During the beginning of the launch, they had some pretty fast growth. Here are the key Truth Social statistics you need to know.

How does Truth Social compare to other social media platforms? There are around 2 million active Truth Social users.

We've put together a list of the latest Truth Social statistics so you can see who uses the platform and whether or not Truth Social is likely to become a dominant social media network in the future.

A survey done in March 2022 found that 31% of Republican voters said they would use Truth Social often and 14% said they plan to use the platform a lot.

You might be surprised how much Truth Social is worth based on its small number of users.

Truth Social, the social media platform launched by U.S. President Donald Trump, has seen fluctuating download numbers since its inception in February 2022. In March 2025, Truth Social recorded approximately ******* Apple App Store downloads and ******* downloads from the and Google Play Store in the United States. User adoption and brand awareness Despite its high-profile launch, Truth Social has struggled to gain widespread adoption. A May 2022 survey found that only ***** percent of U.S. respondents were registered users of the platform, with a slight gender disparity showing **** percent of male respondents having accounts compared to *** percent of female respondents. Brand awareness, however, was higher, with ** percent of U.S. social media users recognizing Truth Social when presented with its logo and name. Generational difference Truth Social's reception varies significantly across age groups and political affiliations. An October 2024 survey revealed that millennials had the most positive opinion of the platform, with **** percent viewing it favorably, followed by **** percent of Generation X and **** percent of Baby Boomers.

A Truth Social data set containing a network of users, their associated posts, and additional information about each post. Collected from February 2022 through September 2022, this dataset contains 454,458 user entries and 845,060 Truth (Truth Social’s term for post) entries.

Comprised of 12 different files, the entry count for each file is shown below.

File	Data Points
users.tsv	454,458
follows.tsv	4,002,115
truths.tsv	823,927
quotes.tsv	10,508
replies.tsv	506,276
media.tsv	184,884
hashtags.tsv	21,599
external_urls.tsv	173,947
truth_hashtag_edges.tsv	213,295
truth_media_edges.tsv	257,500
truth_external_url_edges.tsv	252,877
truth_user_tag_edges.tsv	145,234

A readme file is provided that describes the structure of the files, necessary terms, and necessary information about the data collection.

As of **************, over ** percent of global Truth Social users belonged to the 55 to 64 year age group, making this the largest audience base of the social media platform owned by former president Donald Trump. Users aged 18 to 24 years accounted for just **** percent of users.

In May 2022, an online survey in the United States found that only three percent of white and Hispanic respondents were registered users of social media app Truth Social. Truth Social was launched in February 2022 by former U.S. President Donald Trump. Approximately four percent of Black respondents were registered users of Truth Social.

Overview:

This dataset contains posts and interactions from Donald J. Trump's Truth Social account, specifically during his 2024 U.S. Presidential election campaign. Each post entry provides detailed information, including the post content, number of replies, shares, likes, and metadata such as post date, media URLs (if available), and account details. The data offers a rich source for analyzing political messaging, engagement metrics, and audience reactions during the campaign period.

Use Cases:

• Sentiment Analysis: The dataset can be used to analyze public sentiment toward Trump's campaign, identifying patterns in positive or negative reactions to different posts.
• Political Messaging Analysis: Researchers can study the nature of Trump's political communication strategies, including the themes and issues emphasized during the 2024 campaign.
• Engagement Metrics: By analyzing the number of likes, replies, and shares, this dataset allows for a detailed understanding of public engagement with Trump's posts over time.
• Media Influence Study: With data on video and image URLs, this dataset could be used to assess the impact of multimedia on audience reactions and interaction.

Source:

The posts are sourced directly from Trump's official Truth Social profile, capturing interactions that are publicly available.

Limitations:

The dataset may not include every post or interaction due to scraping limitations, and some interactions might lack context or additional details that could affect interpretability.

License:

This dataset is intended for research and analysis purposes. Please ensure that any use of the data complies with Truth Social's terms of service and applicable copyright laws.

