Social Media Activity Research Articles

Information quality and students’ academic performance: the mediating roles of perceived usefulness, entertainment and social media usage

PurposeThis study evaluates the mediating roles of entertainment, perceived usefulness, and social media use on social information (content) and students’ academic performance.MethodologyPrimary data was collected from 445 students at King Khalid University in Saudi Arabia using the snowball sampling strategy was employed. For data analysis, structural equation modeling (PLS-SEM) was used.FindingsEntertainment partly mediates the link between social information quality “content” (IQ) and social media use (SMU) and SMU mediates the link between IQ and student’s academic performance (SAP). Perceived usefulness mediates the link between IQ and SAP. Suggesting that entertainment and perceived usefulness are crucially necessary for inspiring social media content to obtain optimum performance among graduate students. The study was limited to a single academic institution. Therefore, the results of the investigation cannot be generalized as a whole, and cannot track respondents’ social media activity over time. Thus, longitudinal data may be used in future investigations. Practical implicationsThe results of this study indicate that faculties can adapt and adjust their teaching methods and activities to incorporate social media, perceived usefulness, and entertaining content since it affects student performance. Social media (SM) has a significant influence on students’ social and academic performance. Thus, educational stakeholders, such as university authorities, the government, and parents and guardians, should recognize social media as a tool for achieving educational objectives.Originality/valueThe study enhances the application of UTAUT2 by examining how factors that influence the adoption of technology are connected to the subsequent influence of that adoption on students’ learning and conduct.

“I Was in a Position to Enact Change:” College Athletes’ Use of Social Media for Racial and Social Justice

Recent shifts in societal activism have prompted an exploration of athlete activism, particularly within higher education, where social media has become a pivotal platform for social impact. This paper investigates Division I college athletes’ engagement in athlete activism through the lens of self-authorship and self-presentation on social media for racial and social justice. Existing research underscores the significance of social media in athlete activism, focusing on access barriers, advocacy efforts, and resistance against inequalities. Through an exploratory study, we investigate how college athletes’ processes of self-authorship and selfpresentation relate to social media activism. Our findings reveal three overarching themes: social media as an activist tool, empowerment, and a starting point for advocacy. The findings suggest avenues for college sports administrators to facilitate dialogue, comprehend the strategic utilization of social media in athlete activism, and acknowledge college athletes’ aspiration for increased involvement in effecting meaningful change within their communities. These insights contribute to a deeper understanding of college athletes’ contributions to social discourse and racial and social justice initiatives.

Development of an integrated model for SME marketing and CRM optimization

The development of an integrated model for optimizing marketing and customer relationship management (CRM) in small and medium-sized enterprises (SMEs) presents a crucial advancement in enhancing business competitiveness and customer engagement. This paper proposes a unified model that merges scalable software solutions for social media analytics with AI-driven CRM to provide a comprehensive framework for SMEs to enhance their marketing strategies and customer interactions. Social media platforms have become vital channels for customer outreach, engagement, and feedback, yet SMEs often face challenges in leveraging these platforms due to limited resources and expertise. Integrating social media analytics into CRM systems offers businesses the ability to analyze customer behaviors, preferences, and sentiment on a large scale. The proposed model utilizes artificial intelligence (AI) to streamline customer interactions, enabling personalized communication and improving customer retention. By incorporating AI into CRM, SMEs can automate routine tasks, such as responding to customer inquiries and segmenting audiences based on their social media activity. This allows for more efficient marketing strategies and enables businesses to proactively address customer needs, ultimately driving customer loyalty and long-term growth. Furthermore, the unified model focuses on scalability, ensuring that SMEs can adopt and adapt these technologies according to their evolving needs and resources. This paper also explores the benefits of integrating these technologies, including the potential for improved data-driven decision-making, enhanced customer experience, and increased operational efficiency. In conclusion, this integrated model presents a strategic pathway for SMEs to optimize their marketing and CRM efforts through the adoption of scalable, AI-driven tools that enhance customer engagement and boost business performance. Keywords: SME Marketing, CRM Optimization, Social Media Analytics, AI-Driven CRM, Customer Engagement, Scalable Software Solutions, Business Performance, Personalized Communication, Customer Retention, Data-Driven Decision-Making.

