# A Bibliometric Overview of Twitter-Related Studies Indexed in Web of Science
## 2 Literature Review  
### Twitter and Its Research Lines  
One of the most discussed research field of Twitter was its implication on political issues [10], recent years, scholars have argued the influence of using Twitter in sociopolitical movements [11; 12; 13], in political elections and campaigns [14; 15; 16]. Despite the fact that how much influence Twitter has in such events remains under discussion, scholars' enthusiasm toward Twitter in politics seems increasing. Along with the development of computer science and artificial intelligence, using Twitter as a social, political and economic monitor and predictor becomes a new subject for debate in both engineering and social sciences subjects. For example, scholars used Twitter data to monitor natural disaster social dynamics [17], to detect traffic events [18], to predict general election results [19], to make stock market predictions [20] etc. Table 1 presents a summary table of the aforementioned articles, which provides the researchers easy access to these studies.  
Such research domains and examples are too numerous to list here; there are also several academic works that provided a panorama for this subject. [PERSON] et al., [9] qualitatively classified more than 1000 Twitter-related academic works, they categorized them into 13 domains, which were Business, Classification, Communication, Education, Emergency, Geography, Health, Libraries, Linguistics, Search, Security, Technical, Other. [PERSON] and [PERSON] [21] analyzed the content of 382 Twitter-related academic publications from 2006 to 2012, they classified 17 different domains and 9 categories of research methods regarding to their analyzed papers. On the other hand, they found that the publications related to emerging innovative research methods such as data-driven analysis were developed more rapidly than other types of publication, at the same time, the demand for tweet content as research raw data is also increasing. Hence, they argued that more studies mush be updated with the continued growth of Twitter-based research.  
[PERSON] [22] analyzed Twitter-related scientific literature within social science disciplines, with a focus on the most highly cited articles. The common patterns inside these publications have been found, they fit new methods and research designs into classical methodological backgrounds in both qualitative and quantitative approaches. Meanwhile, she argued that studies about Twitter should not solely rely on single datasets and methods, and that the combination of newly emerged methods and classical methods and the connection of Twitter data with other online or offline data sources would positively improve future studies. Researchers have also studied 134 Twitter-related scientific articles indexed in PubMed [23]: they found the early Twitter-focused publications introduced the topic and highlighted its potential, but without any form of data analysis. However, data analytic techniques were mainstream methods in most of the later publications. Despite the fact that the size of the dataset in these papers varies significantly, they argued that the study of Twitter is becoming quantitative research.