Truth Social Dataset (Limited Version)

License: CC BY 4.0

  Overview

This dataset contains posts and comments scraped from Truth Social, focusing on Donald Trump’s posts (“Truths” and “Retruths”).Due to the initial collection method, all media and URLs were excluded. Future versions will include complete post data, including images and links. Contains 31.8Million Comments, and over 18000 Posts all By Trump. As well as logged over 1.5Million unique users who commented on… See the full description on the dataset page: https://huggingface.co/datasets/notmooodoo9/TrumpsTruthSocialPosts.

This dataset contains the predicted prices of the asset Truth Social over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Source

This folder contains network data for relationships between President Donald Trump and other people, which was originally compiled by John Templon, Anthony Cormier, Alex Campbell, and Jeremy Singer-Vine as part of a larger project of mapping "TrumpWorld" for BuzzFeed News.

The full dataset, which you can access as a Google Sheet or on GitHub also includes information about organizations and agencies. The data was compiled by culling from "public records, news reports, and other sources on the Trump family, his Cabinet picks, and top advisers," as well as via crowdsourced tips and information from the public (if you have any more, you can contribute them here).

Data & Methodology

Nodes: 303; unimodal

Edges: 366; unweighted; undirected

The nodes csv contains 303 different people, and the edges csv contains 366 unweighted relationships between those people, such as friendship, business partner, donor, parent/child, cabinet member, spouse, and more. This information about the relationships, along with the sources from which they were identified, is included as a column (and potential attribute) in the edges csv.

As stated above, the data was compiled by culling from "public records, news reports, and other sources on the Trump family, his Cabinet picks, and top advisers," as well as via crowdsourced tips.

*In order to make this data more accessible for basic social network analysis, I have condensed the network to only the top 303 most connected people in TrumpWorld.

Background & Significance

The relationships between President Donald Trump and other people lend themselves well to basic social network analysis because, as Templon, Cormier, Campbell, and Singer-Vine suggest, "No American president has taken office with a giant network of businesses, investments, and corporate connections like that amassed by Donald J. Trump."

Further, the social network analysis of some of the most powerful people in the nation and the world might help contribute to what Lauren Klein called for at the end of her 2018 MLA talk "Distant Reading After Moretti"--that is, computational analysis "trained on power."

Acknowlegement

Foto von Marco Zuppone auf Unsplash

This study examines how US President Donald Trump uses Truth Social as a strategic tool of power politics to spread his populist rhetoric during his New York civil fraud case. Drawing on van Dijk’s socio-cognitive approach to Critical Discourse Analysis and Mudde’s (2004, 2007) conceptualization of populism, we analyze 218 posts from Trump’s personal account (September 2022-February 2024) to examine how his discourse constructs ideological divides and reinforces his political narrative. The findings reveal that Trump systematically employs positive self-presentation and negative other-presentation to contrast himself and his supporters—the ‘authentic people’—against ‘corrupt elites,’ framing his legal troubles as emblematic of systemic persecution. His rhetoric is further characterized by strategic victimhood, in which he casts himself as the target of political persecution, aligning personal grievances with his followers’ collective identity. Additionally, Trump’s frequent use of derogatory labels functions linguistically to delegitimize opponents and intensify his ‘us vs. them’ framing. By integrating CDA with populism theory, this study contributes to scholarship on political communication by demonstrating how platform-specific discourse fuses personal and collective victimhood to mobilize support, reshape followers’ mental models of political conflict, and heighten ideological polarization.

Research-and-Development Time Series for Trump Media & Technology Group Corp.. Trump Media & Technology Group Corp. engages in social media and streaming services in the United States. The company operates Truth Social, a social media platform for free expression; and Truth+, a streaming platform focusing on news, Christian content, and family friendly programming. It also offers Truth.Fi, a financial service and FinTech brand that incorporates America First investment vehicles. Trump Media & Technology Group Corp. was founded in 2021 and is headquartered in Sarasota, Florida.

com-LiveJournal: LiveJournal social network and ground-truth communities

LiveJournal is a free on-line blogging community where users declare friendship each other. LiveJournal also allows users form a group which other members can then join. We consider such user-defined groups as ground-truth communities. We provide the LiveJournal friendship social network and ground-truth communities.

