Social media growth of orthopaedic surgery residency programs in response to the COVID-19 pandemic

Figure 1 Orthopaedic surgery residency twitter accounts created. This figure demonstrates the number of new orthopaedic surgery residency Twitter accounts that were created from 2009-2021.

Figure 2 Tweet count timeline. This figure demonstrates the number of ‘tweets’ generated by orthopaedic surgery residency Twitter accounts from 2011-2021.

Figure 3 Top 10 most common twitter hashtags. A: This figure illustrates the ten most common hashtags used by orthopaedic surgery residency Twitter accounts prior to the year 2020; B: This figure illustrates the ten most common hashtags used by orthopaedic surgery residency Twitter accounts after the year 2020. A hashtag is defined as using the “#” symbol and associating it with a word or phrase.

Figure 4 Top 10 most common twitter mentions. A: This figure illustrates the ten most common Twitter mentions used by orthopaedic surgery residency Twitter accounts prior to the year 2020; B: This figure illustrates the ten most common Twitter mentions used by orthopaedic surgery residency Twitter accounts after the year 2020. A Twitter “mention” is defined as tagging or mentioning another account using the @ symbol.

Figure 5 Tweet sentiment analysis. A: This figure illustrates the percentage of positive, negative, and neutral tweets sent out by orthopaedic surgery residency accounts prior to the year 2020; B: This figure illustrates the percentage of positive, negative, and neutral tweets sent out by orthopaedic surgery residency accounts after the year 2020.

Figure 6 Word cloud analysis. A: This figure illustrates a word cloud of the most common words used in tweets sent out by orthopaedic surgery residency Twitter accounts prior to the year 2020. Larger words indicate words that were detected more often; B: This figure illustrates a word cloud of the most common words used in tweets sent out by orthopaedic surgery residency Twitter accounts after the year 2020. Larger words indicate words that were detected more often.