Search Results (551)

The proliferation of generative artificial intelligence (AI) as an autonomous recommendation agent fundamentally challenges traditional paradigms of marketing communication. As AI systems increasingly mediate consumer–brand relationships, understanding how artificial agents construct persuasive discourse—distinct from human communicators—becomes critical for developing effective dual-channel marketing strategies. Grounded in Source Credibility Theory and the Computers Are Social Actors (CASA) paradigm, this study investigates the semantic and structural divergence between AI-generated product recommendations and human influencer marketing messages in social commerce contexts. Employing a mixed-methods computational approach integrating term frequency analysis, TF-IDF weighting, Latent Dirichlet Allocation (LDA) topic modeling, and BERT-based contextualized semantic embedding analysis (KR-SBERT), we examined 330 Instagram influencer posts and 541 AI-generated responses concerning inner beauty enzyme products—a hybrid category combining functional health claims with hedonic beauty appeals—in the Korean social commerce market. AI-generated responses were collected through a systematically designed query protocol with empirically grounded prompts derived from actual consumer search behaviors, and analytical robustness was verified through sensitivity analyses across multiple parameter thresholds. Our findings reveal a fundamental divergence in persuasive architecture: human influencers construct experiential narratives exhibiting message characteristics typically associated with peripheral-route cues (sensory descriptions, emotional testimonials, social context), while AI recommendations employ systematic, evidence-based discourse exhibiting message characteristics typically associated with central-route argumentation (functional mechanisms, ingredient specifications, objective criteria). Topic modeling identified four distinct thematic clusters for each source type: human discourse centers on embodied experience and relational consumption, whereas AI discourse organizes around informational utility and rational decision support. Jensen–Shannon Divergence analysis (JSD = 0.213 bits) confirmed moderate distributional divergence, while chi-square testing (χ² = 847.23, p < 0.001) and Cramér’s V (0.312, indicating a medium-to-large effect) demonstrated statistically significant and substantively meaningful differences. These findings extend CASA theory by demonstrating that AI recommendation agents develop a characteristic “AI communication signature” distinguishable from human persuasion patterns. We propose an integrated Dual-Agent Persuasion Proposition—synthesizing CASA, ELM, and Source Credibility perspectives—suggesting that AI and human recommenders serve complementary functions across different stages of the consumer decision journey—a proposition whose predictions regarding sequential persuasive effectiveness and consumer processing routes await experimental validation. These findings carry implications for AI content strategy optimization, platform design, and emerging regulatory frameworks for AI-generated content labeling. Full article

Volunteered Geographic Information (VGI) is geographic data obtained from voluntary contributions of individual contributors on social media and non-social media platforms, where contributors exhibit diverse interests and behavior patterns. While studies have found that the COVID-19 pandemic has influenced VGI contributor behavior on social media platforms (Facebook, X, and Instagram, etc.), less is known about contribution behaviors on non-social media VGI platforms such as OpenStreetMap (OSM). This study investigates how individual OSM contributors’ data contribution behaviors changed after the COVID-19 outbreak, using New York City as a case study. Metrics quantifying temporal, spatial, thematic, participation, and social interaction aspects of contribution behavior were developed to characterize individual-level contribution behaviors in both the pre- and post-COVID periods (2016–2019 and 2020–2023, respectively). Contributors were clustered into three groups based on pre-COVID behavioral patterns (as reflected by the metrics) using the K-Means algorithm. The resulting model was then applied to identify changes in contributors’ cluster memberships in the post-COVID period. Results reveal differences in contribution behaviors between the two time periods. Compared to pre-COVID contributors, post-COVID contributors, on average, showed stronger contribution engagement, including longer lifespans, larger spatial extent of edits, higher contribution volumes, a greater emphasis on modification over creation, and stronger co-editing network interactions. Healthcare amenity-related edits remained a small fraction of total contributions across both periods and all clusters. Contributors participating in data contribution in both time periods generally increased data contribution engagement after the COVID outbreak, characterized by longer lifespans, broader spatial coverage, more balanced creation and modification, and stronger network centrality. These findings highlight changes in individual contribution behavior under COVID-19 and exhibits the value of examining VGI contribution at the individual level. Full article

