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In October 2021, National Basketball Association player Kyrie Irving was banned from competing for the Brooklyn Nets because of his resistance to being vaccinated for COVID-19. Two months later, the Nets softened that stance and allowed Irving to participate in road games. This study examines two prongs of the social media response to Irving's vaccination status. A total of 12,000 posts were collected from the U.S.-based Twitter (now known as X; 6,000) and the Chinese-based Weibo (6,000), covering the first week of coverage of Irving and the Nets' announcement. Results showed that Hofstede's cultural dimensions help explain the theme differences, with Twitter's comments reflecting more individualistic notions and lower power distance than Weibo. Moreover, Twitter users focused more on opinion-based expression themes, while Weibo users avoided commenting on the COVID-19 policy. These findings contribute to the literature by identifying the role culture plays in people's response to a social issue. [ABSTRACT FROM AUTHOR]

The academic literature reports mixed evidence on how social media platform and message impact consumer engagement. We investigated the effects of three platforms (Facebook, Instagram, and Twitter) and three message themes (sales, informational, and relationship building) on six consumer engagement actions (comment, like, search, share, talk about, and purchase) in a lab experiment. College students responded to social media posts featuring their National Collegiate Athletic Association Division I women's basketball team. Results for platform show that participants were more likely to comment on Facebook and Twitter (vs. Instagram) and more likely to purchase on Twitter (vs. Instagram). Results for message theme show that participants were more likely to comment, like, and share informational and relationship building posts and more likely to purchase after sales posts. Results for message theme vary by gender for search and talk about (with others). These results can help sport marketers develop social media content that drives specific engagement actions. [ABSTRACT FROM AUTHOR]

The sport industry is at an inflection point where all major professional sport leagues in North America are struggling to attract the same avid fans, once a staple within the industry. Furthermore, not only are the number of avid fans decreasing, the average age of avid sport fans is increasing. In other words, the current state of the sport industry indicates that fans are decreasing in number while simultaneously aging out of traditional professional sports. The current study aimed to investigate the ability of a traditional sport, NASCAR (National Association for Stock Car Auto Racing) in this case, to utilize an esport, iRacing, to attract new and more diverse fans. Through a partnership with Zoomph, Twitter content was analyzed and revealed the shift from traditional racing to iRacing by NASCAR. Due to the COVID-19 pandemic, it assisted them in attracting new, more diverse fans whose sentiment on Twitter was positive. Overall, the current study demonstrated that traditional sport properties may be well served by tapping into the esport space in an authentic way to enhance their core product(s). [ABSTRACT FROM AUTHOR]

Marketers frequently create social media content (i.e., firm-generated content; FGC) to ignite interest in new movies. Thus, there is a clear need to understand the magnitude and heterogeneity of the effect of FGC on movie demand and associated user-generated content (UGC). The authors empirically examine the complex interactions among FGC, UGC, and sales using social media (tweet) data that are normally available to firms. They investigate two potential mechanisms by which FGC may drive box office revenues: (1) a direct mechanism, such that users who see FGC directly drive revenue, and (2) an indirect "ripple effect," by which FGC increases movie-related UGC, which then drives consumption. By analyzing 145,502 firm-generated and 5.9 million user-generated Twitter posts associated with 159 movies, the authors find a positive and significant effect of FGC on movie sales, which UGC fully mediates, which supports the indirect ripple effect reasoning. Impressions of FGC by followers of firm accounts, as opposed to nonfollowers of firm accounts, mainly drive the effect of FGC on UGC. In addition, FGC by movie accounts is more effective than that by actors and studios. Firms' regular posts with a movie-specific hashtag are more effective than replies, retweets, and posts without the hashtag. The finding of the ripple effect suggests that movie executives should focus on creating FGC that sparks conversations among followers when new movies are released. [ABSTRACT FROM AUTHOR]

The paper will investigate the complexities involved in moderating casteist content on major social media platforms. Focusing on the challenges of categorizing hate speech targeting India's marginalized caste-oppressed minorities, the research aims to delve into the mechanisms utilized by platforms for content moderation. It will critically analyze existing categorization systems, exploring the efficacy and limitations in identifying and addressing casteist comments. By leveraging information sciences concepts like grounded coding and taxonomies, the study will elucidate the complexities of classifying caste-related hate speech within these systems. Moreover, it will highlight the implications of inadequate categorization on content visibility and community impact.

BackgroundManually analyzing public health-related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes.ObjectiveWe aimed to assess the feasibility of using LLMs for topic model selection or inductive thematic analysis of large contents of social media posts by attempting to answer the following question: Can LLMs conduct topic model selection and inductive thematic analysis as effectively as humans did in a prior manual study, or at least reasonably, as judged by subject matter experts?MethodsWe asked the same research question and used the same set of social media content for both the LLM selection of relevant topics and the LLM analysis of themes as was conducted manually in a published study about vaccine rhetoric. We used the results from that study as background for this LLM experiment by comparing the results from the prior manual human analyses with the analyses from 3 LLMs: GPT4-32K, Claude-instant-100K, and Claude-2-100K. We also assessed if multiple LLMs had equivalent ability and assessed the consistency of repeated analysis from each LLM.ResultsThe LLMs generally gave high rankings to the topics chosen previously by humans as most relevant. We reject a null hypothesis (P

