# A Bibliometric Overview of Twitter-Related Studies Indexed in Web of Science
## 4 Results and Discussion
### Science Mapping
#### 4.2.2. Thematic Analysis
\"Algorithm, credibility, emotion\" cluster locates between the first and second quadrant with a very high density, this cluster refers to using computational methods to detect online emotion, and is highly developed within this period. \"Microblogging, privacy, altmetric\" cluster locates between the third and fourth quadrant, as big data is gaining attention and popularity among researchers in this period, the usage of big data starts to be important, which have also caused people's awareness about privacy. This cluster may contain two research lines, using Twitter metrics as a tool to measure research impact [48; 49], and the privacy caution of using microblog service [50]. Disaster-management, crisis-management, natural-disaster\" cluster is the emerging and declining theme of the developing period, apparently, this cluster refers to studies about crisis management and crisis communication during severe disasters, for example, earthquakes [51], tsunami [52], and epidemic crisis [53] etc. The last cluster of this period is \"social-network, sentiment-analysis, big-data\"--this cluster belongs to basic and transversal theme, data-driven sentiment analysis becomes a popular research method for social media studies in this period. For the advanced period (2017-2020), there is no absolute motor theme, \"social-media, facebook, political-communication\" locates between the first and the second quadrant with a high centrality, this cluster refers to the study of political communication with social media. Two clusters are on the second quadrant, \"security, behavior, iot (internet of things)\" and \"altmetric, citation, bibliometric\"; they are highly developed and isolated research themes, and independent from each other. Alongside the rapid development of social network sites, the integration of social media and internet of things has formed a new concept, social internet of things (siot) [54], meanwhile, social network-based recommendation system emerges as a new research topic, for example, researchers used Twitter data to personalize movie recommendation system [55], but such advanced technologies also contain considerable security risk. We believe the cluster \"security, behavior, iot\" refers to use Twitter as an iot medium to study user's online behavior and the potential cybersecurity concerns of siot. The cluster \"altmetric, citation, bibliometric\" is easier to interpret--it refers to Twitter-based scientometric studies, compared to the \"altmetric\" cluster in developing period, the study of scientometrics during 2017 to 2020 becomes an independent and developed research theme. \"Sentiment-analysis, machine-learning, big-data\" was the only basic and transversal research theme, this implies computational methods and techniques are widely used in Twitter research from 2017 to 2020. The cluster \"social-network, information-diffusion, microblogging\" locates between the third and the fourth quadrant, with a low density, this means that although the study of information diffusion on Twitter and microblogs emerged in recent years, yet not fully developed. Figure 7 presents the alluvial diagram of research thematic evolution across the three previously segmented periods; it provides us a global view of the changes. Each of the nodes represents a cluster, and is labeled by the first three words of the clusters, the edges are their temporal evolution track, generated by keyword co-occurrence of the topics between two time slices [33]. Overall, research topics in the initial period were more than in later periods; business-related research lines took an important place in that time. There are two major research topics in the developing period, \"social-network\" (social-network, sentiment-analysis, big-data) and \"social-media\" (social-media, facebook, internet). As we have discussed, they imply different research lines, the former represents Twitter study with computational methods, the latter represents cross-platform comparative studies.