 2015 and November 30th 2016, but not all time intervals between these dates are available.

The four files in this dataset correspond each to one folder (collected using tar). Each folder contains compressed .csv files (compressed using gzip). The content of the .csv files in each folder are:

hashtags_frequency_day.tar Counts of hashtags in each day. The name of each file in the folder indicates the date (GMT). The entries in each file are the hashtag and the count in the interval.

hashtags_frequency_hour.tar Counts of hashtags in each hour. The name of each file in the folder indicates the date (GMT). The entries in each file are the hashtag and the count in the interval.

hashtags_frequency_minutes.tar Counts of hashtags in each minute. The name of each file in the folder indicates the date (GMT, only a fraction of all days is available). The entries in each file are the hashtag and the count in the interval.

number_of_tweets.tar Counts of the number of tweets in each minute. The name of each file in the folder indicates the day. The entries in each file are the minute in the day (GMT) and count of tweets in our dataset.

X Premium subscription service to X (formerly Twitter) costing users ***** U.S. dollars per month. X Premium allows users to add a blue checkmark to their account, which was once a feature only given to verified profiles. The service also offers access to premium features, such as the ability to edit published tweets. As of April 2023, it was reported that there were around *** thousand X Premium subscribers.

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.

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 30th which yielded over 4 million tweets a day. We have added additional data provided by our new collaborators from January 27th to February 27th, to provide extra longitudinal coverage.

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 (101,400,452 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (20,244,746 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 total count of tweets and users by cancer types.

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

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.

Top 10 most tweeted dental papers.

This dataset contains 220,085 tweets containing the word vaccine between December 9th and December 18th 2021 at different times during each day, extracted using the Twitter API v2. Each tweet was extracted at least 3 days after its initial posting time in order to register 3 days of engagements, and it doesn't include retweets. Includes: Tweet ID Text Author ID Date Like count Retweet count Quote count Reply count User data (Followers, Following, Tweet count, Account creation date, Verified status) Usernames are hidden for privacy reasons

This is the data for "Effective tweeting strategies: making 140 characters count". Every line is the ID of a single tweet, which can be used to retrieve the original tweet and its metadata (such as the original poster, the number of retweets, and so on) via Twitter API or third party Twitter data resellers; the metadata retrieved using these IDs can be used to fully replicate our study. We cannot share the metadata directly because according to Twitter's terms and conditions, we can "only distribute or allow download of Tweet IDs and/or User IDs". The data is collected between Nov. 1, 2013 and Apr. 30, 2015 (18 months in total) for 258 accounts (media, companies, investors and CEOs) using Twitter's Streaming API. For every tweet and its retweets, the Tweet ID in this file includes the latest retweet (or if there are no retweets, it is the ID of the original tweet), such that the metadata for the corresponding tweet is the most up-to-date. There are 2,469,642 Tweet IDs enclosed; after purging invalid tweets (e.g., those having invalid timestamps), we use 2,452,120 tweets and the corresponding 121,772,646 user engagements (retweets, favorites, replies) in the paper. Please contact jxu5 at nd dot edu for more info.

This dataset consists of tweet identifiers for tweets harvested between November 28, 2016, following the election of Donald Trump through the end of the first 100 days of his administration. Data collection ended May 1, 2017.

Tweets were harvested using multiple methods described below. The total dataset consists of 218,273,152 tweets. Because of the different methods used to harvest tweets, there may be some duplication.

Methods Data were harvested from the Twitter API using the following endpoints:

search
timeline
filter

Three tweet sets were harvested using the search endpoint, which returns tweets that include a specific search term, user mention, hashtag, etc. The table below provides the search term, data collection dates, the total number of tweets in the corresponding tweet set, and the total number of unique Twitter users represented.

    Search term 
    Dates collected
    Count tweets
    Count unique users




    @realDonaldTrump user mention
    2016-11-28 - 2017-05-01
    4,597,326 
    1,501,806


    "Trump" in tweet text 
    2017-01-18 - 2017-05-01
    11,055,772 
    2,648,849


    #MAGA hashtag 
    2017-01-23 - 2017-05-01
    1,169,897 
    236,033

Two tweet sets were harvested using the timeline endpoint, which returns tweets published by specific users. The table below provides the user whose timeline was harvested, data collection dates, the total number of tweets in the corresponding tweet set, and the total number of unique Twitter users represented. Note that in these cases, tweets were necessarily limited to the one unique user whose tweets were harvested.

    User
    Dates collected
    Count tweets
    Count unique users




    realDonaldTrump
    2016-12-21 - 2017-05-01
    902
    1


    trumpRegrets
    2017-01-15 - 2017-05-01
    1,751
    1

The largest tweet set was harvested using the filter endpoint, which allows for streaming data access in near real time. Requests made to this API can be filtered to include tweets that meet specific criteria. The table below provides the filters used, data collection dates, the total number of tweets in the corresponding tweet set, and the total number of unique Twitter users represented.

Filtering via the API uses a default "OR," so the tweets included in this set satisfied any of the filter terms.

The script used to harvest streaming data from the filter API was built using the Python tweepy library.

    Filter terms
    Dates collected
    Count tweets
    Count unique users



    tweets by realDonaldTrump

    tweet mentions @realDonaldTrump

    'maga' in text

    'trump' in text

    'potus' in text

    2017-01-26 - 2017-05-01
    201,447,504 
    12,489,255

Harvested tweets, including all corresponding metadata, were stored in individual JSON files (one file per tweet).

Data Processing: Conversion to CSV format

Per the terms of Twitter's developer API, tweet datasets may be shared for academic research use. Sharing tweet data is limited to sharing the identifiers of tweets, which must be re-harvested to account for deletions and/or modifications of individual tweets. It is not permitted to share the originally harvested tweets in JSON format.

Tweet identifiers have been extracted from the JSON data and saved as plain text CSV files. The CSV files all have a single column:

id_str (string): A tweet identifier

The data include one tweet identifier per row.

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 yielding 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, and a cleaned version with no retweets. 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, the top 1000 bigrams, and the top 1000 trigrams. Some general statistics per day are included for both datasets. We will continue to update the dataset every two days here and weekly in Zenodo. For more information on processing and visualizations please visit: www.panacealab.org/covid19

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 statistic shows the leading Overwatch League teams on Twitter worldwide as of February 2018, ranked by number of followers. As of the measured period, the most followed Overwatch League team on Twitter was the San Francisco Shock, with 112 thousand fans, followed by the Dallas Fuel team, with 78.2 thousand followers.

Count of tweets captured each week by cancer type.

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.

Twitter counts used in the analysis.