ABSTRACT
OBJECTIVES: Twitter is the most frequently used social media platform by healthcare practitioners, at medical conferences. This study aimed to analyze Twitter conversations during the virtual International Gynecological Cancer Society 2020 conference to understand the interactions between Twitter users related to the conference. METHODS: Tweets using the hashtag '#IGCS2020' were searched using the Twitter Search Application Programming Interface (API) during the period 10-13 September 2020. NodeXL Pro was used to retrieve data. The Clauset-Newman-Moore cluster algorithm clustered users into different groups or 'clusters' based on how users interacted. RESULTS: There were 2009 registrants for the virtual IGCS 2020 conference. The total number of users within the network was 168, and there were 880 edges connecting users. Five types of edges were identified as follows: 'replies to' (n=18), 'mentions' (n=221), 'mentions in retweets' (n=375), retweets (n=198), and tweets (n=68). The most influential account was that of the IGCS account itself (@IGCSociety). The overall network shape resembled a community where distinct groups formed within the network. Our current analyses demonstrated that less than 10% of the total members interacted on Twitter. CONCLUSION: This study identified the most influential Twitter users within the '#IGCS2020' community. he results also confirmed the community network shape of the #IGCS2020 hashtag and found that the most frequent co-related words were 'ovarian' and 'cancer' (n=39).