论文标题
用R：半自动筛选用户，评论和通信模式分析社交媒体网络数据
Analysing Social Media Network Data with R: Semi-Automated Screening of Users, Comments and Communication Patterns
论文作者
论文摘要
社交媒体平台上的沟通不仅在文化和政治上是相关的，而且在整个社会中也越来越广泛。用户不仅通过社交媒体平台进行通信，还专门搜索信息，将信息传播或本身发布信息。但是，假新闻，仇恨言论甚至激进的元素是这种现代交流形式的一部分：有时对个人和社会产生深远影响。对这些机制和沟通模式的基本理解可能有助于抵消负面的沟通形式，例如儿童之间的欺凌或极端的政治观点。为此，将提出一种方法，以分解基本的通信模式，追踪个人用户并在社交媒体平台上检查其评论和范围；或以后通过定性研究对比它们。如果考虑到框架的社交网络以及主题，则可以准确地确定具有100％准确性的特别活跃用户。但是，方法论和抵消方法必须更具动态和灵活性，以确保对传播仇恨言论，假新闻和激进元素的用户的敏感性和特殊性。
Communication on social media platforms is not only culturally and politically relevant, it is also increasingly widespread across societies. Users not only communicate via social media platforms, but also search specifically for information, disseminate it or post information themselves. However, fake news, hate speech and even radicalizing elements are part of this modern form of communication: Sometimes with far-reaching effects on individuals and societies. A basic understanding of these mechanisms and communication patterns could help to counteract negative forms of communication, e.g. bullying among children or extreme political points of view. To this end, a method will be presented in order to break down the underlying communication patterns, to trace individual users and to inspect their comments and range on social media platforms; Or to contrast them later on via qualitative research. This approeach can identify particularly active users with an accuracy of 100 percent, if the framing social networks as well as the topics are taken into account. However, methodological as well as counteracting approaches must be even more dynamic and flexible to ensure sensitivity and specifity regarding users who spread hate speech, fake news and radicalizing elements.