We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

com-Friendster: Friendster social network and ground-truth communities

Friendster is an on-line gaming network. Before re-launching as a game website, Friendster was a social networking site where users can form friendship edge each other. Friendster social network also allows users form a group which other members can then join. We consider such user-defined groups as ground-truth communities. For the social network, we take the induced subgraph of the nodes that either belong to at least one community or are connected to other nodes that belong to at least one community. This data is provided by The Web Archive Project, where the full graph is available.

We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

com-Orkut: Orkut social network and ground-truth communities

Orkut is a free on-line social network where users form friendship each other. Orkut also allows users form a group which other members can then join. We consider such user-defined groups as ground-truth communities. We provide the Orkut friendship social network and ground-truth communities. This data is provided by Alan Mislove et al.

We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

com-Youtube: Youtube social network and ground-truth communities

Youtube is a video-sharing web site that includes a social network. In the Youtube social network, users form friendship each other and users can create groups which other users can join. We consider such user-defined groups as ground-truth communities. This data is provided by Alan Mislove et al.

We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

com-DBLP: DBLP collaboration network and ground-truth communities

The DBLP computer science bibliography provides a comprehensive list of research papers in computer science. We construct a co-authorship network where two authors are connected if they publish at least one paper together. Publication venue, e.g, journal or conference, defines an individual ground-truth community; authors who published to a certain journal or conference form a community.

We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

com-Amazon: Amazon product co-purchasing network and ground-truth communities

Network was collected by crawling Amazon website. It is based on Customers Who Bought This Item Also Bought feature of the Amazon website. If a product i is frequently co-purchased with product j, the graph contains an undirected edge from i to j. Each product category provided by Amazon defines each ground-truth community.

We regard each connected component in a product category as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

email-Eu-core: email-Eu-core network

The network was generated using email data from a large European research institution. We have anonymized information about all incoming and outgoing email between members of the research institution. Th...

Youtube social network and ground-truth communities

https://snap.stanford.edu/data/com-Youtube.html

Dataset information

Youtube (http://www.youtube.com/) is a video-sharing web site that includes a social network. In the Youtube social network, users form friendship each other and users can create groups which other users can join. We consider
such user-defined groups as ground-truth communities. This data is provided by Alan Mislove et al.
(http://socialnetworks.mpi-sws.org/data-imc2007.html)

We regard each connected component in a group as a separate ground-truth
community. We remove the ground-truth communities which have less than 3
nodes. We also provide the top 5,000 communities with highest quality
which are described in our paper (http://arxiv.org/abs/1205.6233). As for
the network, we provide the largest connected component.

Network statistics
Nodes 1,134,890
Edges 2,987,624
Nodes in largest WCC 1134890 (1.000)
Edges in largest WCC 2987624 (1.000)
Nodes in largest SCC 1134890 (1.000)
Edges in largest SCC 2987624 (1.000)
Average clustering coefficient 0.0808
Number of triangles 3056386
Fraction of closed triangles 0.002081
Diameter (longest shortest path) 20
90-percentile effective diameter 6.5
Community statistics
Number of communities 8,385
Average community size 13.50
Average membership size 0.10

Source (citation)
J. Yang and J. Leskovec. Defining and Evaluating Network Communities based on Ground-truth. ICDM, 2012. http://arxiv.org/abs/1205.6233

Files
File Description
com-youtube.ungraph.txt.gz Undirected Youtube network
com-youtube.all.cmty.txt.gz Youtube communities
com-youtube.top5000.cmty.txt.gz Youtube communities (Top 5,000)

Notes on inclusion into the SuiteSparse Matrix Collection, July 2018:

The graph in the SNAP data set is 1-based, with nodes numbered 1 to
1,157,827.