Climate communication scientists search for effective message strategies to engage the ambivalent public in support of climate advocacy. The personal experience of wildfire is expected to render climate change impacts more concretely, pointing to a potential message strategy to engage the public. This study examined Twitter discourse related to climate change during the onset of 20 wildfires in California between the years 2017 and 2021. In this mixed method study, we analyzed tweets geographically and temporally proximal to the occurrence of wildfires to discover framings and examined how frequencies in climate framings changed before and after fires. Results identified three predominant climate framings: linking wildfire to climate change, suggesting climate actions, and attributing climate change to adversities besides wildfires. Mean tweet frequencies linking wildfire to climate change and attributing adversities increased significantly after the onset of fire. While suggesting climate action tweets also increased, the increase was not statistically significant. Temporal analysis of tweet frequencies for the three themes of tweets showed that discussion increased after the onset of a fire but persisted typically no more than 2 weeks. For fires that burned for longer periods of more than a month, external events triggered climate discussions. Our findings contribute to identifying how the personal experience of wildfire shapes Twitter discussion related to climate change, and how these framings change over time during wildfire events, leading to insights into critical time points after wildfire for implementing message strategies to increase public engagement on climate change impacts and policy.

As social media is increasingly used by communities to understand and cope with environmental hazards, understanding how people use social media before, during, and after disasters can support disaster response and recovery efforts. This paper presents an empirical application of Houston et al.’s (Disasters 39:1–22, 2015) functional framework for disaster social media, using the case of Twitter use during and after Hurricane María. Our research aims to (1) identify the predominant patterns of Twitter usage and content dissemination during the Hurricane María crisis and (2) validate and refine the functional framework for disaster social media with a case study of the hurricane that hit Puerto Rico in 2017. We find that people in the US used Twitter mainly to access news of the hurricane, express emotions (both negative and positive), and to understand socio-political events shaping the response and recovery. Most tweets came from individuals rather than organizations, and most were sent as the hurricane was designated as category four and approached Puerto Rico, with far fewer posts after landfall. These findings highlight the importance of individuals sharing and accessing vital information when official outlets are absent or limited and the relatively short-lived attention to slow recovery processes.

Politicians use social media to engage directly with the public using diverse communication styles including aggressive or uncivil language. Yet, little is known about gender differences in politicians' communication styles and their subsequent online reactions. In this study, we investigate whether women politicians who use critical or insulting language on Twitter face disproportionate backlash compared to men politicians. To test our hypothesis, we employ a self‐developed supervised language classifier to categorize @‐mentions of parliamentarians into two incivility levels: criticism and insults. We find that men and women MPs tweet with a similar level of incivility, including both critical and insulting language. For critical language, we find that both men and women MPs receive more critical responses when sending a higher number of critical tweets. In the case of insulting language, we find evidence of a gendered pattern: Compared to men MPs, women MPs receive a higher number of insulting tweets but can reduce such responses to a small degree when being more insulting themselves. These findings underscore that female MPs navigate a more hostile online environment that compels them to use more insulting language as a means of self‐defense. [ABSTRACT FROM AUTHOR]

Past research has studied social determinants of attitudes toward foreign countries. Confounded by potential endogeneity biases due to unobserved factors or reverse causality, the causal impact of these factors on public opinion is usually difficult to establish. Using social media data, we leverage the suddenness of the COVID-19 pandemic to examine whether a major global event has causally changed Americans’ views of another country. We collate a database of 297 million posts on the social media platform Twitter about China or COVID-19 up to June 2020, and we take tweeting about COVID-19 as a proxy for an individual’s awareness of COVID-19. Using regression discontinuity and difference-in-difference estimation, we reveal that awareness of COVID-19 causes a sharp rise in anti-China attitudes. Our work has implications for understanding how self-interest affects policy preference and how Americans view foreign countries. [ABSTRACT FROM AUTHOR]

Social media allow citizens to express their opinions on all aspects of life and society, and this trend has been enhanced during the COVID-19 crisis, when more "traditional" ways of opinion expression were not possible. To get the feeling of Twitter users' opinions on topics of importance we analysed tweets and combined them with relevant news, thus allowing for potential event detection. We showcase the prototypical framework that we have developed with our findings about European COVID-19 mobile contact tracing apps in tweets posted between 09/07/2020 and 10/07/2021. We obtained both high-level results (for example, trending twitter activity, sentiment polarisation of important hashtags, etc.) and more specific ones (such as, the spatial distribution of tweets regarding a specific app), which indicate that our approach can be applied in the future to get useful insights on topics of public interest that result in active discussions on social media platforms. [ABSTRACT FROM AUTHOR]

