Exploring food poverty experiences in the German Twitter-Sphere.

BACKGROUND: This study investigates the subjective perceptions of food poverty in Germany by analysing Twitter discourse using the German-language hashtag #IchBinArmutsbetroffen (#IamPovertyAffected) and examines the extent to which various dimensions of a multidimensional theoretical model of food poverty are represented in the discourse. METHODS: Employing a combination of computational social science and qualitative social research methods, the research identifies, and analyses tweets related to nutrition by applying a hierarchical dictionary search and qualitative content analysis. By examining the narratives and statements of individuals affected by food poverty, the study also investigates the interplay among different subdimensions of this phenomenon. RESULTS: The analysis of 1,112 tweets revealed that 57.96% focused on the material dimension and 42.04% on the social dimension of food poverty, suggesting a relatively balanced emphasis on material and social aspects of food poverty in the narratives of those affected. The findings reveal that tweets on material food poverty underscore economic challenges and resource scarcity for food. Social food poverty tweets demonstrate widespread deprivation in social participation, leading to isolation, exclusion, and social network loss. Overall, the results elucidate intricate interconnections among subdimensions and multidimensional manifestations of food poverty. CONCLUSIONS: This study contributes methodologically by presenting an approach for extracting food-related textual social media data and empirically by providing novel insights into the perceptions and multifaceted manifestations of food poverty in Germany. The results can aid in a better understanding of the phenomenon of food poverty as it currently manifests in Germany, and in developing targeted social, health-promoting, and political measures that address more effectively the empirically evident multidimensionality of the phenomenon.

#clearaligners and social media: An in-depth analysis of clear aligners' content on Instagram.

BACKGROUND AND OBJECTIVES: Clear aligners-related posts are popularized on social media platforms to educate patients and peers and to market aligners in dental practices. This study aimed to characterize the account credentials and content of the top-performing posts to understand the spread of clear aligners-related information on Instagram. MATERIALS AND METHODS: This cross-sectional web-based study analysed 13 Instagram clear aligners-related hashtags. Content analysis was performed for the "Top 10 posts" listed under the "Top" section for each hashtag within Instagram, as sorted by Instagram's algorithm. Data were analysed for the poster's background, credentials, role, post format, content, and engagement level ratio. Duplicate posts and those not relevant to clear aligners were excluded. Quantitative and qualitative analyses of the collected data were conducted. RESULTS: A total of 29 192 596 posts mentioned the selected hashtags, of which 130 posts were screened in this study. Most posts were authored by dentists (n = 84), 79.8% of them were orthodontic specialists. Self-promotional posts comprised 90.2%, while educational posts accounted for only 8.9%. Interestingly, the number of likes and comments received on posts by patients (n = 19, median = 112, IQR = 340) was significantly higher than those posted by dentists (n = 84, median = 93, IQR = 81.75) (P = .004). CONCLUSION: More than 29 million posts about clear aligners were identified on Instagram. Orthodontists are the leading authors of aligners hashtags. However, the majority of the posts are self-promotional and have nonfactual information. Social media awareness among orthodontic specialists may help provide more evidence-based content about clear aligners and can act as an interactive networking and health communication platform.

Current insights on social media as a tool for the dissemination of research and education in surgery: a narrative review.

The purpose of our narrative review is to summarize the utilization of social media (SoMe) platforms for research communication within the field of surgery. We searched the PubMed database for articles in the last decade that discuss the utilization of SoMe in surgery and then categorized the diverse purposes of SoMe. SoMe proved to be a powerful tool for disseminating articles. Employing strategic methods like visual abstracts enhances article citation rates, the impact factor, h-index, and Altmetric score (an emerging alternative metric that comprehensively and instantly quantifies the social impact of scientific papers). SoMe also proved valuable for surgical education, with online videos shared widely for surgical training. However, it is essential to acknowledge the associated risk of inconsistency in quality. Moreover, SoMe facilitates discussion on specific topics through hashtags or closed groups and is instrumental in recruiting surgeons, with over half of general surgery residency programs in the US efficiently leveraging these platforms to attract the attention of potential candidates. Thus, there is a wealth of evidence supporting the effective use of SoMe for surgeons. In the contemporary era where SoMe is widely utilized, surgeons should be well-versed in this evidence.

