Current landscape of social media use pertaining to glioblastoma by various stakeholders

BACKGROUND: Given the potential for social media to allow widespread public engagement, its role in healthcare, including in cancer care as a support network, is garnering interest. To date, the use of social media in neuro-oncology has not been systematically explored. In the current manuscript, we sought to review Twitter use on glioblastoma among patients, caregivers, providers, researchers, and other stakeholders. METHODS: The Twitter application programming interface (API) database was surveyed from inception to May 2022 to identify tweets about glioblastoma. Number of tweet likes, retweets, quotes, and total engagement were noted for each tweet. Geographic location, number of followers, and number of Tweets were noted for users. We also categorized Tweets based on their underlying themes. A natural language processing (NLP) algorithm was used to assign a polarity score, subjectivity score, and analysis label to each Tweet for sentiment analysis. RESULTS: A total of 1690 unique tweets from 1000 accounts were included in our analyses. The frequency of tweets increased from 2013 and peaked in 2018. The most common category among users was MD/researchers (21.6%, n = 216), followed by Media/News (20%, n = 200) and Business (10.7%); patients or caregivers accounted for only 4.7% (n = 47) while medical centers, journals, and foundations accounted for 5.4%, 3.7%, and 2.1%. The most common subjects that Tweets covered included research (54%), followed by personal experience (18.2%) and raising awareness (14%). In terms of sentiment, 43.6% of Tweets were classified as positive, 41.6% as neutral, and 14.9% as negative; a subset analysis of “personal experience” tweets revealed a higher proportion of negative Tweets (31.5%) and less neutral tweets (25%). Only media (β = 8.4; 95% CI [4.4, 12.4]) and follower count (minimally) predicted higher levels of Tweet engagement. CONCLUSION: This comprehensive analysis of tweets on glioblastoma found that the academic community are the most common user group on Twitter. Sentiment analysis revealed that most negative tweets are related to personal experience. These analyses provide the basis for further work into supporting and developing the care of patients with glioblastoma.