Abstract\nKEY MESSAGEThis study assessed the impact of posting video abstracts on journal articles and authors’ X engagement. European Journal of Sport Science articles were disseminated on X as animated video abstracts (AN), author-provided video abstracts (AU), or title-only (TO) posts. Metrics, including page views, Altmetric Attention Score (AAS), X engagements, impressions, link clicks, media engagements, and views, were compared at 7 and 30 days. Authors’ X presence and video abstract creation were also examined. Page views did not differ between groups after 7 or 30 days. After 7 days, AN received significantly more AAS, impressions, media views and media engagements than AU or TO. After 30 days, AN received significantly more AAS, impressions, engagements, media views and media engagements than AU or TO. TO received significantly more link clicks than AU or TO after 7 and 30 days. Fifty percent of authors have an X account and 11.2% indicated interest in creating a video abstract. Articles promoted using animated video abstracts received more attention, reach and impact on X than those promoted using author-provided video abstracts or title-only posts. Animated video abstracts can be used by authors to effectively promote their research findings and increase their visibility on social media.Animated video abstracts are a valuable dissemination strategy for medical journals and researchers to promote their research, increasing visibility on X.Limited X adoption (50%) and low interest in creating video abstracts (less than 25%) among EJSS authors highlight the need to promote X use and video abstract creation.Future research should validate these findings, assess video abstract posts’ impact on citations, and evaluate free versus paid access effects.Guidelines should be developed to assist researchers in translating research abstracts into video abstracts, facilitating the development of effective video abstracts.EJSS articles promoted on X with animated video abstracts had greater attention, reach, and impact, urging authors to embrace X and video abstracts. [ABSTRACT FROM AUTHOR]

Terrorism causes emotional reactions among public audiences, with downstream consequences for their well-being, attitudes and policy preferences. We utilise a novel approach which harnesses a unique dataset of Twitter activity from 324K users to precisely capture emotional responses to terrorism. Our results demonstrate that terrorist attacks induce dramatic spikes in various discrete emotions of a negative valence, which vary based on the characteristics of the attacks. Furthermore, we show that the terrorism-induced effects on emotions are accompanied by changes in feelings about immigration. [ABSTRACT FROM AUTHOR]

Half of all species are predicted to face extinction by the end of the century. Despite this, awareness of certain species' extinctions remains surprisingly muted, highlighting the need to improve and quantify public awareness. We explore the connection between biodiversity loss and public awareness by quantifying the changes in online interest on Twitter (now known as X) and Wikipedia both before and after the extinctions of eight species and following their reclassification in the IUCN Red List. Our findings reveal that extinction announcements generally spike online interest for most species, albeit briefly on Twitter (i.e. tweets and retweets about species), while Wikipedia (i.e. article pageviews of species) exhibits a more prolonged interest. IUCN reports were generally not associated with increased interest. Coordinated media coverage, especially when aligned with broader environmental narratives and key events, enhanced the impact of extinction announcements. On Twitter, spatially we observed a shift from local to global interest of users following extinction. We also found a small subset of influential users on Twitter, including content creators and media organisations, who disproportionately shaped conservation discussions. Environmentally oriented individuals and organisations also play a significant role, collectively comprising a third of the top retweeted users. Overall, these results highlight the need for conservation bodies, such as the IUCN, to engage more directly both with media organisations and content creators in order to drive public interest for conservation efforts, especially for less charismatic species. The tragedy of species extinction necessitates such efforts to ensure sustained and meaningful public awareness. Our findings also show that while social media outlets can generate global interest quickly, which may drive public discussions regarding ongoing extinctions and potential future de‐extinctions, this is likely to be short‐lived, underscoring the importance of alternative platforms such as Wikipedia, which can foster longer‐term engagement. [ABSTRACT FROM AUTHOR]

Aim: The evolution of the utility of medical social media and its global reach has led to a much greater speed of dissemination of medical innovation, such as transanal total mesorectal excision (TaTME). The acceptability and discussions surrounding such innovations can be followed online. Here, we sought to determine if online discussions over time could match known models of innovation evolution using the example of TaTME since its initial description in 2010. Methods: Data on using the X hashtag #TaTME were analysed using the social media analytics tool Brandwatch. Trends in mentions, impressions and reach were highlighted over 13 years (1 May 2010 to 31 July 2023). Each mention's sentiment and emotional connotations were analysed using Brandwatch's natural language processing approach. Results: We identified 18 525 mentions of #TaTME by healthcare professionals, reaching over 30.6 million X users. A Gartner's hype‐cycle‐like pattern was identified for mention volume and emotional connotation over time. The majority of mentions had a neutral (84%; n = 15 341) or positive connotation (15%, n = 2675). A peak of negatively connotated mentions was identified surrounding the temporary suspension of TaTME in 2019. Conclusion: This study presents a novel method of monitoring online discussions surrounding new surgical innovations by healthcare professionals based on sentiment analysis of public social media data. Mention volume and emotional connotation were the most accurate parameters closely resembling Gartner's hype cycle. [ABSTRACT FROM AUTHOR]

