Social Media Messages Research Articles

Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages

Social media messages posted by people during natural disasters often contain important location descriptions, such as the locations of victims. Recent research has shown that many of these location descriptions go beyond simple place names, such as city names and street names, and are difficult to extract using typical named entity recognition (NER) tools. While advanced machine learning models could be trained, they require large labeled training datasets that can be time-consuming and labor-intensive to create. In this work, we propose a method that fuses geo-knowledge of location descriptions and a Generative Pre-trained Transformer (GPT) model, such as ChatGPT and GPT-4. The result is a geo-knowledge-guided GPT model that can accurately extract location descriptions from disaster-related social media messages. Also, only 22 training examples encoding geo-knowledge are used in our method. We conduct experiments to compare this method with nine alternative approaches on a dataset of tweets from Hurricane Harvey. Our method demonstrates an over 40% improvement over typically used NER approaches. The experiment results also show that geo-knowledge is indispensable for guiding the behavior of GPT models. The extracted location descriptions can help disaster responders reach victims more quickly and may even save lives.

Service Quality in Rail Systems: Listen to the Voice of Social Media

Service quality is essential to increase and maintain user loyalty to the railway system. In the literature, surveys have been used to measure user satisfaction, and mathematical methods have been applied to quantify the survey results. In recent years, user-generated content, including comments and complaints shared via social media, has been used to measure the quality of rail services. This content may provide important insights into the quality of the service provided with its dynamic structure. In this study, a SERVQUAL-based social-media analytics approach is used to measure railway service quality, placing special emphasis on the temporal variations in a national rail system. Topic modeling was used to assign each content item to the relevant service dimension and sentiment analysis was applied to measure the level of satisfaction. Importance–performance analysis was employed at the final stage to generate policy suggestions. Gathering more than 2.3 million social-media messages posted from 2011 to 2021, we examined the temporal evolution of service quality of the Turkish rail system. The results reveal the most and least important services and the satisfaction level of each dimension. The differences between the priorities of conventional and high-speed rail passengers are defined, and policy recommendations are presented.

Consumers’ persuasion knowledge of algorithms in social media advertising: identifying consumer groups based on awareness, appropriateness, and coping ability

Advertising and brand communication in social media are increasingly driven by algorithms. Theoretically rooted in the Persuasion Knowledge Model, we aim to identify and investigate the prevalence of specific consumer groups that differ in their awareness levels, critical evaluations, and abilities to cope with such algorithmic persuasion in social media, as well as to investigate the predictors of these groups. By performing an online survey among a Dutch sample (n = 450) and a two-step cluster analysis, we identified four groups: the Control Paradox (the largest group), Fatigued, Uninformed but Critical, and Skilled and Critical. The four groups differed in respect to gender, age, education level, internet skills, self-reported knowledge of algorithms, privacy concerns, and perceived personalization of branded social media messages. Theoretically, this paper contributes to our understanding of algorithmic persuasion by proposing a consumer typology and discussing implications for the Persuasion Knowledge Model. Practically, this study provides evidence-based recommendations for policymakers on how to empower different types of consumers.

Echo Chambers or Doom Scrolling? Homophily, Intensity, and Exposure to Elite Social Media Messages

While existing research shows why politicians’ social media messages spread online, we know comparatively less about the types of individuals who see these messages. The current study tests whether Americans’ exposure to posts from political elites is best explained by their partisan allegiance (homophily) or the intensity of their political engagement. To test this question, we employ data from a 2020 Cooperative Election Study module that asks respondents how often they encounter social media posts from various political figures. We find that both homophily and intensity characterize exposure to elite messages: partisans and ideologues not only tend to encounter posts from politicians on their own side of the aisle most often, but they also encounter posts from politicians on the opposite side more often than do independent or moderate respondents. The role of intensity relative to homophily is greatest for posts by former President Donald Trump, which Democrats were more likely to encounter than Republicans or independents.

Impact of perceived influence on confirmation bias in social media messages: the moderating effect of civic online reasoning

ABSTRACT Social media provides individuals with tremendous opportunities to follow nearly unlimited influencers online, prompting scholars’ concern about confirmation bias and the need to address it. Based on data from 894 participants, this study explores the positive effect of perceived influence on confirmation bias in social media contexts and the negative moderating effect of civic online reasoning on this relationship. These findings indicate that efforts in public media literacy education for citizens must be enhanced to transform subconscious defense mechanisms into mature coping skills through critical thinking.