Tweeting to be a constitution-writer in Chile: Social media activity, public discourse, and electoral outcomes during pandemic times

We examine the impact of social media activity and content on the electoral performance of 1,373 candidates who ran in the 2021 Constitutional election in Chile. In line with the two-step flow of communication hypothesis, estimates from binary and fractional response probit models reveal that candidates with an active Twitter/X account and higher user engagement metrics (i.e., retweets and likes per tweet) are more likely to be elected and secure a larger share of votes. Regarding the content disseminated on social media, the effect of emphasized subjects on electoral outcomes is topic-dependent. Specifically, candidates who focus their posts on sociopolitical issues improve their electoral performance, while tweeting about economics tends to reduce the likelihood of being elected as a constitution-writer in Chile. This could be attributed to the 2021 Constitutional election being part of an institutional response to a series of events, including widespread protests across the country and a strong public demand for profound changes to the Chilean status quo.

PECULIARITIES OF MARKETING AND BRANDING IN THE CONFECTIONERY AND CAFE INDUSTRY

The purpose of this article is to determine the essence and theoretical features of marketing and branding in the confectionery and cafe industry, as well as the challenges associated with marketing activities in these establishments. The main research methods used in the article include induction, synthesis, analysis, comparison, and generalization. The specific features of marketing activities in confectioneries and cafes have been identified. The impact of marketing efforts on service delivery in these establishments has been studied. Key problems arising from marketing activities and brand promotion in confectioneries and cafes have been identified. Various tools used in marketing efforts within this industry, which constitute the marketing mix or marketing complex, have been explored. The peculiarities of developing a marketing plan for confectioneries and cafes using the “5R+1C” integrated marketing model, and elements of the marketing mix specific to the food industry, are discussed. The ecosystem of the internet marketing strategy for confectioneries and cafes is outlined. The necessity for increasing social media activity (SMM) and enhancing market recognition, as well as developing a user-friendly website with online table reservations and sweet order functionalities, has been emphasized. Directions for optimizing the digital strategy effectiveness for confectioneries and cafes, focused on improving brand recognition among target audiences, are proposed. Factors influencing the selection of Google’s contextual media network for the promotion of confectioneries and cafes are outlined. The required changes for social media pages and websites to enhance brand promotion are discussed. International experiences regarding the efficacy of business tools in the food industry, incorporating marketing concepts, are also explored. The main idea of advertising campaigns, centered around creating favorable conditions for customer purchases and replicating the brand’s style in every part of the establishment, is reviewed. The specifics of consumer loyalty, shaped by the brand’s appearance, communication, establishment design, and available offerings, are also examined.

Why partisans feel hated: Distinct static and dynamic relationships with animosity meta-perceptions.

Partisans hold inaccurate perceptions of the other side. What drives these inaccuracies? We address this question with a focus on partisan animosity meta-perceptions (i.e. how much a partisan believes opposing partisans hate them). We argue that predictors can relate to meta-perceptions statically (e.g. at a specific point in time, do partisans who post more about politics on social media differ in their meta-perceptions relative to partisans who post less?) or dynamically (e.g. does a partisan who increases their social media political posting between two defined time points change their meta-perceptions accordingly?). Using panel data from the 2020 US presidential election, we find variables display distinct static and dynamic relationships with meta-perceptions. Notably, between individuals, posting online exhibits no (static) relationship with meta-perceptions, while within individuals, those who increased their postings over time (dynamically) became more accurate. The results make clear that overly general statements about meta-perceptions and their predictors, including social media activity, are bound to be wrong. How meta-perceptions relate to other factors often depends on contextual circumstances at a given time.

Investigation of the influence of 45-minute pre-sleep social media use on sleep quality and memory consolidation in adolescents

Adolescents devote a significant portion of their time to smartphone usage, often engaging in social media activities. Social media use has previously been linked to diminished sleep quality and reduced sleep durations in correlational studies. In this experimental study, we aimed to investigate the influence of pre-sleep social media use on memory consolidation, subjective arousal and objectively assessed sleep quality in adolescents. We compared the social media condition to two reading conditions, one involving reading a book on a smartphone and the other reading from a physical book in a within-subjects design. Twenty participants between 12 and 14 years engaged in these activities for 45 min before bedtime. Contrary to our expectations, the results indicated that pre-sleep social media use did not have a discernible impact on sleep quality, pre-sleep arousal or memory consolidation. All assessed sleep measures remained consistent across the three conditions. Subjectively, the social media condition was rated less thrilling than the reading conditions. This suggests that, within the confines of this experiment, pre-sleep social media exposure did not significantly disrupt adolescents' sleep or their ability to consolidate memories during sleep. This deviation from previous correlational studies might be explained by a possible impact of mental health factors on media consumption and sleep or the fact that contrary to their daily routines participants had to sleep after our intervention and could not continue to engage in their activities. This highlights the need for further investigations into the complexities of this interaction.

