[Paper Review] Soros, Child Sacrifices, and 5G: Understanding the Spread of Conspiracy Theories on Web Communities

Pujan Paudel, Jeremy Blackburn+3 more|arXiv (Cornell University)|Nov 3, 2021

Misinformation and Its Impacts4 citations

TL;DR

This paper presents a multi-platform Learning-to-Rank pipeline to detect and analyze conspiracy theory discussions across Reddit and Twitter, using 189 Snopes-debunked claims. It finds that mainstream subreddits like /r/worldnews and /r/politics are more influential in spreading conspiracies than conspiracy-specific communities, which primarily engage in deep-dive discussions but have limited reach.

ABSTRACT

This paper presents a multi-platform computational pipeline geared to identify social media posts discussing (known) conspiracy theories. We use 189 conspiracy claims collected by Snopes, and find 66k posts and 277k comments on Reddit, and 379k tweets discussing them. Then, we study how conspiracies are discussed on different Web communities and which ones are particularly influential in driving the discussion about them. Our analysis sheds light on how conspiracy theories are discussed and spread online, while highlighting multiple challenges in mitigating them.

Motivation & Objective

• To develop a scalable, cross-platform method for detecting conspiracy theory discussions on social media.
• To understand how different online communities discuss and propagate conspiracy theories.
• To identify which communities are most influential in spreading specific conspiracy theories.
• To assess the role of toxicity and language variation in conspiratorial discourse across platforms.

Proposed method

• A Learning-to-Rank model is trained to identify conspiracy-related content using features derived from text and engagement patterns.
• The system is applied across seven Reddit subreddits and Twitter, using 189 Snopes-debunked conspiracy claims as ground truth.
• Text embeddings and linguistic analysis are used to compare language styles between conspiracy-oriented and general-interest communities.
• Hawkes processes are employed to model and rank the influence of communities in triggering broader conspiracy discussions.
• Data collection spans from 2016 to 2021, capturing 66,274 Reddit posts, 288,721 comments, and 379,708 tweets.
• The pipeline generalizes well: training on Reddit data achieves strong performance on Twitter, enabling cross-platform detection.

Experimental results

Research questions

• RQ1 How do different online communities vary in their discussion of conspiracy theories in terms of duration, toxicity, and language use?
• RQ2 Which Web communities are most influential in spreading conspiracy theories across platforms?
• RQ3 To what extent do conspiracy-oriented subreddits differ in discourse style from general-interest communities?
• RQ4 How do language patterns in conspiratorial discussions vary between communities, and what do they reveal about engagement depth?
• RQ5 Can a model trained on one platform (e.g., Reddit) effectively detect conspiracy discussions on another (e.g., Twitter)?

Key findings

• 80% of conspiracy theory discussions on Reddit and Twitter persist for more than a year, indicating long-term endurance of such narratives.
• Reddit comments discussing conspiracy theories exhibit higher toxicity than general community discussions, though conspiracy posts themselves are the least toxic.
• Conspiracy-oriented subreddits like /r/conspiracy engage in detailed, investigative discussion, while mainstream subreddits like /r/worldnews and /r/Conservative primarily report and reference claims.
• /r/worldnews and /r/politics are the most influential communities for spreading Covid-19-related conspiracy theories.
• /r/Conservative is the most influential for Trump-related conspiracies, while /r/democrats is the least influential for such claims.
• Mainstream communities drive the majority of conspiracy theory spread, while dedicated conspiracy subreddits act as echo chambers with limited external influence.