A Correlational Study on Mobile Phone Addiction among University Students: Prevalence, Student Characteristics, Mobile Phone Use Purposes, and Situations

<p style="text-align: justify;">Due to the notably increased penetration of smartphone use among university students and the alarming risk it poses to both physical and mental health, this study investigated mobile phone addiction among university students concerning student characteristics, mobile phone usage behaviors, and mobile phone use purposes and situations. The participants of this study were 600 university students, who were selected according to the convenience sampling method from different departments in Türkiye. The data were collected using the student characteristics form and the Mobile Phone Addiction Scale. The correlational research method was followed in the study. The data were analyzed using descriptive and inferential statistics. The results showed that students clustered as addicted and non-addicted had different mobile phone use behaviors on account of daily smartphone use duration, internet use duration on a smartphone, and daily smartphone check frequency. Being a female at a lower grade level and using mobile phones mostly at night made students more vulnerable to mobile phone addiction. Additionally, the results indicated a significant positive moderate correlation between internet use duration, daily smartphone use duration, daily smartphone check frequency, and mobile phone addiction scores. Lastly, checking social media apps, messaging, and editing photos significantly contributed to mobile phone addiction scores. Among the mobile phone use situations, when getting bored, during lessons, when watching TV or movies, and when being alone significantly contributed to mobile phone addiction scores. This study provided a thorough discussion and a set of recommendations. </p>

Fitspiration-effect: Fitness identity of emerging adult females on social media

Social media platforms such as the fitspiration online movement aimed at inspiring health and fitness play an important role in how women internalise health and fitness ideals in their sense of self. This qualitative study recruited 14 emerging adult females using purposive sampling. Data collection focussed on gaining insight into participants’ fitness identity and autophotography and photo elicitation were used. Thematic analysis was used to construct meaning from the data. Participants considered fitness beneficial to their physical and mental health and an important aspect of their recreation, socialisation and identity. The findings emphasised how emerging adult females balance social media discourses found in the fitspiration movement. Their journeys to establish a healthy and stable fitness identity included the value of fitness, inspiration, and upward social comparison, and the dangers of judgement and overemphasis on an ideal body and exercise regime. The process of fitness identity development is complex and especially challenging for emerging adult females who are trying to construct a sense of self while moving through a transitional developmental stage and contending with cultural discourses and social media messages that often prioritise weight loss and physical appearance over health.

Examining attitudes towards inclusion and social justice among U.S. Climbers: analysis and findings from a national survey

ABSTRACT Climbing in the U.S. resembles other ‘alternative’ and ‘lifestyle’ sports in that it has long been an exclusionary leisure pursuit. Whiteness, a history of land dispossession, and settler colonialism have reinforced exclusive boundaries to the sport through a ‘hierarchy of participation’. Formal moves from climbing advocacy organisations, gyms, and brands have increased diversity and justice efforts in climbing through funding, pledges, and social media messaging. However, these initiatives receive varied support from within climbing communities. This paper employs a social-psychological approach to examine which factors likely help shape and maintain variation in U.S. climbers’ concern for matters related to inclusion and justice in climbing. We draw data from a national survey conducted in collaboration with the national advocacy organisation Access Fund. We then apply multiple regression to examine how various climbing and demographic attributes are associated with inclusion and justice concerns by testing three hypotheses: experienced privilege and/or marginalisation, partisan political affiliation, and issue prominence. Our findings suggest that variation in climbers’ inclusion and justice attitudes appears driven more by respondents’ affiliation with one or more marginalised identities, political leanings, and other sociodemographic characteristics that we suggest are representative of the ‘politics of everyday life’.