Attention economy in professional football: A study protocol on the individual perspective of social media marketability of European football player

In the digital age, the attention economy assumes that attention flows along the same channels as money. Attention is a scarce commodity, so competing for it should follow a similar mechanism to the general acquisition of income and can therefore be seen as a social currency (Franck, 1998). Nowhere is this more evident than in the realm of professional sports, where athletes have become both performers and brands (Nufer, 2018), competing not only on the field but also in the arena of attention. For the players themselves but also for the clubs, the market value of a football player is no longer solely determined by their athletic prowess but is equally influenced by their ability to capture and maintain the attention of fans or sponsors (Leo & Kuczkowski, 2020). Seeing players as entrepreneurs, we assume that reputation is a fluid and dynamic asset (Gerbaulet, 2016), wherein the player’s ability to manage and cultivate their public image becomes paramount. Football players aim to maximize their lifetime income, which includes both their performance on the pitch and their marketability off it. Marketability can extend beyond their playing career and may follow a life-cycle concept (Vernon, 1966). Therefore, players are motivated to use social media to boost their reputation and lifetime market value. To investigate this phenomenon, we analyse data from the big five European football leagues (Bundesliga, Premier League, Ligue 1, La Liga, and Serie A) focusing on the 2022/2023 season. This season was chosen to ensure a closed information set, as the 2023/2024 season was ongoing during the initial data collection period, and player market values are typically updated multiple times throughout a season. Our study examines the correlation between social media activity and player market value by employing a regression model to quantify the influence of social media metrics, while controlling for other relevant variables. Player market values are sourced from the widely recognized platform Transfermarkt (https://www.transfermarkt.de). Social media activity is quantified through metrics such as the number of followers, the volume of posts, likes, and engagement rate, with data obtained from Fanpage Karma (https://www.fanpagekarma.com/). To account for players’ footballing abilities, we include performance data such as playing time, shots, and packing index sourced from The Analyst (https://theanalyst.com/eu). Additional control variables, including player age, position, league, and club affiliation, are also sourced from Transfermarkt and incorporated into the regression model. The dataset comprises 2,284 players, of whom 80% (1,805 players) have Instagram accounts. Instagram usage is highest among Premier League players (92%) and lowest among those in Ligue 1 (65%). The results of the regression analysis will be presented and discussed, providing insights into the relationship between social media presence and market value. This analysis will contribute to understanding the patterns of attention generation in relation to marketability and the rationality behind social media use in professional football. References Gerbaulet, D. (2016). Der Unternehmer als Reputator [The entrepreneur as reputator]. Mohr Siebeck. Franck, G. (1998). Ökonomie der Aufmerksamkeit. Ein Entwurf [The economy of attention. A draft]. Carl Hanser. Leo, M., & von Kuczkowski, A. (2020). „Kaufen Sie Ronaldo!“ Wie Facebook, Instagram & Google den Profifußball verändern [„Buy Ronaldo!“ How Facebook, Instagram & Google are changing professional football]. Die Werkstatt. Nufer, G. (2018, 30 January). Viel mehr als nur Sportler. Warum Ronaldo und Neymar mehr zu Marken im Fußball taugen als Götze [Much more than just athletes. Why Ronaldo and Neymar are more suitable as football brands than Götze]. Focus Online. https://www.focus.de/sport/experten/nufer/f-f_id_8386959.html Vernon, R. (1966). International investment and international trade in the product cycle. The Quarterly Journal of Economics, 80(2), 190–207. https://doi.org/10.2307/1880689

Organizational communication for social change on social media: NPOs’ social media strategies based on their perception of three stakeholder networks in collective and connective action

Abstract Social media transform and complicate nonprofit organizations’ (NPOs) traditional communication to engage and lead stakeholders for collective action. Stakeholders can self-organize for connective action on social media and form stakeholder networks of varied potential and structures that NPOs may leverage for collective goals. Facing such networks, NPOs may communicate in diverse ways to accommodate and take advantage of the diverse stakeholder networks. Through two surveys conducted with 375 (Study 1) and 74 (Study 2) NPOs, this study suggests that NPOs diversify their communication to leverage different potential from each stakeholder network by crafting different types of social media activities based on their perception of different networks. This study develops a comprehensive theoretical understanding of NPOs’ transformed and complex communication strategies for stakeholder engagement in driving social change, opening up new avenues for organizational communication and collective and connective action scholarship.

Pricing dynamics and herding behaviour of NFTs

AbstractThis paper analyzes the sales of 875,389 art nonfungible tokens (NFTs) on the Ethereum blockchain to identify the key determinants influencing NFT pricing and market dynamics. We find that market liquidity and trade volume are strong predictors of NFT prices. Contrarily, social media activity negatively correlates with prices. Introducing an artist ranking system, our study reveals a “superstar effect”, with a few artists dominating sales, and herding behaviour within the NFT market.

