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Top1. Introduction
The social networking site Twitter is used by approximately 326 Million users every month and each day, approximately 500 Million tweets are sent (Twitter Stats, 2019). Users on Twitter constantly take effective part in any breaking news or mega events that happen around the world. Twitter users can follow other users or can be followed. No reciprocation is required in Twitter like other social networking sites, e.g. Facebook or MySpace (Benetoli et al., 2015). On Twitter, the messages that user receives from other users are called tweets. The response to these tweets is known as retweets and the symbol ‘@’ is used to address the other user while a hashtag ‘#’ is used to follow a keyword. Only 140 characters are allowed to write a Twitter message that is why Twitter is also well known as micro-blogging social networking site. This process strengthens Twitter users to fan out precise and relevant information beyond the original tweet’s followers.
Prior studies have elucidated the significance of Twitter in numerous research fields, such as health (Grover et al., 2018; Nawaz et al., 2017; Jacobson & Mascaro, 2016), education (Hull & Dodd, 2017; Forgie et al., 2013; Kassens-Noor, 2012), social preference learning (Kwon & Lee, 2013), tourism (Sotiriadis & van Zyl, 2013), management (IPCC, 2013), sarcastic sentiment detection (Bharti et al., 2017), event detection (Hasan et al., 2018), users interest detection (Shahzad et al., 2017), politics (Guerrero-Solé, 2018; Di Fatta & Yolles, 2017; McGregor & Mourão, 2016; Hopke, 2015) and sports (Mustafa et al., 2017; Williams et al., 2014). All these studies reflect the significant involvement of Twitter in several prominent sectors. However, there are scarcest studies in the previous literature that provide an overall contribution of Twitter. The number of publications related to Twitter is dramatically increasing and the total number is more than 12000 only in the Web of Science (WoS) database till April 2019. This makes it inevitable to investigate more about who are the most competitive and authoritative journals, countries and organizations that are playing a vital role in the Twitter studies. Therefore, a bibliometric analysis of Twitter is conducted in this study to determine the most competitive and authoritative journals, countries and organizations for Twitter studies. Furthermore, we also explored the related themes of Twitter through co-occurrence of keywords found in the title, abstract and author(s) keywords in Twitter publications.
We searched for bibliometric studies of social media, particularly Twitter in WoS. Consequently, we found only 22 studies as shown in Appendix 1. After analyzing them, we found that most of these studies discussed only specific topics related to Twitter or social media in bibliometric analysis, e.g., bibliometric analysis of highly cited articles in Twitter: case study of biology (Zhang & Wang, 2018), social media bibliometric analysis of information and library science (Gan & Wang, 2014), bibliometric of neurosurgical journals and departments (Alotaibi et al., 2016), bibliometric analysis of social media in psychology (Zyoud et al., 2018), bibliometric of event detection (Chen et al., 2019) and the role of social media in innovation research through bibliometric approach (Appio et al., 2016). However, no study is found in literature according to our best knowledge that explores the overall contribution of Twitter in research academia (most productive journals, institutes and countries in Twitter research) and can inform the researchers where Twitter has been used (thematic analysis).