Social Media Mentions Research Articles

#PorkandPigs: an online media listening analysis of public perception of the U.S. swine industry

Abstract With the majority of the U.S. swine industry being generally bounded by social licensing, there is a growing need to understand social perspectives to better adapt to consumer demands. Online and social media data are rich datasets that researchers are leveraging to tackle economic and societal challenges. The information that can be gleaned from online media regarding public perceptions makes it an important tool for producers to understand driving topics of interest to the public. This study utilized a prominent online and social media listening and data analytics platform to identify and quantify online and social media mentions related to the U.S. swine industry from January 1, 2020, to December 31, 2023. A general search for online media referencing pork and pigs was designed resulting in a total of 41,093,309 mentions. The search was further queried to specific topics of food and cooking (20,580,068 mentions), price (2,866,548 mentions), welfare (1,615,208 mentions), sustainability (771,819 mentions), and top authors/organizations within the U.S. swine industry (1,430 mentions). The study spanned the geographic locations of the overall U.S. (including U.S. Minor Outlying Islands), the top 5 most populous states, and the top 5 pork producing states as of 2024. Of all mentions, X/Twitter was the largest domain for nearly all mentions related to pork and pigs. Major organizations designed to spread information between the general public and pork producers had a minor impact on the overall conversation and no online media presence in the top 5 most populous states. Net sentiment was overall positive across all four years and all geographies except for major events such as the COVID-19 pandemic, the H1N1 Swine Flu, the passing of California Proposition 12, environmental events, and inflation-associated pork prices. Overall, most media presence had positive net sentiments and with most interest surrounding ways to cook pork and how to keep bacon cheap. Understanding public perceptions of the U.S. swine industry provides the opportunity to make informed decisions on marketing strategies and production practices.

How far do oral lectures at European Orthodontic Society congresses reach? A comparison of abstract publication rates, article citations, and social media mentions.

This study investigated the scientific impact of oral abstracts presented in five consecutive European Orthodontic Society (EOS) congresses in terms of full-text publication rates as well as citations and social media metrics (altmetrics) of the resulting articles. PubMed (http://www.ncbi.nlm.nih.gov/pubmed) and Google Scholar (http://scholar.google.nl/) were screened to identify published articles originally presented as lectures at EOS 2015-2019. EOS date, abstract title, subject, number of authors, authors' names, first author's country of origin, and type of affiliation were extracted from congress abstract books. Altmetric Attention Scores (AASs), number of X (formerly Twitter) posts, Mendeley reads, and citations of the articles were retrieved from Altmetric Explorer and Web of Science (WoS) databases, respectively. Abstract details, full publication rates and Altmetric mentions and WoS citations of the related articles were analysed using univariable and multivariable logistic regression. In total, 51.79 to 73.91% of the lectures presented at EOS 2015-2019 were converted into peer-reviewed articles. There was a median interval of 10.95 months (interquartile range 20.5 months) between conference and publication dates. EOS congress year (overall Wald test P-value = .04) and number of authors (overall Wald test P-value < .01) were significant predictors for full-text publication of oral lectures. There was no significant effect of EOS presentation on AASs, citations, X posts, and Mendeley readers (P > .05). Journal impact factors and quartile rankings were not considered to determine the impact of the journals that published articles originally presented as EOS oral abstracts. Overall, 61.30% of EOS 2015-2019 lectures were published as full-length articles. Multi-authored abstracts presented higher odds of publication, whereas oral abstracts presented at EOS 2015 and 2018 had the lowest probabilities to reach full publication. EOS abstract-based articles were assigned similar numbers of citations and AASs to articles not presented at EOS congresses.

A Highly Accurate Adverse Drug Reactions (ADR) Detection from Medical Forum Comments Using Long Short-Term Memory Networks

