The processes of information diffusion across social networks (for example, the spread of opinions and the formation of beliefs) are attracting substantial interest in disciplines ranging from behavioral sciences to mathematics and engineering (see "Summary"). Since the opinions and behaviors of each individual are infl uenced by interactions with others, understanding the structure of interpersonal infl uences is a key ingredient to predict, analyze, and, possibly, control information and decisions [1]. With the rapid proliferation of social media platforms that provide instant messaging, blogging, and other networking services (see "Online Social Networks") people can easily share news, opinions, and preferences. Information can reach a broad audience much faster than before, and opinion mining and sentiment analysis are becoming key challenges in modern society [2]. The first anecdotal evidence of this fact is probably the use that the Obama campaign made of social networks during the 2008 U.S. presidential election [3]. More recently, several news outlets stated that Facebook users played a major role in spreading fake news that might have infl uenced the outcome of the 2016 U.S. presidential election [4]. This can be explained by the phenomena of homophily and biased assimilation [5]-[7] in social networks, which correspond to the tendency of people to follow the behaviors of their friends and establish relationships with like-minded individuals.

中文翻译：

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学习大规模动态社交网络中的隐藏影响：一种基于数据驱动的稀疏性方法，纪念 Roberto Tempo


信息在社交网络上传播的过程（例如，观点的传播和信仰的形成）正在引起人们对从行为科学到数学和工程学等学科的浓厚兴趣（参见“摘要”）。由于每个人的观点和行为都会受到与他人互动的影响，因此了解人际影响的结构是预测、分析以及可能控制信息和决策的关键因素[1]。随着提供即时消息、博客和其他网络服务（参见“在线社交网络”）的社交媒体平台的迅速普及，人们可以轻松地分享新闻、观点和偏好。信息可以比以前更快地传播到广泛的受众，意见挖掘和情感分析正在成为现代社会的关键挑战[2]。这一事实的第一个轶事证据可能是奥巴马竞选团队在 2008 年美国总统选举期间对社交网络的使用 [3]。最近，多家新闻媒体表示，Facebook 用户在传播可能影响 2016 年美国总统选举结果的虚假新闻方面发挥了重要作用 [4]。这可以用社交网络中的同质性和偏见同化现象来解释[5]-[7]，这与人们追随朋友的行为并与志同道合的人建立关系的倾向相对应。