# Exploring and Visualizing Research Progress and Emerging Trends of Event Prediction: A Survey
## 4 Results and Discussion
### Author Co-Citation Network Analysis  
This section assesses the influential authors in the field of event prediction by conducting the author co-citation network analysis in CiteSpace. The analysis encompasses the period from 2012 to 2022, with a particular emphasis on the top N authors within each one-year segment. The N usually falls between 10 and 50. A large value of N poses great pressure for CiteSpace for network analysis and visualization that returns results with low efficiency, while a small value leads to the sparse relationship between nodes and certain research patterns are likely to be missed in this case. In order to keep the balance between computation efficiency and result integrity, we set the N as 20 in this study. This number is typically chosen for network construction in the majority of scientometric analysis studies [67; 68; 69]. The anonymous authors were excluded from the analysis. As shown in Figure 5, the author's co-citation network includes 116 nodes and 645 links. The nodes in the network represent individual authors. When two authors are cited in the same document, a link is established between them, indicating a co-citation relationship. Each color in the visualization corresponds to a specific time slice, typically one year. The concentric rings display the changing patterns of author co-citations over time, with different colors representing different periods. In Figure 5, the larger the node size is, the more frequently cited the author is. The nodes (i.e., authors) owning high citation frequency can be regarded as the core authors in the event prediction field. It reveals that [PERSON] has the highest citation frequency of 263 during each time slice, whose node holds the largest radius in the whole network, followed by [PERSON] and [PERSON] with 185 citations and 170 citations, respectively. It reveals that their publications related to event prediction are much more popular and acknowledged by scholars in the relevant fields. The purple rings enclosing the concentric circles represent the betweenness centrality of the author. The thicker the purple ring, the higher the betweenness centrality. Table 4 lists the top five authors in the event prediction field sorted by the betweenness centrality scores. It shows that there is no significant difference among those authors, indicating that they play critical roles in connecting all authors to compose the research network. Specifically, [PERSON] owns the highest betweenness centrality and closeness centrality, he is from the National Center for Atmospheric Research (NCAR), United States, and his research interests cover a few areas, including Meteorology and Atmospheric Sciences, Geology, Physics, Computer Science, and Environmental Sciences and Ecology. It reveals that he has been a promoter of cooperative and interdisciplinary research as well as an important author with the sum of the shortest path from an author to all other authors in the event prediction field since the year 2013. [PERSON] holds  
Figure 4: The distribution of the number of documents related to each event type. centrality but has the highest degree of centrality, indicating that he has the most direct connections with 45 authors to compose the partial network but is less important for connecting all authors to compose the entire network. We summarized the top five authors by ranking their citation burst scores in Table 5. The highest score was obtained by [PERSON] with a citation burst of 22.08. [PERSON] has 57 publications and 92,987 citations on the WoS. His event prediction-related studies have been increasingly gaining attention from scholars since 2020 and reached an h-index of 34 on the WoS, which is a metric usually used for measuring a research's academic achievement. The other three authors [PERSON], [PERSON], and [PERSON] exhibit similar citation burst patterns over time, indicating that event prediction has emerged as a prominent research direction.