Employee Branding Thru Social Media

Developing a distinct Employer brand sets an Employer apart from its rivals and other companies competing for the same talent pool. Most businesses now utilize internet media significantly in the field of brand development. Branding is a marketing term that is applied to organizations, which are seen as goods with distinct characteristics. Jobseekers collect information from organizations’ online platforms as well as informal feedback from other stakeholders. The investigation includes not only their online presence and how they are portrayed, but also the degree of engagement of their activities in various social media platforms (e.g. Face book, YouTube, LinkedIn, Twitter). Although the research that mostly focused on The analysis includes not only their online presence and how these businesses are presented, but also the level of interactivity of their activities in various social media (e.g., Facebook, YouTube, LinkedIn, and Twitter), as well as a description of the Measurement Model Assessment, social media factor with all items displayed. Fit Indices for SMM Model (CFI)

Predicting social media users' indirect aggression through pre-trained models.

Indirect aggression has become a prevalent phenomenon that erodes the social media environment. Due to the expense and the difficulty in determining objectively what constitutes indirect aggression, the traditional self-reporting questionnaire is hard to be employed in the current cyber area. In this study, we present a model for predicting indirect aggression online based on pre-trained models. Building on Weibo users' social media activities, we constructed basic, dynamic, and content features and classified indirect aggression into three subtypes: social exclusion, malicious humour, and guilt induction. We then built the prediction model by combining it with large-scale pre-trained models. The empirical evidence shows that this prediction model (ERNIE) outperforms the pre-trained models and predicts indirect aggression online much better than the models without extra pre-trained information. This study offers a practical model to predict users' indirect aggression. Furthermore, this work contributes to a better understanding of indirect aggression behaviors and can support social media platforms' organization and management.

Analyzing COVID-19 Sentiments on Twitter: An Effective Machine Learning Approach

The COVID-19 pandemic has brought about a surge in online discussions and social media activity, making it crucial to analyze public sentiment towards the virus and related topics. This thesis focuses on Sentiment Analysis of COVID-19 data on Twitter, employing Multinomial Logistic Regression as the primary classification algorithm. This research explores Sentiment Analysis of COVID-19 data on Twitter using Multinomial Logistic Regression. It constructs a tweet dataset reflecting various sentiments—positive, negative, and neutral. The data undergoes preprocessing, and a Sentiment Analysis model is built, with 70% of data for training and 30% for testing. The model uses Count-Vectorizer, Tf-idf for feature extraction, and Multinomial Logistic Regression to classify tweets. The study achieves state-of-the-art results with a high accuracy of 95.14%, demonstrating the effectiveness of this approach. The results offer valuable insights into public sentiment during crises, aiding in decision-making and communication strategies.

Emotional Digital Labor Among Young People Within the Context of Lumpencybertariat

Türkiye ranks among the countries with the highest rates of social media usage. Especially among the young population, the prevalence of social media usage reaches the highest rates. This article focuses on the formation of hate within the cultural production processes on social media among young population. The monopolization of social media platforms fosters an economic logic where hateful interactions gain exchange value within algorithmic distribution systems. The online activities of social media users are at risk of being drawn into a “discursive spiral of hate”. Algorithms direct social media activities towards emotional escalation and transform online interactions into the “emotional digital labor”. Thus, the digital cultural production is tended to be dominated by the “lumpencybertariat”. This lumpenization process poses a direct risk to young social media users. This article aims to outline the conceptual framework of the position of lumpencybertariat as the producer of emotional digital labor in the digital capitalism. The possibility of “emotional sustainability” as a potential tool to counter the risk of lumpenization in digital cultural production is discussed.

“We’re Not Lab Rats”: Analysis of Netizens’ Response to BCG Vaccine-Test Proposal Against COVID-19 in Africa

In April 2020, two French scientists proposed Africa as the site for testing a BCG tuberculosis vaccine for treating COVID-19. This sparked social media outrage with some describing the gaffe as a hangover of colonial mentality. This study examined netizens’ interpretation of the faux pas and how the social media activism that followed it shaped the narrative about Africa’s identity. The study found that netizens interpreted the discourse as racism against Africa, colonialism, and a breach of medical ethics. These created an avenue for social media activism by a new generation of African netizens to assert their independence, protect their humanity, and promote the idea of Africa for Africans. The study recommends the need for ethics of care and racial sensitivity in public and global health discourses that have the potential to reopen scars of historical trauma in subjugated populations who may be geographically or socially affected by pandemics.

