Browsing by Subject "Twitter"
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Item A Gamified Social Media-Based Head and Neck Radiology Education Initiative of the American Society of Head and Neck Radiology: Viewership and Engagement Trends at 3 Years(American Society of Neuroradiology, 2022-12) Koontz, N. A.; Tomblinson, C. M.; Shatzkes, D. R.; Glastonbury, C. M.; Phillips, C. D.; Dean, K.; Strauss, S.; Agarwal, M.; Robson, C. D.; Wiggins, R. H.; Radiology and Imaging Sciences, School of MedicineBACKGROUND AND PURPOSE: Social media has made inroads in medical education. We report the creation and 3-year (2018–2021) longitudinal assessment of the American Society of Head and Neck Radiology Case of the Week (#ASHNRCOTW), assessing viewership, engagement, and impact of the coronavirus disease 2019 (COVID-19) pandemic on this Twitter-based education initiative. MATERIALS AND METHODS: Unknown cases were tweeted from the American Society of Head and Neck Radiology account weekly. Tweet impressions (number of times seen), engagements (number of interactions), and new followers were tabulated. A social media marketing platform identified worldwide distribution of Twitter followers. Summary and t test statistics were performed. RESULTS: #ASHNRCOTW was highly visible with 2,082,280 impressions and 203,137 engagements. There were significantly greater mean case impressions (9917 versus 6346), mean case engagements (1305 versus 474), case engagement rates (13.06% versus 7.76%), mean answer impressions (8760 versus 5556), mean answer engagements (908 versus 436), answer engagement rates (10.38% versus 7.87%), mean total (case + answer) impressions (18,677 versus 11,912), mean total engagements (2214 versus 910), and total engagement rates (11.79% versus 7.69%) for cases published after the pandemic started (all P values < .001). There was a significant increase in monthly new followers after starting #ASHNRCOTW (mean, 134 versus 6; P < .001) and significantly increased monthly new followers after the pandemic started compared with prepandemic (mean, 178 versus 101; P = .003). The American Society of Head and Neck Radiology has 7564 Twitter followers throughout 130 countries (66% outside the United States). CONCLUSIONS: Social media affords substantial visibility, engagement, and global outreach for radiology education. #ASHNRCOTW viewership and engagement increased significantly during the COVID-19 pandemic.Item A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study(JMIR, 2024-05-08) Xue, Jia; Shier, Michael L.; Chen, Junxiang; Wang, Yirun; Zheng, Chengda; Chen, Chen; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthBackground: Nonprofit organizations are increasingly using social media to improve their communication strategies with the broader population. However, within the domain of human service nonprofits, there is hesitancy to fully use social media tools, and there is limited scope among organizational personnel in applying their potential beyond self-promotion and service advertisement. There is a pressing need for greater conceptual clarity to support education and training on the varied reasons for using social media to increase organizational outcomes. Objective: This study leverages the potential of Twitter (subsequently rebranded as X [X Corp]) to examine the online communication content within a sample (n=133) of nonprofit sexual assault (SA) centers in Canada. To achieve this, we developed a typology using a qualitative and supervised machine learning model for the automatic classification of tweets posted by these centers. Methods: Using a mixed methods approach that combines machine learning and qualitative analysis, we manually coded 10,809 tweets from 133 SA centers in Canada, spanning the period from March 2009 to March 2023. These manually labeled tweets were used as the training data set for the supervised machine learning process, which allowed us to classify 286,551 organizational tweets. The classification model based on supervised machine learning yielded satisfactory results, prompting the use of unsupervised machine learning to classify the topics within each thematic category and identify latent topics. The qualitative thematic analysis, in combination with topic modeling, provided a contextual understanding of each theme. Sentiment analysis was conducted to reveal the emotions conveyed in the tweets. We conducted validation of the model with 2 independent data sets. Results: Manual annotation of 10,809 tweets identified seven thematic categories: (1) community engagement, (2) organization administration, (3) public awareness, (4) political advocacy, (5) support for others, (6) partnerships, and (7) appreciation. Organization administration was the most frequent segment, and political advocacy and partnerships were the smallest segments. The supervised machine learning model achieved an accuracy of 63.4% in classifying tweets. The sentiment analysis revealed a prevalence of neutral sentiment across all categories. The emotion analysis indicated that fear was predominant, whereas joy was associated with the partnership and appreciation tweets. Topic modeling identified distinct themes within each category, providing valuable insights into the prevalent discussions surrounding SA and related issues. Conclusions: This research contributes an original theoretical model that sheds light on how human service nonprofits use social media to achieve their online organizational communication objectives across 7 thematic categories. The study advances our comprehension of social media use by nonprofits, presenting a comprehensive typology that captures the diverse communication objectives and contents of these organizations, which provide content to expand training and education for nonprofit leaders to connect and engage with the public, policy experts, other organizations, and potential service users.Item Computational Exploration of Gerontology-Related Topics Shared on Social Media Platform Twitter(Oxford Academic, 