We examine policymakers' nuanced strategies of digital agenda setting during times of lawmaker uncertainty versus anticipated policy communication. Whereas existing agenda‐setting studies tend to focus on how policymakers allocate attention to preferred policies, we explain how policymakers react to an issue in a digital media climate where the expectation is engagement. We explore the dynamics of digital agenda setting with U.S. senators' Twitter activity in response to the unexpected document leak overturning Roe v. Wade and the anticipated, subsequent Supreme Court decision. Policymakers across the political spectrum quickly reacted to both events, capturing shared policy attention, yet did so with variable response times and differing frames for the issue. We argue that when the agenda rapidly contracts and issues become salient on Twitter, the uncertainty, time, and tenor of lawmakers' response tell us about their policy‐making priorities. Punctuated attention cycles churn fast in a digital climate, but even amid these quick, attention‐grabbing news cycles, the nuance of those moments and policy uncertainty suggest that rhetorical agendas differ when galvanizing events are anticipated. How policymakers convey their agenda when the media environment incentivizes lawmakers to respond regardless of issue prioritization is fundamental to understanding policy attention by lawmakers operating a digital media environment. [ABSTRACT FROM AUTHOR]

Sarcasm is often related to something that has created a mass confusion among the general uninformed public. It is always associated with a mockery tone or trenchancy facial expression or weird language. Existing literatures that are profound in the field of sarcasm detection mainly focused on text-based input with sarcastic comments or facial expression-based analysis, i.e., image input. But both text and image input are not sufficient to analyze the underlying sarcasm behind the scene. This kind of analysis can also be misleading sometimes as the emotional expression can change with social circumstances (i.e., audio tone) over time. Hence to address these challenges, "A Smart Video Analytical framework for Sarcasm Detection using Deep Learning" is introduced where sarcasm detection is done by considering video modality. Proposed model extracts three important features from the video, i.e., text using proposed Enhanced-BERT, image using ImageNet and audio using Librosa. After extraction, each modality is addressed individually and is finally fused using proposed adaptive early fusion approach. The final task prediction of classification is done using novel deep neural network called "SarcasNet-99" to detect sarcasm in video over distributed framework called Apache Storm. TedX and GIF Reply datasets are used for model training and testing with around 10,000 + video clips. When compared against existing state-of-the-art techniques such as AlexNet, DenseNet, SqueezeNet and ResNet, the proposed model predicted accuracy 99.005% with LeakyReLU activation function. [ABSTRACT FROM AUTHOR]

We assessed the perceived risks of COVID vaccines using a Health Belief Model (HBM) among the American public during the vaccination roll-out in the USA. We employed a retrospective study of 1,149 adults from the 2020 American National Election Studies surveys to assess the public's belief about the COVID-19 vaccine during the pandemic. The logistic regression analysis found several predictors of perceived health risks of the COVID vaccine. For urban/suburban residents, having higher education, being older, being White, and having higher income emerged as protective factors. People with these characteristics are less likely to perceive the COVID vaccine as risky. Also, higher use of Twitter emerged as a protective factor for residents from urban/suburban regions. However, residents from rural/small towns who use Facebook often are more likely to perceive the COVID vaccine as risky. Perceived risks of vaccination are high among Facebook users of residents from rural/small towns and low among Twitter users among residents from urban/suburban areas. The authors identified several protective factors: being educated, older, economically well-off, and White. The authors propose interventions to reduce perceived risks and vaccine hesitancy among vulnerable populations. [ABSTRACT FROM AUTHOR]

Legacy media contribute to gendered depictions of culinary themes by associating meat with masculinity, influencing social realities. The current research examines whether similar gendered representations can be found on social media, reinforcing gendered patterns in food consumption. Using content analysis, we examine how men and women tweet about the (non-)consumption of meat. Results confirm gender stereotypes: men tweet more about meat and are more likely to hold negative attitudes toward vegetarianism and veganism. These expressions may reinforce gendered meat consumption patterns, where men continue to choose meat over more healthy and sustainable options. [ABSTRACT FROM AUTHOR]

This article argues that GamerGate, a critical hashtag event in the history of digital harassment, is key to understanding contemporary identity verification systems and digital labour. We build our argument from a comparative analysis of two case studies: (1) digital journalistic responses to GamerGate and (2) Twitter's account verification 'checkmark' system from 2021 to 2022. These phenomena showcase the linkages between the gendered and raced policing of journalists and users during GamerGate and the rise of 'authenticity' as a key resource for journalists and other platformed creators in the present. We draw on digital games, journalism and critical media studies to analyse the work of 'authenticity'. We argue that platform affordances such as identity verification badges are fundamentally implicated in the work of users to appear 'real', even as the visibility requisite for realness brings uneven risks for marginalised cultural workers. [ABSTRACT FROM AUTHOR]

As sites where social media corporations profess their commitment to principles like community and free speech, policy documents function as boundary objects that navigate diverse audiences, purposes, and interests. This article compares the discourse of values in the Privacy Policies, Terms of Service, and Community Guidelines of five major platforms (Facebook, Instagram, YouTube, Twitter, and TikTok). Through a mixed-methods analysis, we identified frequently mentioned value terms and five overarching principles consistent across platforms: expression, community, safety, choice, and improvement. However, platforms limit their burden to execute these values by selectively assigning responsibility for their enactment, often unloading such responsibility onto users. Moreover, while each of the core values may potentially serve the public good, they can also promote narrow corporate goals. This dual framing allows platforms to strategically reinterpret values to suit their own interests. [ABSTRACT FROM AUTHOR]