This article sets out an assertion that a mass art project can make a virtue of ‘network extension’ through an Instagram account, to build creative community, new connections, and physical artwork outcomes. We Are Making A Film About Mark Fisher is an example of a ‘manifested artwork’, where Fisher’s ideas on capitalism and community are explored through electronic media. We have taken the work of critical theorist, Mark Fisher, and subjected it to a process of détournement, alluding to the work of Guy de Bord and The Situationists. The thing in itself—Fisher’s processed ideas—are reprocessed and held up against the posthumous period between 2017 and now, since he died. The assertion in the work is that while the tools are circumscribed by a set of ‘standards’ and ‘production processes’, this does not delimit them from being employed towards the evolution of embodied and shared actions that develop a counter-narrative or something that eschews the methods of Hollywood or broadcast television documentaries. We just have to learn ways to do this. ‘Decapitalising’ a process, working with human agency and good will, turns the platform of Instagram into a tool of empowerment—reappropriating the algorithm and capturing the collective back from the closed corporate system of control. We see that a form of value is pulled back out of the machinic effects of a proprietary platform. Full article

This study examines how followers’ social identity dimensions—cognitive, evaluative, and affective—affect their purchase intention for fashion products promoted by Instagram influencers. It also explores the mediating role of source credibility factors, including trustworthiness, expertise, and attractiveness, in strengthening this relationship. Targeting millennial females, a key fashion consumer group, the study applies social identity theory, source credibility theory, and influencer marketing literature to develop its conceptual framework. A quantitative, correlational approach was used, employing a self-administered questionnaire distributed via a convenience snowball sample of millennial females in Erbil, Kurdistan. Data from 421 respondents collected between were analyzed using SPSS AMOS version 24. Findings reveal that all social identity dimensions significantly influence purchase intention, and source credibility factors play a direct mediating role in this relationship. These insights offer practical implications for marketers and influencers, helping them understand the impact of followers’ social identity on purchasing behavior and refining influencer marketing strategies. This research expands influencer marketing literature by demonstrating the mediating effect of source credibility on the link between social identity and purchase intention. This research provides practical implications for enhancing millennial consumers’ purchase intentions by leveraging social identity mechanisms. The findings offer valuable insights for both social media influencers and brands seeking to employ influencer marketing strategies effectively in fashion promotion. Full article

Background: In 2024, Reddit, an emerging social media platform, saw a 50% increase in monthly users to nearly 100 million. Reddit has also emerged as a significant space for discussions about health conditions, including epilepsy, which affects about 50 million people globally. Purpose: This study aims to explore trends in the volume, timing, themes, emotional tone, and sentiment of posts on the r/Epilepsy subreddit from 1 December 2023 to 31 December 2024. Methods: We collected 25,222 original English-language posts from r/Epilepsy using Reddit’s Application Programming Interface (API). Data extraction was restricted to English-language submissions to ensure compatibility with sentiment and thematic analyses. We analyzed post volume and timing using chi-square tests and Poisson regression. Emotional tone was measured using TextBlob (version 0.19.0), while compound sentiment scores were calculated via VADER (Valence Aware Dictionary and Sentiment Reasoner) (NLTK version 3.9.1). A Pearson correlation assessed agreement between sentiment and emotional tone, with statistical significance set at p < 0.05. Thematic analysis was conducted using a KMeans clustering algorithm (scikit-learn version 1.6.1) to identify recurring discussion topics. Results: Total monthly posts steadily increased, with the highest number (2175) in December 2024. Peak posts in descending order were in December 2024, August 2024, and November 2024. Posts were not evenly distributed across the week, with a significant peak on Mondays (χ² = 86.75, p < 0.001) and Poisson regression confirming higher activity early in the week (p = 0.001). Emotional tones fluctuated, with positive sentiments in January and October 2024, and negative sentiments in March and August 2024. KMeans clustering identified five main themes: treatment experiences, community engagement, personal experiences, solidarity, and subreddit gratitude. Manual validation of a random subset of posts demonstrated moderate concordance between automated sentiment classification and human ratings. Conclusions: This study highlights temporal patterns, sentiment dynamics, and thematic structure in online discussions on epilepsy. Social media may offer valuable, real-time insights into patient-centered concerns and community engagement, which can inform healthcare professionals and advocacy groups in supporting individuals affected by epilepsy. Future studies may compare trends of epilepsy discussions across various social media platforms, such as X and Instagram, to further understand online patient experiences. Full article