Gray hair and pink slips: An analysis of Twitter responses to gendered ageism.

When Canadian broadcaster, Lisa LaFlamme, announced in August 2022 that CTV National News did not renew her contract, some observers suggested that the corporation's decision resulted from LaFlamme's choice to "let her hair go gray" during the pandemic. An international public outcry ensued on Twitter. Our study involved an examination of these tweets (n = 440). Analyses revealed that approximately 80 percent of tweets indicated opposition to LaFlamme's dismissal, while only 2 percent indicated support and 18 percent indicated a neutral position. Among tweets expressing opposition, the most common justification, found in 79 percent of these tweets, centered on assessments of the employer's decision as poor. The frequency of all other justifications for opposition was considerably lower, with only 26 percent of these tweets mentioning ageism, 22 percent mentioning sexism, and 20 percent mentioning a general sense of unfairness to LaFlamme. These findings suggest the salience of capitalist logics in shaping how the public frames gendered ageism in the workplace. Our analyses also suggest a view of responses to this inequality as personal bodywork choices. Together, these framings reflect a more individual- than structural-level critique of gendered ageism, knowledge of which can inform efforts to dismantle it.

Comparison of Social Media Content on Hidradenitis Suppurativa: A Cross-Sectional Study.

BACKGROUND: Research has shown that patients may turn to social media seeking information regarding diagnosis and treatment. This study aimed to analyze and compare content related to hidradenitis suppurativa (HS) using the "hashtag" tool across three of the most popular social media platforms to determine the information that patients are exposed to online. METHODS: We identified hashtags across Instagram, TikTok, and Facebook for "#hidradenitissuppurativa." The top 50 videos returned by the algorithm across each site were selected for analysis. Data extracted for comparison included content creator demographics, number of followers, type of content (educational vs. noneducational), and associated hashtags. RESULTS: Sixty-seven percent of posts were created by females (n = 101/150), 10% by males (n = 16/150), and 22% other (n = 33/150). Distribution was similar across all platforms. User accounts on TikTok have a significantly higher number of followers (median = 38,700, range = 902-17,600,000 followers) compared to Facebook (median = 1,375, range = 58-777,000 followers) and Instagram (median = 2,818, range = 57-9,800 followers). CONCLUSION: This study suggests that there is a disproportionate number of patients creating content to raise awareness on HS on social media compared to patient support groups or medical professionals. We propose that social media is a useful platform that dermatologists and official institutional bodies can utilize as an alternative method of health promotion and patient education. Further research to explore social media trends across a range of dermatological conditions can help guide targeted education campaigns in the future.

#CoreCosmeticSpecialties: An analysis of nonsurgical cosmetic procedure hashtags on Instagram.

OBJECTIVES: In this study, we seek to characterize both the account credentials and content type for posts among the most popular nonsurgical cosmetic procedure hashtags on Instagram. METHODS: Twenty-five hashtags related to nonsurgical cosmetic procedures were identified with over 250,000 posts each, ranging from 256,000 to 12.1 million posts per hashtag. The first 10 posts displayed under the "Top" section for each hashtag within Instagram, as sorted by Instagram's proprietary algorithm, were analyzed for account type and content type. Posts unrelated to the cosmetic procedure or with non-English captions were excluded. In total, 680 posts were queried with 250 posts meeting the inclusion criteria. RESULTS: Content creators included nonphysician providers (68%), core cosmetic physicians (12%), noncore cosmetic physicians (8%), and consumers or others (13%). Content type included before and after (45%), self-promotional (23%), educational (17%), personal (5%), entertainment (5%), and promotional (5%). Among the different content creator types, core cosmetic physicians had the largest proportion of educational content at 38%. CONCLUSIONS: High-quality educational content on Instagram from core cosmetic specialties is scarce. By increasing their presence on Instagram, core cosmetic physicians can provide patient education, counteract misinformation, and raise awareness on training and qualifications regarding nonsurgical cosmetic procedures.

An exploratory analysis of pediatric anesthesia activity on Twitter using the #pedsanes hashtag.