In 2017, the MeToo hashtag spread across the globe. However, it showed limited success in the Japanese Twittersphere and instead inspired local initiatives such as #WeToo and #Furawādemo ("flower demo"). To understand this reformulation, we analyzed 15 interviews with Japanese social media users and 119 Japanese newspaper articles. The results corroborate the framework we label VTM (values, topics, media), suggesting that an intersection between perceived Japanese values, the topic's gendered and sexual nature, and media affordances explain the movement's local development. While perceived Japanese values clash against those associated with #MeToo, new formulations "soften" the protest by blending in values such as reserve and harmony. Overall, we show how perceptions of popular values rather than values as essential orientations shape activism. Finally, we discuss the study's implications for understanding cultural variance in cyberactivism, highlighting how divergent notions of "safe space" shape such movements. [ABSTRACT FROM AUTHOR]

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for combining digital data and official statistics by using the official statistics to model the spatial and temporal dependence structure of the biases of digital data. We use simulations to demonstrate the validity of the model, then empirically illustrate our approach by combining geo-located Twitter data with data from the American Community Survey (ACS) to estimate state-level out-migration probabilities in the United States. We show that our model, which combines unbiased and biased data, produces predictions that are more accurate than predictions based solely on unbiased data. Our approach demonstrates how digital data can be used to complement, rather than replace, official statistics. [ABSTRACT FROM AUTHOR]

Purpose: Social media (SM) has been heavily criticised in recent years for its damaging effects on societies globally. Tasked with empowering those same societies, libraries' continued use of SM is considered ethically contentious. This study presents the findings of a University of Sheffield study that investigated the ethical tension between libraries and their use of SM by aiming to establish whether: (1) libraries' use of SM is ethically motivated; (2) ethically informed; (3) and compatible with codes of ethics in the Library and Information Science (LIS) sector. Design/methodology/approach: A phenomenographic approach was employed to gather and analyse the data for this study, which is drawn from the transcripts of seven online interviews with Bodleian Libraries staff who used Twitter, now X, in a professional capacity. Findings: Three categories of description were identified among participants: (1) Collectivist conception; (2) Settled conception; (3) Questioning conception. The categories are bound by a shared context of conceptualisation made up of a small set of internal and external influences discussed in the interviews which affected all participants to varying degrees. Originality/value: The findings were used to support the following determinations: (1) Libraries' use of SM is ethically motivated. (2) Libraries' use of SM is ethically informed, in part. Due to lack of evidence, no determination was made about whether libraries' use of SM is compatible with codes of ethics in the LIS sector. Recommendations for LIS professions and professional bodies are offered based on these determinations. [ABSTRACT FROM AUTHOR]

Twitter has emerged as an alternative way for actors in agenda-setting on specific issues, creating trending topics, and reaching decision-makers. This open digital environment causes rapidly-changing agendas as it welcomes all the actors and individuals. Thus, it becomes a complex agenda-setting process on Twitter for such a significant issue as sustainable development. This study carried out on the scope of Turkey conducts a content analysis on 3713 sustainable development-themed tweets to investigate the related actors, their motivations, and interactions while questioning how a more effective agenda on the issue can be set in this challenging process on Twitter. [ABSTRACT FROM AUTHOR]

Hegemonic masculinity has developed an appearance on Twitter that spreads to every layer of society and naturalizes digital hegemonic masculinity. In the present study examining the digital hegemonic masculinity towards male sports journalists using Twitter in Türkiye, the comments made by male users on the Twitter posts of 9 sports journalists were analyzed using the netnographic method and 5 sports journalists were interviewed to support the results. As a result of the study, it was determined that male sports journalists were exposed to the discourse of digital hegemonic masculinity on Twitter. Based on the findings of the study, it was found that male sports journalists were exposed to profanity/insult as well as physical and online threats on Twitter. Particularly the individuals who are classified as social hooligans (social media fan) and use Twitter with anonymous credentials act in an organized manner and strengthen the discourse of digital hegemonic masculinity and hegemonic discourse. [ABSTRACT FROM AUTHOR]

Self‐presentation in Congress is more nationalized, with digital constituencies on platforms such as Twitter offering new reputation‐building opportunities. Digital constituencies transform traditional expectations of constituent communication, challenging Richard Fenno's theory that representatives adopt an “expansionist” style with constituents during early, vulnerable phases of their tenure. In a digital era that encourages a more national approach, we question how Fenno's distinction between expansionist and protectionist phases of connecting with constituents applies to reputation‐building with digital constituencies. While electorally vulnerable senators still seek to expand their presentation among geographic constituents, digital platforms, such as Twitter, incentivize them to protect their reputation among a digital constituency. We analyzed senators' Twitter communications from 2013 to 2023. We find the electoral vulnerabilities of Fenno's expansionist local model are associated with a protectionist model of engagement with digital constituencies on Twitter. Our study sheds light on the significance of online reputation management and its implications for representing a media‐influenced, modern Congress. [ABSTRACT FROM AUTHOR]