A Multilayered Preprocessing Approach for Recognition and Classification of Malicious Social Network Messages

The primary methods of communication in the modern world are social networks, which are rife with harmful messages that can injure both psychologically and financially. Most websites do not offer services that automatically delete or send malicious communications back to the sender for correction, or notify the sender of inaccuracies in the content of the messages. The deployment of such systems could make use of techniques for identifying and categorizing harmful messages. This paper suggests a novel multilayered preprocessing approach for the recognition and classification of malicious social network messages to limit negative impact, resulting in fewer toxic messages, scams, and aggressive comments in social media messages and commenting areas. As a result, less technical knowledge would be required to investigate the effects of harmful messages. The dataset was created using the regional Lithuanian language with four classes: aggressive, insulting, toxic, and malicious. Three machine learning algorithms were examined, five use cases of a multilayered preprocessing approach were suggested, and experiments were conducted to identify and classify harmful messages in the Lithuanian language.

Sport Celebrities’ COVID-19 Prevention on Social Media: The Effect of Credibility, Social Distance, Identification, and Message’s Power Style on Health Behavioral Intentions

During the COVID-19 outbreak, there emerged on social media an active cohort of sport celebrities, promoting through their messages virus-prevention behaviors. The study tested how people’s intentions to adopt COVID-19 prevention practices were affected by their perceived credibility of sport celebrities, perceived social distance of sport celebrities, and identification with sport celebrities. The study also tested how the message’s power style moderated those relations. The researchers selected four sport celebrities who were active on social media and applied powerful and powerless linguistic styles in developing their social media messages. College students ( N = 284) were randomly exposed to one of eight stimuli and asked the questions in the self-administered online survey. The perceived credibility positively affected COVID-19 prevention intentions regardless of the message’s power style. The perceived social distance was effective for intentions only in the powerless message. Identification with sport celebrities was effective regardless of the message’s power style, with the powerless message being more effective than the powerful one. The study provides a theoretical perspective on how people utilize sport celebrities’ characteristics as peripheral cues during health information processing. Also, the study offers practical implications for leveraging social media and sports celebrities to promote virus prevention.

Novel Application of Open-Source Cyber Intelligence

The prevalence of cybercrime has emerged as a critical issue in contemporary society because of its far-reaching financial, social, and psychological implications. The negative effects of cyber-attacks extend beyond financial losses and disrupt people’s lives on social and psychological levels. Conventional practice involves cyber experts sourcing data from various outlets and applying personal discernment and rational inference to manually formulate cyber intelligence specific to a country. This traditional approach introduces personal bias towards the country-level cyber reports. However, this paper reports a novel approach where country-level cyber intelligence is automatically generated with artificial intelligence (AI), employing cyber-related social media posts and open-source cyber-attack statistics. Our innovative cyber threat intelligence solution examined 37,386 tweets from 30,706 users in 54 languages using sentiment analysis, translation, term frequency–inverse document frequency (TF-IDF), latent Dirichlet allocation (LDA), N-gram, and Porter stemming. Moreover, the presented study utilized 238,220 open-intelligence cyber-attack statistics from eight different web links, to create a historical cyber-attack dataset. Subsequently, AI-based algorithms, like convolutional neural network (CNN), and exponential smoothing were used for AI-driven insights. With the confluence of the voluminous Twitter-derived data and the array of open-intelligence cyber-attack statistics, orchestrated by the AI-driven algorithms, the presented approach generated seven-dimensional cyber intelligence for Australia and China in complete automation. Finally, the topic analysis on the cyber-related social media messages revealed seven main themes for both Australia and China. This methodology possesses the inherent capability to effortlessly engender cyber intelligence for any country, employing an autonomous modality within the realm of pervasive computational platforms.

Proactive Policing as a Strategy to Prevent Youth Brawls

Cases of brawls between groups of teenagers are not a new phenomenon in the midst of social life. Actions of brawls carried out by groups of delinquent youth continued to flourish and also resulted in injuries and even fatalities. Technological developments also affect the method of carrying out brawls. Groups of teenagers use social media accounts to challenge each other to take brawls at locations that are also determined through social media messages. The timing of brawls is also not only carried out during the day but also at night and early in the morning as in several examples of brawl cases that occurred in 2023. This can disrupt security and public order in the community. Prevention strategies using the Proactive Policing method need to be carried out to prevent brawls from occurring. The Proactive Policing strategy in this case is carried out by forming a joint patrol team to carry out systematic patrol activities in the community and also cyber patrols to monitor social media accounts that have indications of provoking brawls.