Social media platforms have become central arenas for political communication, electoral mobilization, and institutional contestation. This study examines how TikTok, Facebook, and Instagram were used during and after the 2025 Romanian presidential elections to circulate populist, sovereignist, and anti-institutional narratives. Drawing on a mixed-method content analysis of 764 public posts and over 2000 associated comments collected between 1 April and 30 June 2025, the study identifies dominant themes, discursive frames, and forms of user participation across platforms. The findings reveal marked platform-specific differences. TikTok emerges as the primary space for emotionally charged, visually oriented political communication and post-electoral contestation, while Facebook facilitates more argumentative and institution-focused discourse. Instagram plays a marginal role in political communication within the analyzed context. The results further indicate that content challenging the legitimacy of electoral institutions persists beyond the electoral moment and is amplified through coordinated dissemination patterns and interactive forms of participation, including AI-modified visual materials. By integrating thematic, discursive, and participatory analysis in a comparative platform framework, this study contributes to the literature on digital political communication and online populism. It highlights the role of social media platforms as amplifiers of symbolic conflict in democracies undergoing processes of institutional consolidation. Full article

As the first domesticated species, dogs have been shaped by human needs, values, and social structures, resulting in culturally specific expectations of their behaviour. While much of the existing research on companion animal preferences (referred to as ideal traits) has focused on Western contexts, rapidly increasing companion dog populations in Eastern countries mean that preferences in diverse cultures are important to investigate. Considering owner satisfaction is influenced by the match between dogs’ traits and owners’ culturally specific ideals, understanding ideal dog traits may help minimise welfare concerns, including relinquishment and maltreatment of companion dogs. A sample of 312 Vietnamese adults (M age = 27.31, SD = 6.65) were recruited via convenience sampling through Facebook and Instagram. Participants completed translated versions of the 44-item Ideal Dog Scale. Exploratory factor analysis identified four dimensions of ideal dog traits in Vietnam: ‘Calmness’, ‘Energy/Capability’, ‘Affection/Health’, and ‘Cleanliness’. This differs from Australia, where the ideal dog is ‘calm/compliant’, ‘sociable/healthy’, ‘energetic/faithful/protective’, ‘socially acceptable’, and ‘non-aggressive’, and from Italy, where the ideal dog is ‘calm’, ‘sociable and healthy’, ‘well trained and adaptable’, ‘energetic’, and ‘easy to manage‘. For participants with a current dog, most owned a non-desexed, mixed breed male dog. This study deepens psychological insight into how socioecological contexts may shape perceptions of ideal companion animals. It also allows Vietnamese individuals to understand traits that would lead to the best dog–owner ‘match’, improving dog owner wellbeing and dog welfare. Full article

This paper presents a scalable machine learning pipeline for extracting actionable, product-related insights from user-generated social media comments. Leveraging sentence embeddings from SBERT and unsupervised clustering (k-Means and agglomerative), the approach structures informal and noisy comments from Instagram and YouTube into topic groups intended to support thematic analysis. A case study on feedback regarding BMW vehicles, comprising more than 26,000 comments, illustrates how the pipeline can reveal recurring user concerns, such as design critiques, usability issues, and technology-related expectations, even in short and unstructured social media comments. The proposed pipeline operates without labeled data or manual annotation, enabling scalable application and transferability across product categories and industries. By transforming large-scale, unstructured consumer feedback into interpretable themes, the pipeline provides product teams with an efficient and structured basis for data-driven product development and improvement. Full article