The increasing volume of online reviews and tweets poses significant challenges for sentiment classification because of the difficulty in obtaining annotated training data. This paper aims to enhance sentiment classification of Twitter data by developing a robust model that improves classification accuracy and computational efficiency. The proposed method named Tree Hierarchical Deep Convolutional Neural Network optimized with Sheep Flock Optimization Algorithm for Sentiment Classification of Twitter Data (SCTD-THDCNN-SFOA) utilizes the Stanford Sentiment Treebank dataset. The process begins with pre-processing steps including Tokenization, Stop words Elimination, Filtering, Hashtag Removal, and Multiword Grouping. The Gray Level Co-occurrence Matrix Window Adaptive Algorithm is employed to extract features, such as emoticon counts, punctuation counts, gazetteer word existence, n-grams, and part of speech tags. These features are selected using Entropy–Kurtosis-based Feature Selection approach. Finally, the Tree Hierarchical Deep Convolutional Neural Network enhanced by the Sheep Flock Optimization Algorithm is used to categorize the Twitter data as positive, negative, and neutral sentiments. The proposed SCTD-THDCNN-SFOA method demonstrates superior performance, achieving higher accuracy and lesser computation time than the existing models, respectively. The SCTD-THDCNN-SFOA framework significantly improves the accuracy and efficiency of sentiment classification for Twitter data. [ABSTRACT FROM AUTHOR]

We study the prevalence and characteristics of toxic speech on Twitter in the run-up to the 2022 Italian General election. We analyzed over 8.5 M tweets shared by 450k unique users and employed a machine learning classifier to estimate the toxicity score of their messages. We found that supporters of different political coalitions exhibit varying levels of toxic speech, sending between 6-8% of toxic messages overall. Notably, Centre-Left politicians received more toxic messages on average, with the largest target of hate receiving over 15,000 toxic replies. We employed Generalized Linear Models to study factors that drive hate speech to political targets, finding that, importantly, politicians employing more abusive and harmful language are also more likely to attract more inflammatory speech. Our findings underscore the critical need for targeted interventions to address hate speech online, fostering healthier dialogue and safeguarding democratic discourse. [ABSTRACT FROM AUTHOR]

This paper investigates the gendered linguistic patterns of tweets discussing state-sanctioned and vigilante violence against African American women. The paper considers representations of Black women and Black death as engaged on the social media platform formerly known as Twitter. We utilize the theoretical frameworks of Patricia Hill Collins’ (2022. Black Feminist Thought, 30th Anniversary Edition: Knowledge, Consciousness, and the Politics of Empowerment. London: Taylor & Francis) conceptualization of Black feminist epistemology and controlling images and Kimberle Crenshaw’s (2018. “Demarginalizing the Intersection of Race and sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics [1989].” Feminist Legal Theory 1: 57–80) intersectionality to understand the ways that Black women are discussed, remembered and advocated for on social media platforms in relation to their Black men counterparts. The analysis of over seven million tweets utilizes both qualitative content analysis and computational tools. The paper’s findings concluded that there were differences related to passive and active language based on the gender of the victim of state-sanctioned or vigilante-race-based violence, as well as homophily, specifically name events most frequently used within the context of the state-sanctioned killing of Black women versus Black men. [ABSTRACT FROM AUTHOR]

Previous research has shown that in congressional campaigns, incumbents behave very differently than their challengers, especially on social media. The research that currently exists regarding how candidates use social media during their elections, however, is limited by examining only general election tweets. In this manuscript, we update this work by examining the Twitter behavior of candidates throughout both their primary and general election. By examining the Twitter accounts of candidates in the congressional elections in the state of Virginia in 2022, we show that incumbents and challengers address different issues and use a different tone throughout the various stages of their campaigns. We also show that gender and partisanship have different impacts on the Twitter behavior of candidates in their primaries and general elections. [ABSTRACT FROM AUTHOR]

Background: Physician voices on social media are important for health policy advocacy. However, the extent to which physicians use best practices around health communications strategy is unknown. Methods: We implemented a content analysis of 1373 tweets from 12 physicians who specialize in reproductive health care and participated in a reproductive health-related advocacy training program, to describe their reproductive health advocacy tweets in terms of levels of engagement, tone, framing and target audience. Results: The most common framing centered on identifying abortion and contraception as essential health care services. Approximately one-third used proactive (37%), reactive (33%), and neutral (30%) strategies. Less than one-quarter (19%) of the tweets explicitly self-identified as a physician. Conclusions: Participants used a range of message frames, tones, and audience engagement tactics, suggesting a deliberate health communications strategy. Advocacy training discusses the importance of these domains when using social media for advocacy. [ABSTRACT FROM AUTHOR]

