[Paper Review] An Early Look at the Parler Online Social Network

Max Aliapoulios, Emmi Bevensee+5 more|arXiv (Cornell University)|Jan 11, 2021

Misinformation and Its Impacts27 references49 citations

TL;DR

This paper releases a large Parler dataset (183M posts from 4M users and 13.25M profiles) and provides initial analysis showing conservative/Trump content, growth around political events, and prevalence of conspiracy theories. It also documents moderation features and data collection ethics.

ABSTRACT

Parler is as an "alternative" social network promoting itself as a service that allows to "speak freely and express yourself openly, without fear of being deplatformed for your views." Because of this promise, the platform become popular among users who were suspended on mainstream social networks for violating their terms of service, as well as those fearing censorship. In particular, the service was endorsed by several conservative public figures, encouraging people to migrate from traditional social networks. After the storming of the US Capitol on January 6, 2021, Parler has been progressively deplatformed, as its app was removed from Apple/Google Play stores and the website taken down by the hosting provider. This paper presents a dataset of 183M Parler posts made by 4M users between August 2018 and January 2021, as well as metadata from 13.25M user profiles. We also present a basic characterization of the dataset, which shows that the platform has witnessed large influxes of new users after being endorsed by popular figures, as well as a reaction to the 2020 US Presidential Election. We also show that discussion on the platform is dominated by conservative topics, President Trump, as well as conspiracy theories like QAnon.

Motivation & Objective

• Motivate the study of Parler as an emerging, politically polarized platform with free-speech rhetoric.
• Provide a large, FAIR-aligned dataset of Parler posts, comments, and user profiles for research use.
• Characterize user demographics, moderation features, and content themes in the early Parler ecosystem.

Proposed method

• Crawling the undocumented Parler API with a custom crawler to collect /v1/post, /v1/comment, and /v1/user data.
• Collecting 183,056,617 posts and 84,546,856 comments from 4,079,765 users plus metadata for 13.25M profiles.
• Standardizing fields (timestamps, upvotes, scores, followers/followings) and enriching posts with profile context.
• Publishing a dataset under FAIR principles with a DOI and open access for reuse.
• Providing descriptive analyses of bios, bans, badges, follower/following distributions, and growth events.
• Noting ethical considerations and limitations of sampling (non-representative samples possible).

Experimental results

Research questions

• RQ1 What does Parler’s user base look like in terms of bios, badges, and moderation flags?
• RQ2 How does Parler’s content evolve over time, especially around political events and deplatforming?
• RQ3 Which domains and hashtags are most shared, and what do they reveal about user topics (Trump support, QAnon, etc.)?
• RQ4 How does platform moderation (bans, pending status, keyword filters) operate and affect user activity?
• RQ5 How does user growth correlate with external events and platform endorsements?

Key findings

• Parler hosts 183M posts from 4M users (Aug 2018–Jan 2021) and profile metadata for 13.25M accounts; growth spikes align with external events and endorsements.
• Bios show notable presence of conservatives, Trump supporters, patriots, and religious identifiers; gold/verified badges correlate with higher activity and larger follower counts.
• Bans affect 2.09% of users, with most banned accounts private; some bans reflect impersonation violations, indicating active moderation.
• Posts and comments receive substantial upvotes (e.g., 18% of posts have zero upvotes; 61% of posts have at least 10 upvotes; comments rarely negative), suggesting positive reception of content.
• Hashtags on posts emphasize Trump, MAGA, and conspiracy topics like QAnon; comments feature the #parlerconcierge and related community dynamics.
• URLs show mixed sharing of mainstream (YouTube, Twitter) and alternative sources (BitChute, Breitbart), indicating a diverse content ecosystem.