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Shifts in Toxic Behavior on Reddit and Wikipedia

Study reveals changing patterns of toxicity on Reddit and Wikipedia over time.

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Table of Contents

Social media platforms have become a key part of our lives, yet there’s growing concern about toxic or harmful behavior in these spaces. This article looks into how such behavior, known as Toxicity, has changed over time on two major platforms: Reddit and Wikipedia.

The Scope of the Study

Over 14 years, nearly 500 million Comments from Reddit and Wikipedia were examined to analyze patterns of toxicity. Two different measurements were used to evaluate the level of harmful behavior in comments: a toxicity score from the Perspective API and a downvote metric based on user voting.

The study focused on how individual Users’ behavior changed throughout their time on these sites. Surprisingly, users who were around before 2013 tended to show less toxic behavior over time. In contrast, users who joined after 2013 started to behave more toxic as they spent more time on the platform.

Key Findings

  1. Changing Behavior Over Time: Users showed a clear shift in behavior based on when they joined. For those active before 2013, the longer they engaged with the platforms, the less toxic they became. After that year, a reverse trend emerged, leading to increased toxicity over time.

  2. Reddit vs. Wikipedia: The nature of toxic behavior varied between the two platforms. On Reddit, users with a high volume of comments were more likely to display toxic behavior, whereas on Wikipedia, it was the opposite. More active contributors on Wikipedia tended to be less toxic than their less active counterparts.

  3. Influence of Context: Discussions around widely shared content also reflected similar toxicity patterns as individual user comments. The environment and type of interaction influenced the amount of toxicity observed.

Understanding Toxicity

The term toxicity can be tricky. It often lacks a clear definition, making it challenging to measure. The Perspective API provides a specific definition, identifying toxic comments as hateful, aggressive, or disrespectful. This clarity helps in analyzing behavior over extensive data.

Comparing Users and Their Behavior

The study focuses on different levels of activity among users. High-activity users (those who comment frequently) have shown to have higher toxicity scores on Reddit. On the other hand, Wikipedia’s high-activity users were less toxic and seemed to follow stricter norms.

Interestingly, both platforms experienced the same general pattern over time. Users who started before 2013 tended to become less toxic, and users who started later showed an increase in toxicity as they continued to engage.

Tracking Content and Discussions

It’s not just users who change over time; the content and discussions also evolve. Discussions about specific links or topics can vary in toxicity. For instance, URLs shared on Reddit that generated more comments tended to have higher toxicity scores as well.

Using data from various URLs, the trends mirrored those seen with user behavior. Discussions around certain content became increasingly toxic over time.

Exploring Other Metrics

While the focus was on toxicity scores and downvote rates, other measures were also looked at. These included banned users, comments that didn't follow guidelines, and other forms of antisocial behavior. Most studies on this topic examine patterns at the community level rather than looking carefully at individual users over time.

Conclusions

The findings reveal important insights about user behavior on social media. Users' levels of toxicity are influenced by how long they are active on a platform and when they joined. The changes observed in user behavior, especially around 2013, may relate to broader shifts in social media culture and user demographics.

It's essential to understand that the landscape of social media is always changing. The community norms and the interactions users have can significantly impact how they behave over time.

Overall, the exploration of toxicity on social media platforms like Reddit and Wikipedia illustrates a complex picture. While some users may become more toxic over time, others might follow different paths based on their activity level and the norms of the specific platform they are part of. This highlights the importance of ongoing research to better grasp user behavior and the dynamics of social media interactions.

Original Source

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

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.

Authors: Katy Blumer, Jon Kleinberg

Last Update: 2024-07-12 00:00:00

Language: English

Source URL: https://arxiv.org/abs/2407.09365

Source PDF: https://arxiv.org/pdf/2407.09365

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to arxiv for use of its open access interoperability.

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