Twitter (X) is increasingly utilized by medical residency programs to boost engagement and potentially enhance ranking. This study aims to evaluate the role of Twitter (X) in neurosurgery residency programs, assessing their online activity, followership, and content to identify current practices and potential improvements. We identified 97/123 neurosurgery residency programs in the United States with Twitter accounts. Active accounts, posting in 2022 and 2023, were matched with the American Association of Neurological Surgeons Neurosurgical Residency Training Program Directory. Tweets from January 2022 through June 2023 were categorized as original or retweets and further subcategorized based on content. Descriptive and correlation analyses were conducted. Twitter (X) accounts were found for 78.8% of accredited neurosurgery programs (n = 97/123), with 68.3% active as of July 2023 (n = 84/123). All active accounts amassed 167,068 followers. Among 5612 tweets identified, 2764 were original content, and 2848 were retweets. Tweets primarily focused on resident or program information (64.3%), research publications (32.0%), and conference participation (9.4%). Only 12.3% (n = 341) of original tweets contained public medical information. A significant correlation (r = 0.493, P < 0.001) was observed between Twitter (X) following and program ranking. The majority of US neurosurgery residency programs actively use Twitter (X), primarily to showcase academic achievements and aid in recruitment. The correlation between Twitter following and program ranking suggests that online engagement reflects program visibility and impact, underscoring the importance of social media in program outreach and strategic management for maximizing program benefits. [ABSTRACT FROM AUTHOR]

This study harnesses the linguistic diversity of Arabic dialects to create two expansive corpora from X (formerly Twitter). The Gulf Arabic Corpus (GAC-6) includes around 1.7 million tweets from six Gulf countries—Saudi Arabia, UAE, Qatar, Oman, Kuwait, and Bahrain—capturing a wide range of linguistic variations. The Saudi Dialect Corpus (SDC-5) comprises 790,000 tweets, offering in-depth insights into five major regional dialects of Saudi Arabia: Hijazi, Najdi, Southern, Northern, and Eastern, reflecting the complex linguistic landscape of the region. Both corpora are thoroughly annotated with dialect-specific seed words and geolocation data, achieving high levels of accuracy, as indicated by Cohen's Kappa scores of 0.78 for GAC-6 and 0.90 for SDC-5. The annotation process leverages AI-driven techniques, including machine learning algorithms for automated dialect recognition and feature extraction, to enhance the granularity and precision of the data. These resources significantly contribute to the field of Arabic dialectology and facilitate the development of AI algorithms for linguistic data analysis, enhancing AI system design and efficiency. The data provided by this research are crucial for advancing AI methodologies, supporting diverse applications in the realm of next-generation AI technologies. [ABSTRACT FROM AUTHOR]

People are becoming more reliant on social media networks to express their opinions about various topics and obtain health information. The study is intended to explore and analyse the sentiments of Indian people related to Covid-19 vaccines as well as to visualise the top most frequently occurring terms individuals have used to communicate their ideas on Twitter about Covid-19 vaccines in India. The Tweet Archiver was used to retrieve the Tweets against 'Covid19vaccine' and 'Coronavirusvaccine' hashtags for the period of 2 months 18 days (4 January 2021–22 March 2021). After collecting data, the Orange software and VOSviewer were used for further analysis. The Tweets were posted across the country, with an immense contribution from Maharashtra (223, 15.58%), followed by Delhi (220, 15.37%) and Tamil Nadu (73, 5.10%). The majority (639, 44.65%) of the Tweets reflect positive sentiments, followed by neutral (521, 38.50%) and negative (241, 16.84%) sentiments, respectively. This signifies that most Twitter users have a favourable opinion towards Covid vaccines in India. Based on the relevance score of the words, the words 'Delhi heart', 'Lung institute', 'Gift', 'Unite2fightcorona', and 'Covid-19 Vaccine' are the leading words appearing in Tweets. The study illustrates the sentiments of the Indian people towards 'Covid-19 vaccines', gains some insights into overall public communication about the topic and complements the existing literature. It can assist health policymakers and administrators in better understanding the polarity (positive, negative, and neutral) of Tweets about Covid-19 vaccines on Twitter to raise public awareness about health concerns and misinformation about the vaccine. [ABSTRACT FROM AUTHOR]

Electoral cycles are highly charged, politically intense moments that influence public discourse. Political elites, citizens, and the traditional news media seek to generate opinions and interactions on social networks. This research is motivated by the following questions: What are the communicative and deliberative practices used in these spaces? Is it possible to identify the characteristics that --through deliberative conversations-- potentially foster or undermine democratic debate, particularly when using populist and polarizing discourse? Using a mixed methods approach, we apply a social network analysis tool to track conversations and identify the volume of political discourse (N=346,000). Using selective and staged filtering, we identified posts from nine Peruvian Twitter accounts during the September 2022 electoral campaign in Lima: three candidates, three media outlets, and three accounts with high levels of engagement. Our data comprised the comments from these nine accounts and was extracted using an Application Programming Interface (API). Subsequently, we carried out ethnographic content analysis on publications with more than 30 comments. In this phase, we analyzed Twitter comments using a codebook to identify deliberative practices and user responses. Our findings underscore the significant role of principal media outlets in shaping political conversation on Twitter. We also discovered that attempts to interact and deliberate were often overshadowed by heated comments attempting to impose opinions on others. Most importantly, our research reveals a widespread disillusionment with politics, political institutions, and even the political preferences of fellow citizens in Peru, highlighting a key challenge for democratic discourse on social media. [ABSTRACT FROM AUTHOR]

