# Applications of Advanced Analysis Technologies in Precise Governance of Social Media Rumors
## 2 Literature Mining  
### Literature Mining of Rumor Research  
To conduct a literature review on rumors, we searched relative literature on Web of Science (WOS) (1959-2021) by using keywords \"rumor\" and its different spelling \"rumour\". WOS is the world's largest comprehensive academic database. It includes more than 26,000 world-renowned and high-impact academic journals, and contains various fields of natural sciences, engineering technology, biomedical, and so on. WOS can provide us with relatively comprehensive, formats uniformed and academically quality references and has nice compatibility to CiteSpace and Endnote. The total number of articles we obtained from WOS databases is 2391. To ensure the accuracy, the following steps were performed. * Deleting repetitive articles. A total of eight duplicated publications were identified and eliminated by Endnote. * Adding missing information. Some literature lack publication year information, for they belong to Early Access publications. We manually added publication year to 26 Early Access articles. * Excluding irrelevant documents. We found that even though the double quotation marks (\" \") to perform a precise search, some irrelevant medical literature appeared. We excluded these five irrelevant papers. In order to summarize the hot spots and trends of rumor research, a systematic literature mining was carried out on the final 2378 documents of Web of Science (WOS) data. CiteSpace, one of the most popular tools for knowledge mapping, is used for visualizing and analyzing trends and patterns in scientific literature. For the first, we applied this tool to generate a keyword co-occurrence knowledge graph, as shown in Figure 1.  
CiteSpace automatically extracts the clustering identification to cluster texts on the relevant literature in the WOS database, and the visual clustering map is shown in Figure 1. The clustering results show that the research hot spots include heterogeneous network,social media, financial rumor, rumor detection, and fake news. Public emotion and social ties are also the focuses. The top 13 keywords with the strongest citation burst in the WOS database are shown in Figure 2. The keywords burst out recently are machine learning, propagation, deep learning, epidemic model, news, and fake news. It can be seen that machine learning is a popular advanced analysis technology recently applied in the research of rumors. As it is shown in Figure 3, the distribution of research for different countries from 1959 to 2021 is visualized by Citespace. In a given time period, the thickness of a ring of a circle is proportional to the total number of papers of that country. On the top of the figure is a time bar, and the color of the rings can show different publication times accordingly. If two circles are connected with a line, then there exists co-authorship. Although rumor papers from China were first published as late as 2001, the number of published papers in China ranks second, accounting for 18.33% of total studies. The top four countries (USA, China, England, France) contributed nearly 50% of rumor research and dominated this research field in the perspective of the number of publications. Figure 4 shows a dual-map overlay of the final document storage. The dual-map overlay is designed by [PERSON] and [PERSON] [3] to reveal patterns of a scientific portfolio with respect to a global map of scientific literature. The visualization of dual-map overlay refers to the relationship between citing and cited. Citespace visualizes the degree of  
Figure 1: Keyword clustering map of WOS database. Figure 2: Top 13 keywords with the strongest citation bursts in the WOS database. concentration of these papers and how these papers connect different regions based on their citation relationships. Each area is represented by a color, standing for a research field. The color curves represent the reference paths, which start from the citing map on the left and point to the cited map on the right.