BACKGROUND: The use of social media within the medical field has rapidly evolved over the past two decades, with Twitter being one of the most common platforms of engagement. The use of hashtags such as #pedsanes has been reported as a community builder around the subject of pediatric anesthesia. Understanding the use of #pedsanes can inform dissemination of pediatric anesthesia content and discourse. We aimed to describe the distribution and patterns of tweets and contributors using #pedsanes across the globe. METHODS: Using Tweetbinder (https://www.tweetbinder.com) and the R package "academictwitteR," we extracted tweets that included the hashtag "#pedsanes" from March 14, 2016 to March 10, 2022. Tweets were analyzed for frequency, type, unique users, impact and reach, language, content, and the most common themes. RESULTS: A total of 58 724 tweets were retrieved; 22 071 (38.8%) were original tweets including 3247 replies, while 35 971 (61.2%) were retweets all generated by over 5946 contributors located in at least 122 countries. The frequency distribution of tweets gradually increased over time with peaks in activity corresponding to major pediatric anesthesia societal meetings and during the early phases of the COVID-19 pandemic. The most retweeted and most liked posts included images. DISCUSSION: We report the widespread and increasing use of social media and the "#pedsanes" hashtag within the pediatric anesthesia and medical community over time. It remains unknown the extent to which Twitter hashtag activity translates to changes in clinical practice. However, the #pedsanes hashtag appears to play a key role in disseminating pediatric anesthesia information globally.

Hashtags in Plastic Surgery: A Sentiment Analysis of over 1 Million Tweets.

BACKGROUND: Current literature has sparse recommendations that guide social networking practices in plastic surgery. To address this, we used natural language processing and sentiment analysis to investigate the differences in plastic surgery-related terms and hashtags on Twitter. METHODS: Over 1 million tweets containing keywords #plasticsurgery, #cosmeticsurgery, and their non-hashtagged versions plastic surgery and cosmetic surgery were collected from the Twitter Gardenhose feed spanning from 2012 to 2016. We extracted the average happiness/positivity (h-avg) using hedonometrics and created word-shift graphs to determine influential words. RESULTS: The most popular keywords were plastic and cosmetic surgery, comprising more than 90% of the sample. The positivity scores for plastic surgery, cosmetic surgery, #plasticsurgery, and #cosmeticsurgery were 5.72, 6.00, 6.17, and 6.18, respectively. Compared to plastic surgery, the term cosmetic surgery was more positive because it lacked antagonistic words, such as "fake," "ugly," "bad," "fails," and "wrong." For similar reasons, #plasticsurgery and #cosmeticsurgery were more positively associated than their non-hashtagged counterparts. CONCLUSION: Plastic surgery-related hashtags are more positively associated than their non-hashtagged versions. The language associated with such hashtags suggests a different user profile than the public and, given their underutilization, remain viable channels for professionals to achieve their diverse social media goals. LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Influence of the pandemic lockdown on Fridays for Future's hashtag activism.

Social movement organizations (SMOs) increasingly rely on Twitter to create new and viral communication spaces alongside newsworthy protest events and communicate their grievance directly to the public. When the COVID-19 pandemic impeded street protests in spring 2020, SMOs had to adapt their strategies to online-only formats. We analyze the German-language Twitter communication of the climate movement Fridays for Future (FFF) before and during the lockdown to explain how SMOs adapted their strategy under online-only conditions. We collected (re-)tweets containing the hashtag #fridaysforfuture (N = 46,881 tweets, N = 225,562 retweets) and analyzed Twitter activity, use of hashtags, and predominant topics. Results show that although the number of tweets was already steadily declining before, it sharply dropped during the lockdown. Moreover, the use of hashtags changed substantially and tweets focused increasingly on thematic discourses and debates around the legitimacy of FFF, while tweets about protests and calls for mobilization decreased.

An exploration of the reach of the #MakeSpace4Research hashtag.

BACKGROUND: Use of social media to communicate with and engage health professionals is increasing. A communications campaign at Newcastle upon Tyne Hospitals NHS Foundation Trust used a Twitter hashtag to improve the visibility of nursing, midwifery and allied health professionals research. AIM: This study aimed to explore the reach of the #MakeSpace4Research campaign during its first 12 months. METHODS: Between November 2018 and 2019, data on all tweets containing #MakeSpace4Research were examined using an online analytical tool. The studied variables were: total reach; total impressions; unique authors; total retweets; total mentions; and top tweeters. All these were collated using two separate variables: matching tweets and impact. FINDINGS: #MakeSpace4Research appeared in 6884 tweets, involving 1085 individual Twitter accounts, resulting in more than 16 million impressions. Mentions and impressions both increased threefold, and unique authors more than doubled over the 12-month period. A spike in activity was noted after the campaign was launched at a nursing, midwifery and allied health professionals research conference in May 2019. CONCLUSION: The #MakeSpace4Research campaign has the potential to connect online communities of research-interested nurses, midwives and allied health professionals.

Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis.

BACKGROUND: "Data Saves Lives" is a public engagement campaign that highlights the benefits of big data research and aims to establish public trust for this emerging research area. OBJECTIVE: This study explores how the hashtag #DataSavesLives is used on Twitter. We focused on the period when the UK government and its agencies adopted #DataSavesLives in an attempt to support their plans to set up a new database holding National Health Service (NHS) users' medical data. METHODS: Public tweets published between April 19 and July 15, 2021, using the hashtag #DataSavesLives were saved using NCapture for NVivo 12. All tweets were coded twice. First, each tweet was assigned a positive, neutral, or negative attitude toward the campaign. Second, inductive thematic analysis was conducted. The results of the thematic analysis were mapped under 3 models of public engagement: deficit, dialogue, and participatory. RESULTS: Of 1026 unique tweets available for qualitative analysis, discussion around #DataSavesLives was largely positive (n=716, 69.8%) or neutral (n=276, 26.9%) toward the campaign with limited negative attitudes (n=34, 3.3%). Themes derived from the #DataSavesLives debate included ethical sharing, proactively engaging the public, coproducing knowledge with the public, harnessing potential, and gaining an understanding of big data research. The Twitter discourse was largely positive toward the campaign. The hashtag is predominantly used by similar-minded Twitter users to share information about big data projects and to spread positive messages about big data research when there are public controversies. The hashtag is generally used by organizations and people supportive of big data research. Tweet authors recognize that the public should be proactively engaged and involved in big data projects. The campaign remains UK centric. The results indicate that the communication around big data research is driven by the professional community and remains 1-way as members of the public rarely use the hashtag. CONCLUSIONS: The results demonstrate the potential of social media but draws attention to hashtag usage being generally confined to "Twitter bubbles": groups of similar-minded Twitter users.

Investigating the COVID-19 vaccine discussions on Twitter through a multilayer network-based approach.

Modeling discussions on social networks is a challenging task, especially if we consider sensitive topics, such as politics or healthcare. However, the knowledge hidden in these debates helps to investigate trends and opinions and to identify the cohesion of users when they deal with a specific topic. To this end, we propose a general multilayer network approach to investigate discussions on a social network. In order to prove the validity of our model, we apply it on a Twitter dataset containing tweets concerning opinions on COVID-19 vaccines. We extract a set of relevant hashtags (i.e., gold-standard hashtags) for each line of thought (i.e., pro-vaxxer, neutral, and anti-vaxxer). Then, thanks to our multilayer network model, we figure out that the anti-vaxxers tend to have ego networks denser (+14.39%) and more cohesive (+64.2%) than the ones of pro-vaxxer, which leads to a higher number of interactions among anti-vaxxers than pro-vaxxers (+393.89%). Finally, we report a comparison between our approach and one based on single networks analysis. We prove the effectiveness of our model to extract influencers having ego networks with more nodes (+40.46%), edges (+39.36%), and interactions with their neighbors (+28.56%) with respect to the other approach. As a result, these influential users are much more important to analyze and can provide more valuable information.

Cultural heritage through the lens of COVID-19.

This study examines the discourse emerging from cultural heritage content shared online during the COVID-19 pandemic. It aims to understand the different affective and cognitive dynamics that are associated with the online sharing of cultural heritage in difficult times. To do so, we analyzed two Instagram hashtags-#ShareOurHeritage and #ShareCulture - that are promoted by UNESCO on a global scale. We applied a comprehensive quantitative method for qualitative data analysis. This method relied on Latent Dirichlet Allocation for topic modeling to generate automated induction of semantic topics and understand the underlying cognitive and affective dimensions of Instagram posts under each topic. Social values- including safety, inclusion, participation, and resilience - positive emotional language, and diverse cultural expressions were the most shared by the investigated hashtag community during the COVID-19 pandemic. In addition, results showed that users approach the virtual space as a substitute for the loss of their physical place through terms like home, virtual, online, travel tomorrow, and museums from home. Results are discussed in the context of the global digital divide, the social value of heritage to hashtag communities, and the use of Instagram as a longitudinal record of how cultural heritage values change across time.

