Social media users post content on various topics. A defining feature of social media is that other users can provide feedback—called community feedback—to their content in the form of comments, replies, and retweets. We hypothesize that the amount of received feedback influences the choice of topics on which a social media user posts. However, it is challenging to test this hypothesis as user heterogeneity and external confounders complicate measuring the feedback effect. Here, we investigate this hypothesis with a predictive approach based on an interpretable model of an author’s decision to continue the topic of their previous post. We explore the confounding factors, including author’s topic preferences and unobserved external factors such as news and social events, by optimizing the predictive accuracy. This approach enables us to identify which users are susceptible to community feedback. Overall, we find that 33% and 14% of active users in Reddit and Twitter, respectively, are influenced by community feedback. The model suggests that this feedback alters the probability of topic continuation up to 14%, depending on the user and the amount of feedback.

中文翻译：

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使用预测模型评估社区反馈对社交媒体中主题选择的影响

社交媒体用户发布有关各种主题的内容。社交媒体的一个定义特征是其他用户可以以评论，回复和转发的形式向他们的内容提供反馈（称为社区反馈）。我们假设收到的反馈数量会影响社交媒体用户发布主题的选择。然而，由于用户异质性和外部混杂因素使反馈效果的测量变得复杂，因此检验该假设具有挑战性。在这里，我们使用一种预测方法来研究该假设，该方法基于作者决定继续其先前帖子主题的可解释模型。通过优化预测的准确性，我们探索了一些混杂因素，包括作者的主题偏好和未观察到的外部因素，例如新闻和社交事件。这种方法使我们能够确定哪些用户容易受到社区反馈的影响。总体而言，我们发现Reddit和Twitter中分别有33％和14％的活跃用户受到社区反馈的影响。该模型表明，根据用户和反馈量的不同，此反馈最多可将话题继续发生的概率更改为14％。