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Characterizing Twitter Users: : What do Samantha Cristoforetti, Barack Obama and Britney Spears Have in Common?

机译:Twitter用户的特征:萨曼莎·克里斯托福雷蒂,巴拉克·奥巴马和小甜甜布兰妮有什么共同点?

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The exponential growth in the use of digital devices and the ubiquitous online access produce a huge amount of structured and unstructured data that can be mined and analyzed to gather insights into several domains. In particular, since the advent of Web 2.0, Online Social Networks (OSNs) represent a rich opportunity for researchers to collect real user data and to explore OSNs users behavior. This study represents a first attempt to characterize and classify OSNs users according to their level of activity through the use of user profile attributes. We analyzed four case studies from the Twitter platform for a final total of around 721 thousand users, divided into four sub-datasets and examined over a period of at least six months in 2017. Following a data-driven methodology, we found that static, profile-based information - based on the entire lifetime of the users - can help to recognize users influence in Twitter online communities. On the other hand, these profile attributes are not enough to characterize user activity on the microblogging platform.
机译:数字设备使用的指数级增长和无处不在的在线访问产生了大量的结构化和非结构化数据,可以对其进行挖掘和分析,以收集对多个领域的见解。特别是自Web 2.0问世以来,在线社交网络(OSN)为研究人员提供了收集真实用户数据并探索OSN用户行为的丰富机会。这项研究代表了通过使用用户配置文件属性,根据OSN用户的活动水平来对OSN用户进行表征和分类的首次尝试。我们分析了来自Twitter平台的四个案例研究,最终总共约有721 000名用户,分为四个子数据集,并在2017年进行了至少六个月的检查。采用数据驱动的方法后,我们发现静态,基于配置文件的信息-基于用户的整个生命周期-可以帮助识别用户在Twitter在线社区中的影响力。另一方面,这些配置文件属性不足以表征微博平台上的用户活动。

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