Purpose: Adverse Drug Reactions (ADR) classification is useful in modern medical diagnostics and related applications. ADR is an example of how medical information is frequently accessible on social media platforms for healthcare, where people can share their experiences with treatments on desktop computers and mobile devices. Many researchers are interested in gathering valuable medical data from social media for the ADR system training and classification process. Materials and Methods: This research explores the effects of three aspects on recognizing ADR mentions in social media for the medical field and proposes a deep neural network of Long Short-Term Memory (LSTM) neural networks to do so. The comments are collected from various social media platforms to implement the ADR system with proper training and testing processes. The texts from the dataset are initially preprocessed by using a data filtering and clustering process to remove the input data's redundant information to increase the training process's quality. Characteristic features, such as semantic features and text statistics, are extracted from the input text using the American Standard Code for Information Interchange (ASCII) array. Further, the features are converted and fed to LSTM networks for training and validation. Results and Conclusion: This work is evaluated using two datasets, CODEC, and ADR Corpus datasets are used to evaluate the performance of the proposed ADR technique via multiple angles. Via extensive experiments, this work achieved 99.79 accuracy, 98.37 sensitivity, 97.63 specificity, 99.72 precision, 98.39 recall, 97.62 F1-score for the CODEC dataset, 98.16 for accuracy, 99.19 for sensitivity, 98.49 for specificity, 99.49 for precision, 96.72 for recall, and 93.16 for F1-score for ADR corpus, respectively.

Uncovering the reasons of retraction in virology: a citation and Altmetric investigation

Purpose This paper aims to delve into the critical examination of retractions in virology to identify the underlying factor that led to the retraction of scientific publications in this specialised domain. Further, this study offers insights into the impact of the retracted publications in the scholarly world vis-à-vis citation and Altmetric indicators. Design/methodology/approach The top 100 highly cited retracted articles from virology category were taken from the Web of Science (WoS) database. The Retraction Watch database was used for knowing the reasons for retraction for each retracted publication. The citation and Altmetric score of retracted publications were noted down from WoS and Altmetric.com databases, respectively. Journal Citation Report was used to note down the impact factor of the journals that have published these articles. Findings “Misconduct” (57.73%) is the most prevalent reason for the retraction of publications followed by plagiarism (18.55%) and journal issues (14.43%). The retracted papers are cited even after their retraction. Around 70.52% citations were received before and 29.47% after retraction. The highest number of retracted papers was published in the Journal of Virology (14) and Journal of Chemistry (10). High-impact factor journals such as Lancet, Cell and Nature each own one retracted paper. The study found dissemination of these publications through social media platforms with highest social media mentions (394) followed by policy and patents mentions (373) and news and blog mentions (300). Practical implications The research delves into understanding the reasons behind the retraction of virology papers and the impact of these publications through citation and Altmetric analyses. Its impactions include bolstering quality control in virology research, maintaining trust in scientific literature. Citation and Altmetric analyses offer deep insights into the broader impact of retracted papers, informing policy and publishing practices to uphold scientific integrity in virology. Originality/value This study addresses a specific and crucial aspect of scientific research retractions within the field of virology. While retractions have been studied in broader terms in scientific research, to the best of the authors’ knowledge, no such study has been conducted in the scientific field of virology.

Second-order citations in altmetrics: A case study analyzing the audiences of COVID-19 research in the news and on social media

Abstract The potential to capture the societal impact of research has been a driving motivation for the use and development of altmetrics. Yet, to date, altmetrics have largely failed to deliver on this potential because the primary audience that cites research on social media has been shown to be academics themselves. In response, our study investigates an extension of traditional altmetric approaches that goes beyond capturing direct mentions of research on social media. Using research articles from the first months of the COVID-19 pandemic as a case study, we demonstrate the value of measuring “second-order citations,” or social media mentions of news coverage of research. We find that a sample of these citations, published by just five media outlets, were shared and engaged with on social media twice as much as the research articles themselves. Moreover, first-order and second-order citations circulated among Twitter accounts and Facebook accounts that were largely distinct from each other. The differences in audiences and engagement patterns found in this case study provide strong evidence that investigating these second-order citations can be an effective way of observing overlooked audiences who engage with research content on social media.