The use of social networks has been shown as a powerful tool for driving populations opinions towards specific trends and interests. Yet what actually makes the success of a profile? Are emotions responsible for driving the public opinion and the opinion of the followers? We present a study on the influence of emotions in their success. To do so, we first created a novel dataset called InfluEmo, crawled from Instagram, in which we designed and analyzed the impact of emotions in influencers’ success. The dataset InfluEmo is novel and freely available. Automatic emotion extraction yielded promising results, supporting our hypothesis that specific emotional profiles in influencers’ posted content are associated with measurable indicators of success measured as number of followers. These findings suggest that emotions might play a systematic and quantifiable role in shaping public opinion and influencing users’ interactions on Instagram. Using the novel InfluEmo dataset (≈38,000 posts, ≈970 profiles, 4 domains: fashion, climate, AI, and journalism), the paper shows, in fact, that more positive emotional language is consistently associated with higher engagement, with fashion influencers achieving the highest average likes (≈138,885/post) and lowest emotional entropy, while AI, climate, and journalism content—characterized by more neutral or mixed emotions—exhibits lower likes (≈6761–19,544/post), weaker sentiment–likes correlations, and higher entropy, indicating that positivity and emotional predictability outperform informational complexity in driving Instagram success. Full article

The alcohol industry uses social media platforms to normalise alcohol consumption in aquatic locations, which can lead to injury and drowning. This research investigated alcohol content posted on Instagram to determine marketing strategies and the extent to which aquatic locations and activities were featured. The Australian Instagram accounts of five alcohol brands were identified across beer, spirits, and cider. The 20 most recent posts were captured for analysis. Each image and caption were saved and coded to examine (1) ‘What marketing characteristics are used by alcohol brands on Instagram?’; and (2) ‘Which aquatic locations and activities featured in the posted Instagram content?’. Ninety-nine posts comprising 176 individual images were identified and analysed. Alcoholic beverages were shown in 53.4% of images. Aquatic locations were observed in 21.6% and aquatic activities in 17.0%. The use of aquatic locations and activities varied significantly by brand (p < 0.001). Advertising themes included associating alcohol with hobbies (29.6%) and mateship (22.7%). Only 21.6% of images contained an age restriction or warning; all accounts employed some form of age-gating. Social media platforms provide alcohol industry actors the opportunity to increase their exposure to young people. Brands used imagery that associated alcohol with fun and mateship and promoted the use of alcohol in aquatic locations. Full article

This study examines the influence of stakeholder engagement with corporate social responsibility (CSR) disclosures on social media and corporate financial performance, grounded in legitimacy theory and stakeholder theory. Using a panel dataset of 388 firm-year observations of Indonesian listed companies over the period 2019–2022, we investigate how stakeholder interactions across four social media platforms—Facebook, Twitter, Instagram, and YouTube—relate to firm performance measured by Return on Assets (ROA) and Return on Equity (ROE). Panel data regression results reveal that stakeholder engagement on visual-based platforms plays a significant role in enhancing financial performance. In particular, Instagram likes and YouTube likes are positively associated with ROA (β = 0.0004, p < 0.05; β = 0.0002, p < 0.05), while Instagram comments, YouTube likes, and YouTube views show a significant positive relationship with ROE (β = 0.011, p < 0.01; β = 0.0006, p < 0.01; β = 0.000249, p < 0.01). In contrast, engagement metrics on Facebook and Twitter do not exhibit a statistically significant association with firm performance. These findings suggest that stakeholder engagement with CSR disclosures through high-engagement, visual-oriented social media platforms can strengthen corporate legitimacy and stakeholder relationships, ultimately contributing to improved financial outcomes. The study highlights the strategic importance of platform-specific digital communication in enhancing firm performance. Full article

The COVID-19 pandemic has fundamentally transformed residential spaces, yet traditional survey-based approaches face limitations in objectively capturing these changes. This study investigates residential design trends in the Post-pandemic era, defined as the period in which pandemic-induced lifestyle changes have become institutionalized in everyday living environments. Residential interior images were collected from Pinterest and Instagram and analyzed using an image-based deep learning approach combined with expert evaluation. A pretrained convolutional neural network (ResNet50) was employed as a visual feature extractor to quantify three spatial attributes—openness and comfort, flexibility and diversity, and nature-friendliness—across four residential space types: balconies, living rooms, entrances, and bedrooms. The model-generated proportional scores were validated by experts and compared between pre-pandemic and post-pandemic periods. The results reveal dual transformation patterns of functional specialization and increased multifunctionality. Balconies evolved into well-being-oriented spaces with enhanced nature-related features, while living rooms emerged as multifunctional hubs with a substantial increase in spatial flexibility. In contrast, entrances exhibited reduced openness, functioning as hygienic buffer zones. These findings indicate a reconfiguration of spatial hierarchy in post-pandemic housing, where auxiliary spaces gain prominence and traditional primary spaces adopt flexible roles. This study demonstrates the value of image-based deep learning for objectively identifying residential design trends and provides practical implications for resilient housing design in the post-pandemic era. Full article

