Social media has brought a revolution on how people are consuming news.
Beyond the undoubtedly large number of advantages brought by social-media
platforms, a point of criticism has been the creation of echo chambers and
filter bubbles, caused by social homophily and algorithmic personalization.
In this paper we address the problem of balancing the information exposure in
a social network. We assume that two opposing campaigns (or viewpoints) are
present in the network, and that network nodes have different preferences
towards these campaigns. Our goal is to find two sets of nodes to employ in the
respective campaigns, so that the overall information exposure for the two
campaigns is balanced. We formally define the problem, characterize its
hardness, develop approximation algorithms, and present experimental evaluation
results.
Our model is inspired by the literature on influence maximization, but we
offer significant novelties. First, balance of information exposure is modeled
by a symmetric difference function, which is neither monotone nor submodular,
and thus, not amenable to existing approaches. Second, while previous papers
consider a setting with selfish agents and provide bounds on best response
strategies (i.e., move of the last player), we consider a setting with a
centralized agent and provide bounds for a global objective function.

本文提出一种解决在社交网络中平衡信息暴露的问题的算法，通过使用近似算法来找到两组节点，以使两组节点的信息曝光在整个网络中基本上保持平衡。

社交网络中的信息曝光平衡

Balancing Information Exposure in Social Networks

Recent findings showed that users on Facebook tend to select information that
adhere to their system of beliefs and to form polarized groups -- i.e., echo
chambers. Such a tendency dominates information cascades and might affect
public debates on social relevant issues. In this work we explore the
structural evolution of communities of interest by accounting for users
emotions and engagement. Focusing on the Facebook pages reporting on scientific
and conspiracy content, we characterize the evolution of the size of the two
communities by fitting daily resolution data with three growth models -- i.e.
the Gompertz model, the Logistic model, and the Log-logistic model. Then, we
explore the interplay between emotional state and engagement of users in the
group dynamics. Our findings show that communities' emotional behavior is
affected by the users' involvement inside the echo chamber. Indeed, to an
higher involvement corresponds a more negative approach. Moreover, we observe
that, on average, more active users show a faster shift towards the negativity
than less active ones.

本文探讨了在 Facebook 平台上科学和阴谋论社群的演化和情感行为对社群动态的影响。研究结果显示，用户对社群的参与程度和使用者情感行为对社群的演化有显著影响，越参与社群的使用者更容易表现出负面情绪，并且更活跃的用户比不活跃的用户更容易表现出负面情绪。

回音室：情感传染和群体极化在 Facebook 上的表现

Echo Chambers: Emotional Contagion and Group Polarization on Facebook

In online social networks, users tend to select information that adhere to
their system of beliefs and to form polarized groups of like minded people.
Polarization as well as its effects on online social interactions have been
extensively investigated. Still, the relation between group formation and
personality traits remains unclear. A better understanding of the cognitive and
psychological determinants of online social dynamics might help to design more
efficient communication strategies and to challenge the digital misinformation
threat. In this work, we focus on users commenting posts published by US
Facebook pages supporting scientific and conspiracy-like narratives, and we
classify the personality traits of those users according to their online
behavior. We show that different and conflicting communities are populated by
users showing similar psychological profiles, and that the dominant personality
model is the same in both scientific and conspiracy echo chambers. Moreover, we
observe that the permanence within echo chambers slightly shapes users'
psychological profiles. Our results suggest that the presence of specific
personality traits in individuals lead to their considerable involvement in
supporting narratives inside virtual echo chambers.

研究表明，不同和相互冲突的社区由显示相似心理特点的用户填充，科学和阴谋主义回响室中的主导个性模型相同，并且回响室内的稳定略微改变了用户的心理特征。