167 An Evaluation of Altmetric Attention using Network Science and Natural Language Processing

OBJECTIVES/GOALS: Our project aims to assess the composition or characteristics of research papers that score high on alternative metrics. These alternative metrics including the number of newspaper mentions, social media mentions, and the attention score as catalogued on Altmetric, a tool used to document community attention for a given research paper. METHODS/STUDY POPULATION: Our study intends to 1) Utilize topic modeling to identify prevalent themes on Altmetric, and 2) Apply network analysis to elucidate the interconnectedness among universities, funding sources, journals, and publishers associated with high-attention papers. 3) Examine how these patterns vary when attention metrics shift, such as social media mentions, newspaper mentions, or the Altmetric score. We'll first perform this analysis on all types of papers and then limit the networks to Biomedical and Clinical Sciences, and Public and Allied Health Sciences to help inform what health topics garner attention. RESULTS/ANTICIPATED RESULTS: Our initial Altmetric topic models revealed sustained attention for COVID-19 and vaccination-related publications well beyond the pandemic (specifically, papers from January 2023). Health topics like cancer, dementia, and obesity also garnered high attention. Additionally, political papers (elections, democracy), climate change, and battery research had notable attention values. Further analysis needs to be done to explain why these topics gain attention and the type of attention they garner. We will construct networks to see the relationship between attention and entities like universities, funding sources, journals, and publishers. This will identify whether certain clusters of these entities produce papers with high attention or if attention is distributed evenly amoung them. DISCUSSION/SIGNIFICANCE: To gauge the broader impact of scholarly research alternative metrics beyond citations are needed. Altmetric is used widely by CTSA’s to measure the community interest in research. Understanding the types of research that gain traction on Altmetric can help researchers understand how to garner interest from the community.

Drivers of citations in social pharmacy and practice research articles

BackgroundResearch in Social and Administrative Pharmacy has been expanding in the last decade. The recently published Granada Statements offer key recommendations to improve the quality of research in this field. ObjectivesTo identify the factors associated with the citations of articles in the field of social, administrative, clinical pharmacy and practice research. MethodsThis study was a retrospective, observational analysis of articles published in three leading journals. Per article Google Scholar citations was the dependent variable. Predictor variables were extracted from all articles published from 2013 to 2015. The dependent variable was dichotomized using sample's median Google Scholar citations. Logistic regression analysis was performed to identify independent predictors of citations ≥ median. ResultsThe median number of citations per article was 17 (range 0–341), with a mean of 24.2 (SD 27.6). The number of references included in the articles (OR 1.03, CI 1.02–1.04), the year of publication (OR 0.31 CI 0.21–0.46 for articles published 2015), article social media mentions (OR = 1.01, CI 1.01–1.03 and OR 1.10 CI 1.04–1.18 for Facebook and X, respectively), the topic area of research namely pharmacy services (OR 1.65, CI 1.06–2.57) and medication adherence (OR 2.22 CI 1.13–4.33) were independently associated with article having citations ≥ median. ConclusionsThe number of references, the year of publication, social media mentions and the topic area of research, namely pharmacy services and medication adherence, were associated with citations above median in the leading journals of social and administrative pharmacy research. Authors may consider providing a thorough literature review in their articles, while researchers, editors, and publishers are advised to use social media to promote newly published work. This article complements the Granada Statements and may contribute to fostering wider dissemination of the discipline's outputs.

텍스트마이닝 분석을 통한 가상 인플루언서의 인식 및 활용 방안에 관한 연구

The virtual Influence market is gradually expanding, and its influence is growing as it provides inspiration for tastes and lifestyles. However, research on public awareness and utilisation method regarding this phenomenon is still lacking. In this respect, this research investigated issues on virtual influencers that have appeared in the news and social media over the past two years divided into two periods based on the lifting of outdoor mask mandates during the COVID-19 pandemic. Frequency analysis, N-gram analysis, CONCOR analysis and sentiment analysis were conducted. Through the analysis, the current status of the use of virtual influencers in South Korea and societal perceptions were examined. Based on this, business insights regarding the utilisation of virtual influencers were derived. The analysis revealed that virtual influencers are expanding beyond advertising models to various fields such as finance, fashion, beauty. They are extending their roles to include singers and show hosts, creating economic ripple effects. Despite the increase in positive sentiment towards virtual influencers, there has been a significant decrease in media and social media mentions due to the increase of outdoor activities and related events after the pandemic. The appearance of virtual influencers has evolved to the point where expressions like 'cute', and 'pretty' are used, overcoming uncanny valley. It is assumed that people feel a sense of intimacy, experiencing emotions such as 'love', 'friendship', and 'expectation'. However, it is confirmed that negative perception related to technological anxiety when using new technology based products or services and skepticism about authenticity, implied by the word 'fake' still exist. This research can be a cornerstone for design research related to user journey or scenarios when planning services using virtual influences in the future by helping the public's perception and use of virtual influencers.