Using health belief model and social media analytics to develop insights from hospital-generated twitter messaging and community responses on the COVID-19 pandemic

PurposeThis study aims to examine how different hospitals utilize social media to communicate risk information about COVID-19 with the communities they serve, and how hospitals' social media messaging (firm-generated content and their local community's responses (user-generated content) evolved with the COVID-19 outbreak progression.Design/methodology/approachThis research proposes a healthcare-specific social media analytics framework and studied 68,136 tweets posted from November 2019 to November 2020 from a geographically diverse set of ten leading hospitals' social media messaging on COVID-19 and the public responses by using social media analytics techniques and the health belief model (HBM).FindingsThe study found correlations between some of the HBM variables and COVID-19 outbreak progression. The findings provide actionable insight for hospitals regarding risk communication, decision making, pandemic awareness and education campaigns and social media messaging strategy during a pandemic and help the public to be more prepared for information seeking in the case of future pandemics.Practical implicationsFor hospitals, the results provide valuable insights for risk communication practitioners and inform the way hospitals or health agencies manage crisis communication during the pandemic For patients and local community members, they are recommended to check out local hospital's social media sites for updates and advice.Originality/valueThe study demonstrates the role of social media analytics and health behavior models, such as the HBM, in identifying important and useful data and knowledge for public health risk communication, emergency responses and planning during a pandemic.

Role of Self-Regulatory in Luxury Brands’ Social Media Advertising

Luxury brands are increasingly using social media messages as their ads to consumers. This paper investigates the impact of regulatory focus on brand attitudes after research participants viewed a luxury brand’s message on social media. The research question is whether promotion-focused consumers and prevention-focused consumers have different responses to messages that emphasize either innovation or tradition. Based on an online experiment, this research findings show that the framing of the message interacts with regulatory focus. An ad that emphasizes innovation yields more favorable brand attitudes than an ad that emphasizes tradition among promotion-focused consumers. However, this does not happen among prevention-focused consumers. This research provides theoretical implications and practical suggestions for industry practitioners.

Strength in diversity: How incongruent racial cues enhance consumer preferences toward conservative brands

A growing number of brands utilize political stances and ideological beliefs to communicate their image to customers. In examining how a brand’s ideological stance might impact consumer preferences, the current research examines how a persuasive appeal can be more effective when it provides cues which are incongruent with a brand’s perceived political ideology. Five studies show that conservative brands can enhance consumer attitudes, purchase intentions, and brand choice by using dark brown (versus pale white or yellow) skin-toned messaging cues such as emojis in their social media messages. These racial cues, which are incongruent with the in-group preferences associated with conservativism, increase a consumer’s willingness to advocate for the brand. Furthermore, this effect is mitigated if the social media message includes excessive cues or if the message is a paid promotion. Practical implications for marketing and social media strategies are provided.

A remote brief intervention plus social media messaging for cannabis use among emerging adults: A pilot randomized controlled trial in emergency department patients

IntroductionInterventions addressing cannabis use among emerging adults (ages 18–25) are currently needed to prevent negative outcomes. Emergency Department (ED) visits provide an opportunity to initiate interventions. In this pilot study, we created a brief intervention (BI), extended with private social media messaging for emerging adult ED patients who use cannabis regularly. Study aims were to examine intervention feasibility, acceptability, and descriptive outcomes. MethodsWe recruited and randomized N = 58 emerging adults (M age 21.5 years, 65.5% female) who used cannabis from an ED in-person and remotely after their ED visit (given COVID-19 restrictions). Participants randomized to the intervention (N = 30) received a Motivational Interviewing-based BI and 4 weeks of health coaching via private social media; control participants received a resource brochure and entertaining social media messaging. Follow-ups occurred at 1-month and 3-months. ResultsMost intervention participants liked the BI (95.8%), found it helpful to discuss cannabis use in the BI (91.7%), and liked interacting with coaches on social media (86.3%). Social media content (e.g., video clips, images/still pictures/memes) were highly rated. Descriptively, the intervention group showed theory-consistent changes in importance of and intentions to change cannabis (increases vs. decrease/stability in control group), whereas findings for cannabis consumption/consequences were mixed. ConclusionsThis BI paired with social media messaging was acceptable in a sample of emerging adults from an ED who used cannabis regularly. Despite feasibility challenges due to COVID-19, this intervention warrants future investigation with a larger sample and longer follow-up period, with attention to the changing cannabis landscape when measuring outcomes.

