Fringe communities promoting conspiracy theories and extremist ideologies
have thrived on mainstream platforms, raising questions about the mechanisms
driving their growth. Here, we hypothesize and study a possible mechanism: new
members may be recruited through fringe-interactions: the exchange of comments
between members and non-members of fringe communities. We apply text-based
causal inference techniques to study the impact of fringe-interactions on the
growth of three prominent fringe communities on Reddit: r/Incel,
r/GenderCritical, and r/The_Donald. Our results indicate that
fringe-interactions attract new members to fringe communities. Users who
receive these interactions are up to 4.2 percentage points (pp) more likely to
join fringe communities than similar, matched users who do not.
This effect is influenced by 1) the characteristics of communities where the
interaction happens (e.g., left vs. right-leaning communities) and 2) the
language used in the interactions. Interactions using toxic language have a 5pp
higher chance of attracting newcomers to fringe communities than non-toxic
interactions. We find no effect when repeating this analysis by replacing
fringe (r/Incel, r/GenderCritical, and r/The_Donald) with non-fringe
communities (r/climatechange, r/NBA, r/leagueoflegends), suggesting this growth
mechanism is specific to fringe communities. Overall, our findings suggest that
curtailing fringe-interactions may reduce the growth of fringe communities on
mainstream platforms.

边缘社区通过交换评论吸引新成员是推动边缘社区增长的机制之一。当有毒语言被使用时，这种相互作用会对边缘社区的吸引新成员的能力产生更大的影响。总体而言，阻止边缘相互作用可能会减少主流平台上边缘社区的增长。

陌生人危险！与边缘用户的跨社区互动增加了 Reddit 上边缘社区的增长

Stranger Danger! Cross-Community Interactions with Fringe Users Increase  the Growth of Fringe Communities on Reddit

Recent work in cognitive science has uncovered a diversity of explanatory
values, or dimensions along which we judge explanations as better or worse. We
propose a Bayesian account of how these values fit together to guide
explanation. The resulting taxonomy provides a set of predictors for which
explanations people prefer and shows how core values from psychology,
statistics, and the philosophy of science emerge from a common mathematical
framework. In addition to operationalizing the explanatory virtues associated
with, for example, scientific argument-making, this framework also enables us
to reinterpret the explanatory vices that drive conspiracy theories, delusions,
and extremist ideologies.

提出了一种贝叶斯方法来解释认知科学中广泛的说明价值，并阐明了心理学、统计学和科学哲学中的核心价值如何从一个公共数学框架中出现。同时，这个框架还可以用来重新解释推动阴谋论、妄想和极端意识形态的说明副产品。