Does Altmetric Attention Score Correlate with Citations of Articles Published in High CiteScore Journals

In the ever-evolving landscape of scholarly communication, research impact assessment has expanded beyond traditional citation metrics. Altmetrics, which encompass a wide range of online indicators like social media mentions, downloads, and blog posts, provide insights into the broader societal engagement with scholarly works. This study explores the relationship between Altmetric Attention Scores (AAS) and traditional citation metrics within the Library and Information Sciences (LIS) domain, focusing on high CiteScore open-access journals. The study collected bibliographic data of top 100 articles from Dimensions.ai database that were published between 2013 and 2022 and assesses the alignment between scholarly recognition and online engagement. The top 100 articles were selected based on highest AAS to focus on the most influential and widely-discussed research in order to provide a comprehensive overview of current trends and impactful findings in the field. The dissemination pattern of research highlights across various social web platforms is examined, shedding light on the diverse channels through which research reaches audiences. Correlation analysis reveals a weak and statistically insignificant connection between AAS and citations for the studied journals, emphasising the nuanced nature of scholarly impact in today’s digital landscape. The findings underscore the need to consider both traditional and alternative metrics when evaluating research influence and engagement in the evolving scholarly communication paradigm of the digital age. While this study is confined to specific journals within the LIS domain, its insights contribute to a deeper understanding of the multifaceted nature of research impact assessment.&#x0D;

Research impact in randomized controlled trials of diabetes: an altmetric approach.

This study aimed to assess the impact of research in randomized controlled trials (RCTs) of diabetes and explore the various subject areas related to diabetes that receive attention on social media platforms. Altmetric measures were utilized to collect and extract relevant data, providing valuable insights into the social reach and influence of clinical research beyond traditional citation-based metrics. The research focused on RCTs of diabetes involving at least one Iranian author, indexed in Scopus. Altmetric.com was employed to extract altmetric data, and the collected articles were categorized into 14 subject areas for individual analysis using STATA. The analysis revealed that a majority of the diabetes studies examined nutrition, complications, treatment, genetics, basic mechanisms, and comorbidities of the disease. Conversely, subject areas such as diagnosis, education, gestational diabetes, psychology, physical activity, prevention, dentistry, and economics had fewer studies associated with them. Among social media platforms, Twitter, Facebook, Google+, and Reddit emerged as the most frequently mentioned platforms. Furthermore, Mendeley readership was identified as the preferred platform for engagement across several subject areas. The substantial number of social media mentions indicates a significant level of public interest and concern regarding diabetes. Social media platforms serve as effective tools for disseminating research findings from clinical trials. Altmetric data proves valuable to researchers and funding agencies seeking to comprehend the impact of their work, enabling them to allocate resources more effectively.

Measuring engagement with shark research in science, news and social media, and policy: A bibliometric analysis

Shark conservation is an urgent and complex biodiversity matter. While research on sharks is an important output of the knowledge production processes that could inform conservation policy and management decisions, whether all relevant knowledge is reaching the public and policy-makers has been questioned. Concerns have been expressed that attention given to research is skewed towards specific and often more sensationalist topics that do not provide an accurate picture of the shark-related issues and of possible solutions to decision-makers and the general public. This study thus analysed Web of Science publications related to sharks to determine the degree of attention different areas of shark-related research received in science, social media, news media, and policy documents. Highly concentrated distributions of citations, and mentions in social media, news media, or policy documents were found, but little relationship exists between the attention that individual publications or research areas receive in the different spheres. These findings show the diversity of shark-related research and its audiences and suggest a need for research evaluation to acknowledge that research impact can take many forms. In addition, developing outreach strategies is needed to ensure that relevant research is adequately disseminated to the public and policy-makers. This study can help researchers, resource managers, and other stakeholders better understand the diverse body of scientific evidence that could be mobilized into policies and practices for shark conservation.

