Emmert-Streib Frank, Yli-Harja Olli P, Dehmer Matthias
Predictive Medicine and Data Analytics Lab, Department of Signal Processing, Tampere University of Technology, Tampere, Finland.
Institute of Biosciences and Medical Technology, Tampere, Finland.
Front Big Data. 2018 Sep 11;1:2. doi: 10.3389/fdata.2018.00002. eCollection 2018.
Social media in general provide great opportunities for mining massive amounts of text, image, and video-based data. However, what questions can be addressed from analyzing such data? In this review, we are focusing on microblogging services and discuss applications of streaming data from the scientific literature. We will focus on text-based approaches because they represent by far the largest cohort of studies and we present a taxonomy of studied problems.
一般来说，社交媒体为挖掘大量基于文本、图像和视频的数据提供了绝佳机会。然而，通过分析此类数据可以解决哪些问题呢？在本综述中，我们聚焦于微博服务，并讨论来自科学文献的流数据的应用。我们将专注于基于文本的方法，因为它们代表了迄今为止最大的研究群体，并且我们展示了所研究问题的分类法。