Young adults often underuse ultraviolet radiation (UVR) protective strategies and engage in indoor tanning, heightening lifetime skin cancer risk. The national Skin Smart Campus (SSC) initiative encourages universities to adopt policies that reduce UVR exposure. We evaluated a 6-month SSC university campaign using an independent-samples pre-post design with surveys before (N = 230) and after (N = 267) implementation. The campaign included SSC designation, an educational webpage, targeted Instagram content, small media, and sunscreen dispensers. Following campaign launch, knowledge increased over time (t = 5.02, df = 493, p < 0.001), as did dispenser use (21.9% to 57.7%; χ² = 64.4, p < 0.001). The sun safety behavior composite showed an upward trend (13.5 to 14.2, t = 1.71, df = 490, p = 0.09). Variance models indicated a significant time effect (F [1, 482] = 4.55, p = 0.03, η²p = 0.01; small effect), with higher sun safety associated with greater knowledge (F = 8.29, p = 0.004, η²p = 0.02; small effect) and SSC campaign awareness (F = 56.88, p < 0.001, η²p = 0.10; large effect). In multivariable regression, campaign engagement predicted higher odds of dispenser use (Odds Ratio = 3.01, 95% CI: 1.82–4.98, p < 0.001). Implementing SSC with environmental supports and tailored education increased knowledge, sun safety, and dispenser use, highlighting the strong influence of SSC visibility and multimodal campus-wide prevention strategies. Full article

This study investigates how Portuguese teenagers (aged 13–18) perceive and prefer the communication characteristics of so-called “newsfluencers” on social media platforms such as Instagram, TikTok, and YouTube. Through 20 semi-structured interviews, the research explores how verbal and non-verbal traits shape adolescents’ engagement with news in a media ecosystem increasingly dominated by digital intermediaries. Drawing on literature on brand journalism, the study categorizes preferences into four key elements: character, tone, language, and purpose. The findings reveal that teenagers favor newsfluencers who are inspiring and friendly (character), are honest and direct (tone), use simple and fun speech (language), and aim to educate and inform (purpose). Participants express a desire for journalists who “talk to me as a friend”, emphasizing authenticity, emotional proximity, and conversational clarity over traditional, formal modes of reporting. These insights suggest that effective youth-oriented journalism on social media must balance factual accuracy and emotional engagement, blending education with entertainment. The research contributes to emerging scholarship on social media journalism and youth news consumption by highlighting how relational and affective communication strategies can enhance young audiences’ trust, understanding, and participation in news. Full article

This study examines how Generation Z’s digital practices on TikTok and Instagram shape their music festival experiences, focusing on event perception, engagement, and the development of collective identity. The aim is to identify key factors connecting online and offline aspects of festival participation. The research adopts a quantitative approach based on an online survey of 248 respondents born between 1995 and 2010 from various regions of Serbia. Data were analyzed in SPSS 26.0 using Spearman correlation, quantile regression, and the Mann–Whitney test. Given the exploratory nature of the study, the findings should be interpreted accordingly. Findings show that frequent social media use has a positive but limited effect on how important these platforms are perceived for the festival experience. However, user-generated content created by attendees plays a more significant role in shaping engagement and attitudes than influencer content. Influencer credibility also influences how festivals are interpreted digitally. The interplay between online interaction and offline participation motivates content sharing and reinforces a sense of community. Overall, the study concludes that social media and digital narratives are central to Generation Z’s festival experience. Authentic, attendee-created content strongly contributes to collective identity, helping bridge digital and physical dimensions—insights valuable for festival organizers, influencers, and cultural tourism. Full article