Publishing on Topical Subjects in Total Joint Arthroplasty Is Associated With Increased Social Media Attention

BackgroundSocial media platforms are often used for research dissemination and collaboration. Given the increased prevalence of online-only publications, understanding what drives research dissemination is important. Here, we analyzed factors associated with increased social media attention among peer-reviewed publications in total knee arthroplasty, total hip arthroplasty, and unicompartmental knee arthroplasty. MethodsWe analyzed publications about total knee arthroplasty, total hip arthroplasty, or unicompartmental knee arthroplasty from 2010 to 2022 using a national database. We analyzed a weighted count of social media mentions, using negative binomial regressions adjusting for days since publication. Publications on “hot topics” in arthroplasty were examined including navigation/robotics, COVID-19, race/ethnicity, body mass index, and reimbursement. There were 9,542 publications included, 4,216 (44%) were open access (OA), 338 (3.5%) included navigation, 32 (0.34%) discussed race/ethnicity, 20 (0.2%) discussed COVID-19, 3,840 (40%) were randomized studies, 30 (0.3%) discussed reimbursement, and 2,867 (30%) were in top-10 orthopaedic journals. ResultsFactors associated with higher weighted score included studies about COVID-19 (50 versus 6.0, P < .001), race/ethnicity (15.8 versus 6.0, P < .001), OA status (6.3 versus 5.8, P = .001), and randomized studies (6.5 versus 5.7, P < .001). Studies from top-10 journals had a lower score (5.8 versus 6.2, P = .025), as did studies about body mass index (3.4 versus 6.1, P = .001). Studies about navigation and reimbursement did not have significantly different scores. ConclusionsStudies on COVID-19, race/ethnicity, randomized studies, and OA publication were associated with increased social media while those in top-10 orthopaedic journals had lower scores. Level of EvidenceLevel IV, Prognostic Study.

Research on the evaluation of academic journals from a multidimensional fusion measurement perspective

PurposeThis paper aims to conduct a comprehensive analysis to evaluate the current situation of journals, examine the factors that influence their development, and establish an evaluation index system and model. The objective is to enhance the theory and methodologies used for journal evaluation and provide guidance for their positive development.Design/methodology/approachThis study uses empirical data from economics journals to analyse their evaluation dimensions, methods, index system and evaluation framework. This study then assigns weights to journal data using single and combined evaluations in three dimensions: influence, communication and novelty. It calculates several evaluation metrics, including the explanation rate, information entropy value, difference coefficient and novelty degree. Finally, this study applies the concept of fuzzy mathematics to measure the final results.FindingsThe use of affiliation degree and fuzzy Borda number can synthesize ranking and score differences among evaluation methods. It combines internal objective information and improves model accuracy. The novelty of journal topics positively correlates with both the journal impact factor and social media mentions. In addition, journal communication power indicators compensate for the shortcomings of traditional citation analysis. Finally, the three-dimensional representative evaluation index serves as a reminder to academic journals to avoid the vortex of the Matthew effect.Originality/valueThis paper proposes a journal evaluation model comprising academic influence, communication power and novelty dimensions. It uses fuzzy Borda evaluation to address issues related to the weighing of single evaluation methods. This study also analyses the relationship of the three dimensions and offers insights for journal development in the new media era.

The relation between social media mentions and academic citations in orthodontic journals: A preliminary study.

To study the relation between social media mentions and academic citations for articles published in peer-reviewed orthodontic journals. Articles published in early 2018 in seven peer-reviewed orthodontic journals were retrospectively analyzed in September 2022. Citation counts of the articles were evaluated using two databases: Google Scholar (GS) and Web of Science (WoS). The Altmetric Attention Score, Twitter, Facebook mentions, and Mendeley reads were tracked using the Altmetric Bookmarklet. The citation counts and social media mentions were correlated using Spearman rho. A total of 84 articles were identified during the initial search; 64 (76%) were original studies and systematic review articles and included in the analysis. A total of 38% of the articles had at least one mention on social media. Over the study period, the average number of citations of the articles mentioned on social media was higher than the non-mentioned articles for GS and WoS, respectively. Moreover, significant positive correlations existed between the Altmetric Attention Score and the number of citations in GS and WoS (rs=0.31, P=0.001 and rs=0.26, P=0.04). Social media mentions and citations of articles published in peer-reviewed orthodontic journals are correlated, with a clear difference in the number of citations in articles mentioned on social media versus those not mentioned, indicating possible increased reach of articles disseminated on social media.