2018-11-16) Cornet, Victor P.; Hong, MichinTwitter, a popular Internet social media platform, has become a significant medium for sharing information and ideas about various topics, including aging and older adults. While studies have been conducted to examine stigma or perception about specific diseases such as Alzheimer’s disease and seizure on Twitter, there has been little effort to identify general themes of Twitter posts related to aging and older adults. This exploratory study attempts to answer this need by conducting a topic analysis of posts shared on Twitter posts about aging and older adults in English. We collected 328,568 English posts from Twitter posted between 07/01/18 and 07/31/18 using 19 English keywords referring to older adults. We analyzed this whole dataset as well as a subset of posts explicitly including aging-related hashtags, such as #olderadults. We used data mining methods (including Latent Dirichlet Allocation) in computing environment MATLAB to discover topics emerging from these two sets. Among posts with explicit aging-related hashtags, the most recurrent topics were family (relation with children and grandchildren, commemoration), community (resources, looking after older adults), health (disease-specific, public health, home care, formal and informal caregivers), politics and policies (insurance/pension, new laws), and news involving older adults (e.g., crimes on/by older adults). The analysis of the larger dataset additionally uncovered posts promoting pornography featuring older females and posts sharing general Internet content featuring older adults (e.g., YouTube videos). We also share the methodological challenges we encountered and practical recommendations for gerontological researchers interested in using social media data to inform new research.Item The Impact of Social Media on Social Behaviors and Alcohol Consumption(2016-04-08) Burress, KimberlyThis research project examines the subliminal effects that alcohol consumption may or may not have on a person’s technology-based social behaviors. If the effect of alcohol consumption alters social behaviors, then a logical question is whether and how these behaviors are expressed through social media. Sub-areas of inquiry include alcohol’s effect on mood, alcohol-based interactions on social media and the impact of alcohol on an individual’s use of different social media platforms. The main objective of this research is to obtain a clearer understanding of the extent to which alcohol consumption and advertisement impact social media interactions. If correlations can be found, then a further step is to examine alcohol consumption interactions and advertising-based interactions and their influence on the activities of other social media users and the content of their posts. The research will examine social media content created about consuming alcohol through the use of keyword analysis. It will focus specifically on data that can be gleaned from Facebook and Twitter postings. The frequency of social media content creation when under the influence of alcohol will be compared with content creation during periods of sobriety. The research will discern whether there is a noticeable change in content subject matter, attitude and/or tone when alcohol is being consumed. It will also determine whether there is a correlation between social media advertisements related to alcohol, and if so, whether the followers of those advertisements increase their own alcohol-related user content and whether this then increases alcohol consumption. Technology such as social media has significantly reduced the time and distance between communication channels and users. This research project examines technology-based social behaviors to discern whether user content on social media can be collected and analyzed to cultivate additional sales within the alcohol industry.Item A Novel Pipeline for Targeting Breast Cancer Patients on Twitter for Clinical Trial Recruitment(Office of the Vice Chancellor for Research, IUPUI, 2016-04-08) Sligh, Jon; Abedtash, Hamed; Yang, Mengye; Zhang, Enming; Jones, JosetteBackground and Preliminary Exploration: Breast cancer is the leading form of cancer in women, estimated to reach the incidence rate of 246,660 in 2016 in the US population. Scientist have developed new therapies for mitigating the disease and side effects in recent years through conducting randomized clinical trials as the gold standard clinical research method. However, recruiting individuals into clinical trials including breast cancer patients has remained a significant challenge. Our preliminary analysis on ClinicalTrial.gov registry showed that the majority of terminated clinical trials were due to recruitment challenges. Out of 525 terminated trials on breast cancer patients registered in the database, 230 (43.8%) of the terminations happened due to low or slow accrual, 34 (6.5%) due to lack of funding, and 31 (5.9%) due to toxicity concerns. Objectives: In this study, we developed and assess a scalable framework to identify Twitter users who have breast cancer based on personal health mentions on Twitter. In fact, we are looking for “fingerprints” of patients’ health status on Twitter, a microblogging social networking service. This method could provide a new avenue for contacting potential study candidates for recruitment. Methods: We analyzed the tweets of users who were following at least one of the top 40 twitter accounts where breast cancer patients gather. The rationale behind this approach is that cancer patients are following certain Twitter accounts to access support from other patients, doctors, or healthcare institutions. Consequently, these top twitter accounts provide a central point in which to find actual patients with breast cancer. We retrieved users’ tweets from Twitter API, and processed through the framework to match cancer relevant words and phrases individually and in combinations (caner, benign, malignant, etc.), possessive terms (I, my, has, have, etc.), and supporting attributes (mass, tumor, hair loss, etc.) to determine if the user has been diagnosed with cancer. The performance of the pipeline was measured in terms of sensitivity and specificity of detecting actual breast cancer patients. Results: We retrieved 25,870,106 tweets of 40 cancer community followers on Twitter. After excluding “retweets” and non-related breast cancer messages, we selected 81,429 tweets for further processing. The developed text processing pipeline could find total of 462 tweets based on the predefined sets of rules, representing 218 unique users. Our new method of Twitter data retrieval and text processing could identify breast cancer patients with remarkable sensitivity of 88.7% and specificity of 91.0%.Item Nursing in the spotlight: Talk about nurses and the nursing profession on Twitter during the early COVID-19 pandemic(Elsevier, 2022) Miller, Wendy R.; Malloy, Caeli; Mravec, Michelle; Sposato, Margaret F.; Groves, Doyle; School of NursingBackground: Nurses comprise the largest portion of healthcare workers and are integral to the COVID-19 response. Twitter has become a popular platform for the public, including nurses, to engage in pandemic-related discourse. Purpose: We sought to analyze the representation of the nursing profession and characterize nurses’ experiences during the pandemic from tweets published in April 2020. Methods: We analyzed tweets using natural language processing, Word Adjacency Graph (WAG) Modeling, and thematic analysis. Authors independently reviewed 10% of raw tweets in each WAG-generated topic, qualitatively analyzed tweets, and identified emerging themes. Findings: Six themes emerged: Support and Recognition of Nurses, Military Metaphors, Superhuman/Spiritual Metaphors, Advocacy, Personal Experiences with Nurses, and Social/Political Commentary. Public perception of nurses was positive, but nurses conveyed harsh realities of their work. Discussion: Findings highlight discrepancies in nursing experiences and public perceptions of nursing. Further research should accurately identify and convey the complexities of the nursing profession.Item Pediatric Program Directors Should have an Active Presence on Twitter(Elsevier, 2020-11-20) Heitkamp, Nicholas M.; Morgan, Lucas E.; Carmody, J. Bryan; Heitkamp, Darel E.; Pediatrics, School of MedicineFor academic pediatricians, social media has become an important avenue for professional development through continuing education, professional networking, and academic collaboration. Pediatric residency program directors have recognized additional benefits of social media engagement via program promotion and resident recruitment. The novel coronavirus disease 2019 (COVID-19) pandemic and subsequent move to virtual interviews for the 2020–2021 residency interview season have created a new urgency for pediatric program directors to establish an active social media presence, primarily as a means to engage applicants and provide them with information in lieu of cancelled away rotations and in-person interviews. Twitter is a free microblogging and social networking platform that allows real-time engagement among academic pediatricians. Here, we make the case that all pediatric program directors should have an active presence on Twitter.Item Personal Sentiment and Marketing of Electronic Cigarettes Among Twitter Users(Office of the Vice Chancellor for Research, 2016-04-08) Lomax, Victoria; Wendling, Brooke; Wright, EmilieThe use of electronic cigarettes (e-cigarettes) is growing in the United States and there is increasing controversial dialogue surrounding e-cigarettes on social media, including Twitter. With the recent spike in popularity, we conducted a systematic review of the literature to: a.) examine what Twitter users are exposed to regarding e-cigarettes, and b) identify potential ramifications for this exposure. Using predesignated inclusion and exclusion criteria, relevant articles were located using PubMed, EMBASE, EBSCOhost, and CINAHL Complete and reviewing reference lists of relevant articles. Full text, English language, peer-reviewed articles relevant to e-cigarette dialogue on Twitter were reviewed. Of the twelve studies, seven met the inclusion criteria. From our analysis of the content, two key themes were found: marketing (predominant theme) and positive personal sentiment regarding e-cigarette use. Also, within our review, common ramifications for increased marketing and positive sentiment were identified. First, the rise in marketing reaching vulnerable populations, specifically adolescents and young adults, may contribute to the growing use of e-cigarettes and influence positive perceptions of these smoking behaviors. Second, there is controversial information shared regarding the health effects of e-cigarette use. This is an emerging topic and there is relatively scant literature available related to e-cigarette dialogue on Twitter. As a result of our review, we recommend Twitter as a platform for methodically analyzing social media trends and informing health care providers of current issues regarding e-cigarettes. Although more research on the health risks of e-cigarettes is required, there is the need for the current health information on e-cigarettes to be disseminated through Twitter. Health care providers also need to discuss e-cigarette use with patients in the clinical settings. Continued surveillance of e-cigarette use and marketing, as well as examination of the necessity for marketing regulations are important as e-cigarette use becomes more prevalent.Item Public perspectives of monkeypox in Twitter: A social media analysis using machine learning(Elsevier, 2022) Farahat, Ramadan Abdelmoez; Yassin, Mohammed Abdelwahab; Al-Tawfiq, Jaffar A.; Bejan, Cosmin A.; Abdelazeem, Basel; Medicine, School of MedicineItem Top Pediatric Dermatology Twitter Post Characteristics and Trends From 2020 to 2021: Content Analysis(JMIR, 2022-10-26) Kokoska, Ryan E.; Kim, Lori S.; Szeto, Mindy D.; Aukerman, Erica L.; Dellavalle, Robert P.; Dermatology, School of Medicine