An Early Look at the Parler Online Social Network

• URL: http://arxiv.org/abs/2101.03820v3
• Date: Thu, 18 Feb 2021 21:51:55 GMT
• Title: An Early Look at the Parler Online Social Network
• Authors: Max Aliapoulios, Emmi Bevensee, Jeremy Blackburn, Barry Bradlyn, Emiliano De Cristofaro, Gianluca Stringhini, Savvas Zannettou
• Abstract summary: Parler is an "alternative" social network promoting itself as a service that allows to "speak freely and express yourself openly" 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.
• Score: 10.683059193632943
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

Related papers

• Impact of Stricter Content Moderation on Parler's Users' Discourse [1.7863534204867277]
  We studied the moderation changes performed by Parler and their effect on the toxicity of its content. Our quasi-experimental time series analysis indicates that after the change in Parler's moderation, the severe forms of toxicity immediately decreased and sustained. We found an increase in the factuality of the news sites being shared, as well as a decrease in the number of conspiracy or pseudoscience sources being shared.
  arXiv  Detail & Related papers  (2023-10-13T04:09:39Z)
• Big Tech's Tightening Grip on Internet Speech [0.0]
  Control over online speech lies in the hands of a select few. Platforms have their own interests at stake. With control over online speech so centralized, online outcasts are left with few avenues for expression.
  arXiv  Detail & Related papers  (2023-06-05T13:47:12Z)
• A User-Driven Framework for Regulating and Auditing Social Media [94.70018274127231]
  We propose that algorithmic filtering should be regulated with respect to a flexible, user-driven baseline. We require that the feeds a platform filters contain "similar" informational content as their respective baseline feeds. We present an auditing procedure that checks whether a platform honors this requirement.
  arXiv  Detail & Related papers  (2023-04-20T17:53:34Z)
• Design and analysis of tweet-based election models for the 2021 Mexican legislative election [55.41644538483948]
  We use a dataset of 15 million election-related tweets in the six months preceding election day. We find that models using data with geographical attributes determine the results of the election with better precision and accuracy than conventional polling methods.
  arXiv  Detail & Related papers  (2023-01-02T12:40:05Z)
• "Gettr-ing" Deep Insights from the Social Network Gettr [10.667165962654996]
  Gettr hosts pro-Trump content mixed with conspiracy theories and attacks on the perceived "left" It's social network structure is asymmetric and centered around prominent right-thought leaders. While right-leaning users joined Gettr as a result of a perceived freedom of speech infringement by the mainstream platforms, left-leaning users followed them in numbers as to "keep up with the misinformation"
  arXiv  Detail & Related papers  (2022-04-08T13:34:57Z)
• Comparing the Language of QAnon-related content on Parler, Gab, and Twitter [68.8204255655161]
  Parler, a "free speech" platform popular with conservatives, was taken offline in January 2021 due to the lack of moderation of hateful and QAnon- and other conspiracy-related content. We compare posts with the hashtag #QAnon on Parler over a month-long period with posts on Twitter and Gab. Gab has the highest proportion of #QAnon posts with hate terms, and Parler and Twitter are similar in this respect. On all three platforms, posts mentioning female political figures, Democrats, or Donald Trump have more anti-social language than posts mentioning male politicians, Republicans, or
  arXiv  Detail & Related papers  (2021-11-22T11:19:15Z)
• An Early Look at the Gettr Social Network [11.319938541673578]
  We find that users on the platform heavily discuss politics, with a focus on the Trump campaign in the US and Bolsonaro's in Brazil. Although toxicity has been increasing over time, the average level of toxicity is still lower than the one recently observed on other fringe social networks like Gab and 4chan.
  arXiv  Detail & Related papers  (2021-08-12T17:49:30Z)
• News consumption and social media regulations policy [70.31753171707005]
  We analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation. Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content. The lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior.
  arXiv  Detail & Related papers  (2021-06-07T19:26:32Z)
• Capitol (Pat)riots: A comparative study of Twitter and Parler [37.277566049536]
  On 6 January 2021, a mob of right-wing conservatives stormed the USA Capitol Hill interrupting the session of congress certifying 2020 Presidential election results. Immediately after the start of the event, posts related to the riots started to trend on social media. Our report presents a contrast between the trending content on Parler and Twitter around the time of riots.
  arXiv  Detail & Related papers  (2021-01-18T07:46:14Z)
• Privacy-Aware Recommender Systems Challenge on Twitter's Home Timeline [47.434392695347924]
  RecSys 2020 Challenge organized by ACM RecSys in partnership with Twitter using this dataset. This paper touches on the key challenges faced by researchers and professionals striving to predict user engagements.
  arXiv  Detail & Related papers  (2020-04-28T23:54:33Z)
• Echo Chambers on Social Media: A comparative analysis [64.2256216637683]
  We introduce an operational definition of echo chambers and perform a massive comparative analysis on 1B pieces of contents produced by 1M users on four social media platforms. We infer the leaning of users about controversial topics and reconstruct their interaction networks by analyzing different features. We find support for the hypothesis that platforms implementing news feed algorithms like Facebook may elicit the emergence of echo-chambers.
  arXiv  Detail & Related papers  (2020-04-20T20:00:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.