Leveraging social media data for pandemic detection and prediction

Governments and healthcare institutions are increasingly recognizing the value of leveraging social media data to address disease outbreaks. This is due to the rapid dissemination and rich content of social media data, which includes real-time reactions and calls for help from people. However, current research on which social media data can be utilized for information support, as well as the underlying reasons why social media data can be utilized for information support, remains limited. This study aims to make up for the aforementioned limitation by investigating which social media information is more likely to reflect the severity of an outbreak through empirical and prediction models, while also elucidating why social media data has the ability to reflect pandemic through content analysis. The COVID-19 outbreak was utilized as a case example in this study because it has the advantage of enhancing the universality of results and promoting the validation of the model with multiple waves of data. The empirical model results indicate that social media activity from public users is more likely to reflect the ground truth during pandemic. In particular, it was found that negative sentiment expressed in blog posts by public users during pandemic aligns more closely with the severity of disease outbreak. Then, a prediction model was proposed to further validate these findings of the empirical model. Finally, a content analysis was conducted based on the conclusions drawn from empirical model and prediction model. The content analysis revealed that the predictive capability of social media data for pandemic originates from individual self-reporting of illness. This study provides contributions and insights into which types of information can be used for pandemic monitoring and forecasting. The findings of our research have significant implications for governments and healthcare institutions in leveraging social media data for pandemic monitoring and forecasting.

Schoolfeeds: A study of principals’ governance of school social media pages and students’ data, privacy and treatment

It is common for contemporary schools to have a presence on social media for the purpose of connecting with the school community and often the wider public. Drawing on the perspectives of five Australian non-government principals, the study explored why schools engaged with social media and the approaches used to manage the school's social media activities. We found that the main perceived value was in marketing the school to prospective families, which required active curation of posts and comments to ensure a positive image was presented and maintained. We further found that principals consider social media platforms to be neutral mechanisms for communication, not dissimilar to previous forms of communication long used by schools to engage with their communities. When viewed through a data justice lens, we argue that these views result in unintended consequences by presenting an image of the school that does not represent the diversity of its students and activities and by perpetuating the exploitative practices of commercial platforms that commodify students’ data. There are also missed opportunities for schools to better promote their educational goals and activate students as agents in representing themselves online and developing their data literacy. We propose that by adopting the term ‘schoolfeeds’ we can promote a more critical engagement with school social media that can lead to better policy and practice.

Adverse weather amplifies social media activity and worsens online sentiment: Evidence from over 10 billion social media posts

Adverse weather amplifies social media activity and worsens online sentiment: Evidence from over 10 billion social media posts

Does ostracism/rejection impact self-disclosures? Examining the appeal of perceived social affordances after social threat

Abstract Two studies examine how experiencing a social need threat (ostracism and rejection) impacts subsequent preferences for self-disclosure to various digital audiences. Findings consider how contextual/situational factors like need threats may impact the appeal of two established perceived social affordances of media: personalization and privacy/visibility. Participants took part in a (bogus) social media activity to elicit feelings of inclusion/ostracization/rejection and then were asked about sharing their media preferences with various potential audiences. Results show that social need threats have no significant impact on privacy preferences but do affect preferences for sharing with some audiences and not others. Notably, ostracized and rejected participants show different patterns of preferences, suggesting these forms of social need threat may have distinct impacts on future self-disclosures. Implications for online relationship development and community building are considered in the discussion.

An Investigation into Social Media Utilisation in Small and Medium-Sized Enterprises and its Effect on Business Performance: A Case Study of Kabwata Township, Lusaka

This study investigated the impact of social media on Small and Medium-Sized Enterprises (SMEs) in Kabwata Township, focusing on the types of social media used, its impact on brand visibility, customer acquisition, and the influence of social media marketing strategies on sales revenue and profitability. A mixed methods approach was employed, integrating quantitative surveys and qualitative interviews to provide a comprehensive understanding of SMEs' social media practices. The study targeted SMEs actively using social media in Kabwata. 100% response rate was achieved from a sample of 133 SMEs for quantitative data and additional insights from 20 SMEs for qualitative data. The results indicated that platforms like Facebook, Instagram, X (formerly known as Twitter), and LinkedIn significantly enhanced brand visibility and customer engagement. However, the choice of platform alone did not predict success; strategic implementation was crucial. Significant correlations and regression coefficients demonstrated the positive impact of social media marketing on SME success, though with a modest effect on sales revenue. Recommendations emphasized aligning social media activities with business objectives to maximize benefits.