Language cases against UU ITE in Indonesia

Since the law's enactment in 2008, language cases against the Undang-Undang Informarmasi dan Transaksi Electronic Republik of Indonesia (hereafter UU ITE), also known as the Electronic Information and Transaction of Republic of Indonesia Law, have risen year after year. One source of language cases against the law is social media messages, which are the result of their users' lack of legal and intellectual comprehension. Defamation, hate speech against specific persons or SARA (ethnicity, religion, race, intergroup), threats, decency, and obscenity are all prevalent components of the unpleasant content of legal-related social media text messages. The issues addressed in this study are (1) the category of language offence and (2) the microlinguistic and macrolinguistic analysis of the text type of offence. The objective, which is supported by a qualitative descriptive method within the Forensic Linguistics approach, is to identify a system of violations that could be justified based on linguistic facts. The findings demonstrate that texts with the potential to become legal cases can be proven by microlinguistic facts like word choices and grammatical structure, while macrolinguistic facts can support the microlinguistic elements like disregard for language ethics, lack of social media literacy, and lack of editing steps before text publication.

Examining approaches to encourage COVID‐19 vaccination on social media

AbstractFollowing the release of the first COVID‐19 vaccinations many people utilized social media to promote vaccination among their social circles. These attempts to persuade others to get vaccinated ranged from positive encouragement (e.g., emphasizing the prosocial benefits and positive outcomes) to shame and threats (e.g., name calling and threating to end friendships over vaccination status). The present study investigated how these different social media messages affected COVID‐19 vaccination intentions. In June 2021, shortly after vaccines had been made freely available to anyone over the age of 16 in the United States, unvaccinated participants read a manipulated Twitter message designed to be either encouraging or shaming. Message‐type did not significantly affect intentions to become vaccinated against COVID‐19; however, participants who saw the encouraging message reported that the post made them feel more likely to get vaccinated. Self‐efficacy was also manipulated but did not reveal any significant effects. Additional analyses suggest that having personal experience with COVID‐19 moderates reactions to these different messages. We discuss limitations and promising avenues for future research on the effects of social media messages on health behaviors.

The relevance of Catholic Social Teaching for building a better world - conflict with values promoted on social media

ObjectivesThe subject of this article is a kind of values conflict which arises between traditional principles and values, which are proposed, among others, by Catholic Social Teaching, and those often promoted by various influencers in social media. The aim is to demonstrate that the traditional values of Catholic Social Teaching are still relevant and important for building a better world within us and around us. Simultaneously, the goal is to show that these values are often contradicted to the the values promoted by social media.Material and methodsThe method of analyzing the sources of Catholic Social Teaching (bible, church's teaching, literature) and analyzing the content conveyed through social media messages (content in such social media as: Facebook, YouTube, Tik Tok) is used in this article.ResultsThe result of this analysis shows the big conflict between traditional values given by Catholic Social Teaching with those promoted in social media by different influencers. In addition, the results shows the very negative impact of those values often given in social media.ConclusionsThe article concludes that in order to build a better world, it is necessary for the values proposed by Catholic Social Teaching to become the foundation of the value system embraced by members of society.

A Test of Autonomy Restoration Postscripts to Mitigate Psychological Reactance to an Opt-Out Organ Donor Registry in the United States

ABSTRACT The organ shortage continues to present problems around the world including the United States. In response, some countries have switched from an opt-in organ donor registry to an opt-out registry. The United States currently utilizes an opt-in registry where an individual is not considered an organ donor until they register their intentions. In the current study, U.S. adults were randomly assigned to a 2 (message valence: promotional, refutational) x 2 (autonomy restoration postscript: present, not present) x 2 (social proof: high likes, low likes) posttest only control group design evaluating social media message regarding an opt-out organ donor registry for implementation in the U.S. Results revealed an interaction between message valence and autonomy on freedom threat perceptions toward the message. Consistent with psychological reactance theory, freedom threat perceptions were positively associated with reactance, which in turn was positively associated with an intention to sign a petition and call a representative to voice disapproval of the opt-out organ donor registry. The discussion is focused on pragmatic recommendations for organ donor practitioners and advocates as well as the theoretical contributions to reactance theory.