The article examines how distrust regarding the COVID-19 pandemic has served as a catalyst for the diffusion of conspiracy theories. It discusses the nature of conspiracy theories, their relationship with institutional distrust, and their representation in the social media. The methodology used is based on the analysis of hashtags from over one million tweets to determine if certain theories act as "gateways" to others. The findings suggest that logical ties exist between distinct conspiracy theories, influenced by distrust towards specific institutions and amplified by the COVID-19 crisis. It is concluded that the combination of conspiracy theories is not random, but rather, it follows an internal logic that is based on distrust, since these theories are interconnected in an internally coherent way within the context of the pandemic. [ABSTRACT FROM AUTHOR]

The Melbourne Cup is Australia's pinnacle horse racing event, attracting more than 80,000 physical attendees each year (pre-COVID-19), as well as numerous others watching via live broadcasts around the country and overseas. In recent times, however, there have been growing calls to boycott the event, following concerns over the treatment of horses. New hashtag movements lobbying against horse racing have also emerged, aided by the affordances of social media. However, very little attention has been paid to these digital movements in the animal-based leisure and recreation literature. In this study, we investigate one such growing movement, namely, #Nuptothecup. We explore how horse racing is framed by digital activists, revealing their moral, socio-cultural, and political objections. Our findings suggest a societal shift towards a strong animal ethics sentiment combined with a more generalised disdain towards the racing industry and its wider societal ramifications. We argue that if #Nuptothecup and related activisms continue to gain momentum, the Cup may eventually lose its social licence to operate. Further, we consider potential opportunities for managers to reinvent horse racing's image and practices, if it is to secure its survival as an Australian recreational institution. [ABSTRACT FROM AUTHOR]

Do campaigns message to voters consistently across different media? And do competing candidates tend to converge over time on a single national style of campaign messaging? To address these questions, this article employs novel data from a content analysis of campaign spots and candidate tweets from the 2015 and 2019 presidential elections in Argentina. We find that the policy orientation of candidate messaging is similar across different media, with spots and tweets addressing specific issues in similar proportions. We also find that, consistent with the theory of success contagion, campaign messaging across candidates and election cycles varies along a wide range of variables as candidates have failed to converge on a similar campaigning style. Contrary to expectations drawn from prior research, we find that candidate tweets contain policy content and attacks on opponents just as often as do campaign spots. [ABSTRACT FROM AUTHOR]

We investigate gender disparities in politics through an exploration of the Italian political Twitterverse. Using network analysis and structural topic models on a novel dataset of Italian politicians' tweets (January 2020 - February 2022), we find that women are as well-connected to their political peers and as active as their male colleagues, and tweet on a wide range of topics emphasizing the sub-issues they care the most. These findings indicate that, as for women's positioning within the politicians' network, their activism and issue attention, Twitter seems to be a more favorable environment than more conventional arenas, where numeric under-representation, appointment to marginal positions, and gender gaps in issue attention are still detectable. [ABSTRACT FROM AUTHOR]

We study the roles of elected officials in the dissemination of misinformation on Twitter. This is a particularly salient online population since elected officials serve as primary sources of information for many stakeholders in the public, media, government, and industry. We analyze the content of tweets posted from the accounts of over 3,000 U.S. state lawmakers throughout 2020 and 2021. Specifically, we identify the dissemination of URLs linked to unreliable content. Our starkest finding is that Republicans share more misinformation than do Democrats by an order of magnitude. Additionally, we uncover distinct patterns in the temporal trends of tweets and tweets associated with misinformation across party and state lines. Delving into the content of tweets referencing unreliable URLs reveals discussions of election integrity, abortion, COVID-19 policies, and immigration. Furthermore, consistent with the literature on asymmetric polarization, Republicans exhibit a greater inclination toward engaging in partisan attacks. We also find that state lawmakers often tweet about state-specific topics. These findings enhance our understanding of misinformation, political communication, and state politics. [ABSTRACT FROM AUTHOR]

Diplomacy is traditionally associated with politeness and civility. As a fundamental element of international relations, diplomacy is rooted in professional skills and codified practices. By moving diplomacy to online platforms, diplomatic statements have been accelerated, sometimes resulting in aggressiveness. The purpose of this paper is to identify outrage in diplomatic communication. Outrage can be defined as uncivil expressions evoking emotion in the audience. This concept is examined based on the tweets produced by the Russian Foreign Ministry account between 1 December 2021, and 24 April 2022 (total: 2485 tweets). Based on the framework proposed by Berry, Jeffrey M., and Sara Sobieraj (2014. The Outrage Industry: Political Opinion Media and The New Incivility. Oxford: Oxford University Press), qualitative analysis identifies 370 outrageous tweets. Frame analysis shows how outrage acts as a narrative tool for activating (self-)representational devices. Moreover, outrage influences the diplomatic tone, international actors' characterisation, and international institutions' delegitimization. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Social media platforms like Twitter offer scientists the opportunity to share professional, personal, and scientific information with the public. This study explores the effects of these self-disclosure types. In an online between-subjects experiment (N = 1458), participants rated scientists who disclosed personal information as more likable but less competent, and scientists who disclosed professional information as more competent and engaging. Subsequently, these perceptions influenced tweet engagement and certain scientific attitudes. Social presence served as a mediator between self-disclosure and perceptions. These findings broaden our understanding of science communication on Twitter as situated within a social media platform. [ABSTRACT FROM AUTHOR]