#MIGS: Minimally Invasive Gynecologic Surgery Tag Ontology Project.

STUDY OBJECTIVE: The creation of an ontology may enable providers to more definitively engage the public in evidence-based and meaningful discussions about women's health. The goal of this study is to review and analyze the current social media status of minimally invasive gynecologic surgery (MIGS) on Twitter and create a tag ontology. DESIGN: Tag ontologies are lists of hashtags used to standardize searches within a social media platform. We examined trending terms and influencers on Twitter on the basis of the keyword "MIGS." We then compiled a list of top hashtags on the basis of the number of tweets from January 2018 to August 2020. Terms were identified with manual Twitter queries and Symplur Signals and selected for inclusion in the ontology on the basis of frequency of use and clinical relevance. The ontology was then categorized by pelvic disease and intervention and reviewed/supplemented by key social media influencers for inclusivity. SETTING: N/A PATIENTS: N/A INTERVENTIONS: N/A MEASUREMENTS AND MAIN RESULTS: We identified 4550 tweets and 1836 users while searching #MIGS in August 2020. Twenty-nine terms were included in our ontology, which were then subcategorized into 6 groups (uterine pathology, adnexal pathology, menstruation, pelvic pathology, pelvic pain, and other). CONCLUSION: Our study has created an ontology specific to the MIGS on the basis of Twitter usage over the last 2 years that may facilitate more effective social media communication.

#Covid4Rheum: an analytical twitter study in the time of the COVID-19 pandemic.

Social media services, such as Twitter, offer great potential for a better understanding of rheumatic and musculoskeletal disorders (RMDs) and improved care in the field of rheumatology. This study examined the content and stakeholders associated with the Twitter hashtag #Covid4Rheum during the COVID-19 pandemic. The content analysis shows that Twitter connects stakeholders of the rheumatology community on a global level, reaching millions of users. Specifically, the use of hashtags on Twitter assists digital crowdsourcing projects and scientific collaboration, as exemplified by the COVID-19 Global Rheumatology Alliance registry. Moreover, Twitter facilitates the distribution of scientific content, such as guidelines or publications. Finally, digital data mining enables the identification of hot topics within the field of rheumatology.

Image Hashtag Recommendations Using a Voting Deep Neural Network and Associative Rules Mining Approach.

Hashtag-based image descriptions are a popular approach for labeling images on social media platforms. In practice, images are often described by more than one hashtag. Due the rapid development of deep neural networks specialized in image embedding and classification, it is now possible to generate those descriptions automatically. In this paper we propose a novel Voting Deep Neural Network with Associative Rules Mining (VDNN-ARM) algorithm that can be used to solve multi-label hashtag recommendation problems. VDNN-ARM is a machine learning approach that utilizes an ensemble of deep neural networks to generate image features, which are then classified to potential hashtag sets. Proposed hashtags are then filtered by a voting schema. The remaining hashtags might be included in a final recommended hashtags dataset by application of associative rules mining, which explores dependencies in certain hashtag groups. Our approach is evaluated on a HARRISON benchmark dataset as a multi-label classification problem. The highest values of our evaluation parameters, including precision, recall, and accuracy, have been obtained for VDNN-ARM with a confidence threshold 0.95. VDNN-ARM outperforms state-of-the-art algorithms, including VGG-Object + VGG-Scene precision by 17.91% as well as ensemble-FFNN (intersection) recall by 32.33% and accuracy by 27.00%. Both the dataset and all source codes we implemented for this research are available for download, and our results can be reproduced.

Hashtag Health: College Health on Social Media and Students' Motivations to Follow, Interact, and Share Their Social Media Content.