How do people communicate about sensory descriptors in social media? An investigation comprising floral descriptors, four beverages, and thirteen English‐speaking countries

AbstractThe internet has become a mainstay of modern‐day life, with people worldwide using social media platforms to discuss ideas and exchange opinions. In recent years, social media platforms have become a data source for research focusing on consumers' natural and spontaneous lexicons. The increased use of social media and virtual meetings means people can exchange ideas, and cultural boundaries have blurred. Thus, this study aims to investigate how culture influences the use of the beverage descriptor “floral” on social media for four different beverages when people share the same language. A social media study was performed, collecting data over 1 year in 13 English‐speaking countries: Australia, Canada, South Africa, the United Kingdom, Singapore, New Zealand, and seven Caribbean Islands. Words associated with four beverages (beer, cocktails, tea, and wine) and floral were filtered on social media mentions. A total of 258,221 mentions were obtained from different types of social media such as Twitter, Instagram, Facebook, and so forth. The mentions were filtered to obtain the frequency of words by country. Each beverage was analyzed separately, and contingency tables were arranged by country and descriptor. A correspondence analysis was performed on each contingency table to identify relative similarities and dissimilarities between the countries in the study. Overall, rose was the most cited floral descriptor, and there was a link between beer and wine descriptions. However, for cocktails and tea, the floral descriptors varied per country. Thus, it suggests that the impact of culture on the use of floral descriptors depends on the beverage being discussed.Practical ApplicationsThe results obtained in this study have relevance for people interested in sensory and specifically in beverage descriptions, as well as those involved in the alcohol industry, particularly those involved in beer and wine, and the non‐alcohol industry (tea). These results can drive the construction of applied and effective marketing strategic plans for the beverage and flavor industry in the areas covered by the study.

Twitter Gynecologic Surgery Journal Club: Impact on Citation Scores and Social Media Attention

To study the impact of a Twitter-based gynecologic surgery journal club of articles published in the Journal of Minimally Invasive Gynecology (JMIG) on their social media attention and citation scores. A cross-sectional study. N/A. N/A. Comparison of citation and social media attention scores was conducted for all articles presented in the JMIG Twitter Journal Club (#JMIGjc), a monthly scientific discussion on Twitter of JMIG selected articles, between March 2018 and September 2021 (group A), with 2 matched control groups of other JMIG articles: group B, articles mentioned on social media but not promoted in any JMIG social media account, and group C, articles with no social media mentions and not presented in #JMIGjc. Matching was performed for publication year, design, and topic in a 1:1:1 ratio. Citation metrics included number of citations per year (CPY) and relative citation ratio (RCR). Altmetric Attention Score (AAS) was used to measure social media attention. This score tracks research articles' online activity from different sources such as social media platforms, blogs, and websites. We further compared group A with all JMIG articles published during the same period (group D). Thirty-nine articles were presented in the #JMIGjc (group A) and were matched to 39 articles in groups B and C. Median AAS was higher in group A than groups B and C (10.00 vs 3.00 vs 0, respectively, p <.001). CPY and RCR were similar among groups. Median AAS was higher in group A than group D (10.00 vs 1.00, p <.001), as were median CPY and RCR (3.00 vs 1.67, p=.001; 1.37 vs 0.89, p=.001, respectively). Although citation metrics were similar among groups, #JMIGjc articles had higher social media attention metrics than matched controls. Compared with all publications within the same journal, #JMIGjc articles resulted in higher citation metrics.

Coastal Adaptation and Vulnerability Assessment in a Warming Future: A Systematic Review of the Tourism Sector

The uncertainty behind a warming climate produces significant risk for communities that rely on tourism, but vulnerability assessment can help inform planning for adaptation and mitigation efforts. Since coastal regions have significant tourism economies, and rely on the tourism sector for socio-economic stability, we seek to understand how assessments of vulnerability have been applied in coastal communities by systemically assessing literature that describes the concepts of adaptation, resilience, and vulnerability. We conducted a systematic search across three peer-reviewed journal databases (Web of Science, Scopus, and PubMed) to compare the types of methods and models used to determine coastal adaptation and vulnerability in various geographical and demographic settings. The systematic process found 205 unique articles; 143 were deemed relevant as they focused on adaptation, resilience, or vulnerability assessment. A qualitative analysis of the key themes of relevant studies, identified using thematic coding, found that vulnerability and adaptation research in tourism-based coastal communities is predominantly done through qualitative methods, researched more frequently in higher-populated areas of Europe and North America, have a focus on water as a driver of vulnerability, focus on socio-economic impacts of vulnerability, and emphasize locally-based knowledge in understanding adaptive capacity. Bibliometric analysis of citations and mentions in social-media reveal a larger number of papers with a higher citation rate focused on coastal-based systems (salt-water) with an emphasis on regional studies rather than those with a specific urban or rural focus. We found few studies aimed at coastal communities using tourism operators as informants, but rural coastal communities had higher social-media metrics indicating their comparative public importance. Thus, we highlight the need for locally-informed case studies in vulnerability and adaptation assessment for small coastal communities.