In the SuiteSparse Matrix Collection, Problem.A is the undirected Youtube
network, a matrix of size n-by-n with n=1,134,890, which is the number of
unique user id's appearing in any edge.

Problem.aux.nodeid is a list of the node id's that appear in the SNAP data set. A(i,j)=1 if person nodeid(i) is friends with person nodeid(j). The
node id's are the same as the SNAP data set (1-based).

C = Problem.aux.Communities_all is a sparse matrix of size n by 16,386
which represents the communities in the com-youtube.all.cmty.txt file.
The kth line in that file defines the kth community, and is the column
C(:,k), where C(i,k)=1 if person ...

Ebitda Time Series for Trump Media & Technology Group Corp.. Trump Media & Technology Group Corp. engages in social media and streaming services in the United States. The company operates Truth Social, a social media platform for free expression; and Truth+, a streaming platform focusing on news, Christian content, and family friendly programming. It also offers Truth.Fi, a financial service and FinTech brand that incorporates America First investment vehicles. Trump Media & Technology Group Corp. was founded in 2021 and is headquartered in Sarasota, Florida.

LiveJournal social network and ground-truth communities

https://snap.stanford.edu/data/com-LiveJournal.html

Dataset information

LiveJournal (http://www.livejournal.com/) is a free on-line blogging
community where users declare friendship each other. LiveJournal also
allows users form a group which other members can then join. We consider
such user-defined groups as ground-truth communities. We provide the
LiveJournal friendship social network and ground-truth communities.

We regard each connected component in a group as a separate ground-truth
community. We remove the ground-truth communities which have less than 3
nodes. We also provide the top 5,000 communities with highest quality
which are described in our paper (http://arxiv.org/abs/1205.6233). As for
the network, we provide the largest connected component.

Dataset statistics
Nodes 3,997,962
Edges 34,681,189
Nodes in largest WCC 3997962 (1.000)
Edges in largest WCC 34681189 (1.000)
Nodes in largest SCC 3997962 (1.000)
Edges in largest SCC 34681189 (1.000)
Average clustering coefficient 0.2843
Number of triangles 177820130
Fraction of closed triangles 0.04559
Diameter (longest shortest path) 17
90-percentile effective diameter 6.5

Source (citation)
J. Yang and J. Leskovec. Defining and Evaluating Network Communities based on Ground-truth. ICDM, 2012. http://arxiv.org/abs/1205.6233

Files
File Description
com-lj.ungraph.txt.gz Undirected LiveJournal network
com-lj.all.cmty.txt.gz LiveJournal communities
com-lj.top5000.cmty.txt.gz LiveJournal communities (Top 5,000)

Notes on inclusion into the SuiteSparse Matrix Collection, July 2018:

The graph in the SNAP data set is 0-based, with nodes numbering 0 to
4,036,537.

In the SuiteSparse Matrix Collection, Problem.A is the undirected
LiveJournal network, a matrix of size n-by-n with n=3,997,962, which is
the number of unique user id's appearing in any edge.

Problem.aux.nodeid is a list of the node id's that appear in the SNAP data set. A(i,j)=1 if person nodeid(i) is friends with person nodeid(j). The
node id's are the same as the SNAP data set (0-based).

C = Problem.aux.Communities_all is a sparse matrix of size n by 664,414
which represents the communities in the com-lj.all.cmty.txt file. The kth line in that file defines the kth community, and is the column C(:,k),
where C(i,k)=1 if person nodeid(i) is in the kth community. Row C(i,:)
and row/column i of the A matrix thus refer to the same person, nodeid(i).

Ctop = Problem.aux.Communities_top5000 is n-by-5000, with the same
structure as the C array above, with the content of the
com-lj.top5000.cmty.txt file.

Review of Economics and Statistics: Forthcoming.