[2407.09365] Tracking Patterns in Toxicity and Antisocial Behavior Over User Lifetimes on Large Social Media Platforms

Skip to main content

Search arXiv

Press Enter to search · Advanced search

-->

Computer Science > Social and Information Networks

arXiv:2407.09365 (cs)

[Submitted on 12 Jul 2024 (v1), last revised 21 Sep 2025 (this version, v2)]

Title:Tracking Patterns in Toxicity and Antisocial Behavior Over User Lifetimes on Large Social Media Platforms

Authors:Katy Blumer, Jon Kleinberg<br>View a PDF of the paper titled Tracking Patterns in Toxicity and Antisocial Behavior Over User Lifetimes on Large Social Media Platforms, by Katy Blumer and Jon Kleinberg

View PDF<br>HTML (experimental)

Abstract:An increasing amount of attention has been devoted to the problem of "toxic" or antisocial behavior on social media. In this paper we analyze such behavior at very large scales: we analyze toxicity over a 14-year time span on nearly 500 million comments from Reddit and Wikipedia, grounded in two different proxies for toxicity.

At the individual level, we analyze users' toxicity levels over the course of their time on the site, and find a striking reversal in trends: both Reddit and Wikipedia users tended to become less toxic over their life cycles on the site in the early (pre-2013) history of the site, but more toxic over their life cycles in the later (post-2013) history of the site. We also find that toxicity on Reddit and Wikipedia differ in a key way, with the most toxic behavior on Reddit exhibited in aggregate by the most active users, and the most toxic behavior on Wikipedia exhibited in aggregate by the least active users. Finally, we consider the toxicity of discussion around widely-shared pieces of content, and find that the trends for toxicity in discussion about content bear interesting similarities with the trends for toxicity in discussion by users.

Subjects:

Social and Information Networks (cs.SI); Computers and Society (cs.CY); Human-Computer Interaction (cs.HC)

Cite as:<br>arXiv:2407.09365 [cs.SI]

(or<br>arXiv:2407.09365v2 [cs.SI] for this version)

https://doi.org/10.48550/arXiv.2407.09365

Focus to learn more

arXiv-issued DOI via DataCite

Journal reference:<br>Sci. Rep. 15 (2025), 25369

Related DOI:

https://doi.org/10.1038/s41598-025-07086-3

Focus to learn more

DOI(s) linking to related resources

Submission history<br>From: Katy Blumer [view email]<br>[v1]<br>Fri, 12 Jul 2024 15:45:02 UTC (24,419 KB)

[v2]<br>Sun, 21 Sep 2025 23:38:27 UTC (5,824 KB)

Full-text links:<br>Access Paper:

View a PDF of the paper titled Tracking Patterns in Toxicity and Antisocial Behavior Over User Lifetimes on Large Social Media Platforms, by Katy Blumer and Jon Kleinberg<br>View PDF<br>HTML (experimental)<br>TeX Source

view license

Current browse context:

cs.SI

next >

new<br>recent<br>| 2024-07

Change to browse by:

cs<br>cs.CY<br>cs.HC

References & Citations

NASA ADS<br>Google Scholar

Semantic Scholar

export BibTeX citation<br>Loading...

BibTeX formatted citation

&times;

loading...

Data provided by:

Bookmark

Bibliographic Tools

Bibliographic and Citation Tools

Bibliographic Explorer Toggle

Bibliographic Explorer (What is the Explorer?)

Connected Papers Toggle

Connected Papers (What is Connected Papers?)

Litmaps Toggle

Litmaps (What is Litmaps?)

scite.ai Toggle

scite Smart Citations (What are Smart Citations?)

Code, Data, Media

Code, Data and Media Associated with this Article

alphaXiv Toggle

alphaXiv (What is alphaXiv?)

Links to Code Toggle

CatalyzeX Code Finder for Papers (What is CatalyzeX?)

DagsHub Toggle

DagsHub (What is DagsHub?)

GotitPub Toggle

Gotit.pub (What is GotitPub?)

Huggingface Toggle

Hugging Face (What is Huggingface?)

ScienceCast Toggle

ScienceCast (What is ScienceCast?)

Demos

Demos

Replicate Toggle

Replicate (What is Replicate?)

Spaces Toggle

Hugging Face Spaces (What is Spaces?)

Spaces Toggle

TXYZ.AI (What is TXYZ.AI?)

Related Papers

Recommenders and Search Tools

Link to Influence Flower

Influence Flower (What are Influence Flowers?)

Core recommender toggle

CORE Recommender (What is CORE?)

Author

Venue

Institution

Topic

About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Which authors of this paper are endorsers? |<br>Disable MathJax (What is MathJax?)

Major funding support from