COVID-19 topics and emotional frames in vaccine hesitation: A social media text and sentiment analysis.

Addressing gaps in COVID-19 vaccine-hesitancy research, the current study aimed to add depth and nuance to the exploratory research examining vaccine-hesitant groups. Using a larger, but more focused conversation occurring on social media, the results can be used by health communicators to frame emotionally resonant messaging to improve COVID-19 vaccine advocacy while also mitigating negative concerns for vaccine-hesitant individuals. Social media mentions were collected using a social media listening software, Brandwatch, to examine topics and sentiments in COVID-19 hesitancy discourse during a period of September 1, 2020, through December 31, 2020. The results from this query included publicly available mentions on two popular social media sites, Twitter and Reddit. The dataset of 14,901 global, English language messages were analyzed using a computer-assisted process in SAS text-mining and Brandwatch software. The data revealed eight unique topics before being analyzed by sentiment. Among the COVID-19 hesitancy data, trust-related topics emerged that included declining vaccine acceptance, a parallel pandemic of distrust, and a call for politicians to let the scientific process work, among others. Positive sentiment revealed interest in the sources which included healthcare professionals, doctors, and government organizations. Pfizer was found to elicit both positive and negative emotions in the vaccine-hesitancy data. The negative sentiment tended to dominate the hesitancy conversation, accelerating once vaccines hit the market. Relevant topics were identified to help support targeted communication, strategically accelerate vaccine acceptance, and mitigate COVID-19 vaccine hesitancy among the public. Strategic methods of online and offline messaging tactics are suggested to reach diverse, malleable populations of interest. Topics of personal anecdotes of safety, effectiveness, and recommendations among families are identified as persuasive communication opportunities.

Patient perspectives of atopic dermatitis: comparative analysis of terminology in social media and scientific literature, identified by a systematic literature review.

Atopic dermatitis (AD) is a chronic skin disease that significantly impacts patient quality of life (QoL). It is unknown whether patients and physicians have the same interpretation of AD burden. Unmet needs and AD disease burden were evaluated by comparing terminology used in social media with terminology used in scientific literature. AD terminology in social media was identified using the NetBase platform, and natural language processing was performed. Topics and words driving negative sentiment were evaluated overall and in relation to specific symptoms. The systematic review of scientific literature identified publications that included AD and QoL terms was identified from PubMed. Term analysis of titles and abstracts was conducted via natural language processing. The occurrence of topics and co-occurrence of words associated with QoL terms were evaluated. More than 3 million social media mentions (2018-2020) and 1519 scientific publications (2000-2020) were evaluated. There were more negative than positive social media mentions, and flare and pain were common symptoms driving negative sentiment. Face and hands were major drivers of negative sentiment in relation to AD symptoms in social media. Sleep and pain were often mentioned together. In scientific literature, pruritus and depression were the most frequently occurring symptoms. Similarly, pruritus was the most common AD symptom co-occurring with QoL terms in the assessed scientific literature. Social media analyses provide a unique view into the patient experience of AD. Symptoms driving negative sentiment in social media appear to be discordantly represented in scientific literature. Incorporating patient perspectives may improve disease understanding and management.

Information coverage of protests in the Republic of Belarus in 2020 in social media and mass media: Dynamics and patterns

The article presents a socio-media analysis of protest moods in the Republic of Belarus in 2020. As part of working with a database collected through IQ Buzz, the author presented the dynamics of protest mentions in social media by main time intervals and cities of the country, the rating of the most popular words, and also showed the role of external forces in influencing the protest moods of Belarusian citizens. The results obtained allow us to consider the process of organizing mass protests through media tools as a technology with its own patterns and features.