Social media are advocated as a prime channel through which to reach college students with health-related information. However, how well are colleges and universities utilizing social media as it was intended-a means to be truly social and not just promotional? Social media can only be effective if students actually follow, interact, and share the content being produced. The following study completed a census of student health center Facebook accounts in the United States as well as investigated students' motivations to follow, interact with, and share health-related content. Facebook pages were found for about 20% of student health centers, and about two thirds posted content within the past 14 days. However, their median number of "likes" was between 191 and 496 despite being in existence for an average of 6 years. Additionally, the majority of these centers' most recent posts were promotional, instead of trying to socially engage with their followers. Students indicated that they would be likely to follow, interact, or share social media content from college health accounts if they were incentivized to do so, if they thought the content could be relevant to them, or if they simply knew that the account existed. Unless more attention is given to growing their followings, resources used by student health organizations to consistently post content might be better placed elsewhere. Recommendations for increasing engagement with students are discussed.

#Orthorexia on Instagram: a descriptive study exploring the online conversation and community using the Netlytic software.

Orthorexia nervosa (ON) is a relatively new phenomenon. The purpose of this study was to investigate (1) the #orthorexia conversation on Instagram (using the Netlytic software), and (2) among a random subsample of images (N = 245), analyse the types of images (N = 145) and author biographies (N = 68). Among the 4,533 downloaded records, there were 48,780 unique words associated with the posts, with the most commonly used being love (n = 535) and #edrecovery (n = 425). Among the images, the majority contained food (68%) and people (13%). Among the unique authors, the majority were female (84%) and mentioned ED (eating disorder) recovery and being food/fitness focused. The ON community on Instagram is relatively small and the positive conversation may suggest a supportive community that focuses on recovery and adopting healthier eating behaviours.Level of evidence Level V, descriptive study.

Breaking International Barriers: #ColorectalSurgery Is #GlobalSurgery.

Colorectal surgeons have lagged behind other professionals in the use of social media. Currently, Twitter is the most widely utilized social platform for professional purposes among them. Connection and contagion are the two key actions that, together with immediate feedback and quantifiable impact, favor the use of Twitter over other social networks. In early 2016, a group of colorectal surgeons launched the #colorectalsurgery hashtag and, in less than 1 year, the ecosystem has incorporated over 2,600 users that generated over 24,000 tweets and 100 million impressions. "Live-Tweeting" surgical conferences by attendees including institutional or society accounts have greatly contributed to the success of the initiative. However, there are some barriers to a more wide adoption of social media, such as misrepresentation of non-peer-reviewed data, challenges to intellectual property protection, or even damage to the professional image. Active engagement with the #colorectalsurgery community may result in benefits for the global surgery community through information sharing, social interactions, personal branding, and research.

Impact of a New Gynecologic Oncology Hashtag During Virtual-Only ASCO Annual Meetings: An X (Twitter) Social Network Analysis.

Background: Official conference hashtags are commonly used to promote tweeting and social media engagement. The reach and impact of introducing a new hashtag during an oncology conference have yet to be studied. The American Society of Clinical Oncology (ASCO) conducts an annual global meeting, which was entirely virtual due to the COVID-19 pandemic in 2020 and 2021. Objective: This study aimed to assess the reach and impact (in the form of vertices and edges generated) and X (formerly Twitter) activity of the new hashtags #goASCO20 and #goASCO21 in the ASCO 2020 and 2021 virtual conferences. Methods: New hashtags (#goASCO20 and #goASCO21) were created for the ASCO virtual conferences in 2020 and 2021 to help focus gynecologic oncology discussion at the ASCO meetings. Data were retrieved using these hashtags (#goASCO20 for 2020 and #goASCO21 for 2021). A social network analysis was performed using the NodeXL software application. Results: The hashtags #goASCO20 and #goASCO21 had similar impacts on the social network. Analysis of the reach and impact of the individual hashtags found #goASCO20 to have 150 vertices and 2519 total edges and #goASCO20 to have 174 vertices and 2062 total edges. Mentions and tweets between 2020 and 2021 were also similar. The circles representing different users were spatially arranged in a more balanced way in 2021. Tweets using the #goASCO21 hashtag received significantly more responses than tweets using #goASCO20 (75 times in 2020 vs 360 times in 2021; z value=16.63 and P<.001). This indicates increased engagement in the subsequent year. Conclusions: Introducing a gynecologic oncology specialty-specific hashtag (#goASCO20 and #goASCO21) that is related but different from the official conference hashtag (#ASCO20 and #ASCO21) helped facilitate discussion on topics of interest to gynecologic oncologists during a virtual pan-oncology meeting. This impact was visible in the social network analysis.