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The present study investigates the antecedents of sharenting, underlying strategies to mitigate the privacy risks of sharing children's personally identifiable information (PII) and majorly explores the relationship between sharenting activities of the parents and their buying behaviour. The study corroborates the previous studies in an advanced manner and adds a new construct “sherub marketing” as an effective marketing tool to impact the buying decisions of the parents.

Following interpretative phenomenological analysis, semi-structured personal interviews were conducted towards actively engaged parents on social media. For inferential analysis, responses of 23 parents were analysed with the help of theoretical thematic analysis

The findings uncover the multifaceted reasons persisting behind sharenting activities of the parents and observe a strong relationship between sharenting and buying behaviour of parents. The study results into exploration of sherub marketing as an effective marketing tool to influence the actions of the sharenters.

The study will be of use to both the practitioners and the society as a whole as it indicates the ramification of parental sharing and the role of marketers in influencing the purchasing decisions of the sharenters.

The present study is a novice and untapped area in the literature of interactive marketing and sheds light on sherub marketing as an effective marketing strategy.

The purpose of this paper is to identify the motives for posting or sharing food photos using social media, focussed within the context of fine dining (FD) restaurants.

Ethnographic fieldwork was conducted in France by combining analysis of qualitative diary research and transcripts of focus group discussions.

The motivation to take food images can be broadly categorised according to experiential (hedonism, altruism and passion collecting) and symbolic (social status, uniqueness, self-esteem and self-presentation) benefits.

This research is limited by its relatively small sample size and the inability to consider the direct influences of demographic variables and attitudes to FD and social media. Moreover, the cultural context of the study needs to be considered as the study took place in France.

User-generated images are increasingly an integral aspect of the holistic dining experience. Luxury restaurants need to leverage the opportunities of user-generated content. The FD experience needs to be visually captured and expressed. This can include both tangible and intangible attributes.

Although the literature has provided a comprehensive overview of social media behaviour, the efficacy of a gastronomic perspective is limited. To the authors’ knowledge, this is the first study to investigate consumer-generated postings of images of food within the luxury restaurant classification.

This research was conducted to outline the capturing and analysis of composite texts. We contextualize this using selfies as image and textual data sourced from Instagram and analyzed using a three stage analysis approach from a genre perspective.

The capturing of composite texts is outlined for numerous services available to researchers to study social media contexts. The analysis applies a three-stage technique of (1) what is shown, (2) what is said, and (3) what is the central narrative to overcome interpretive limitations of privileging text over image or vice versa.

Based on their structural characteristics, seven genre types emerged from the coded sample set.

Issues arise in capturing this data as social media platforms change their access and usage policies and as capturing services alter their capabilities.

The paper outlines a novel approach to capturing and understanding the mimesis and diegesis of selfies as composite texts.

Online images can convey sensory-based elements affecting digital users' emotions and digital engagement. The purpose of this study is to investigate which image-based features are more effective in conveying and stimulating particular emotions and engagement towards organizations operating in the food industry.

An online experimental survey was implemented. Two image-based features, narrativity and dynamism were chosen. The stimuli comprise four images, one with high and one with low level of narrativity, and one with high and one with low dynamism, published by a food company on its official Instagram account. Food-identity, emotional appeals and digital visual engagement behaviours were measured. A total of 141 students between 19 and 25 years old of a European University completed the questionnaire. Data was analysed through SPSS software using t-test analysis.

Results show that both narrativity and dynamism impact digital users' emotions and it was found to impact digital visual engagement attitude. Food involvement was measured in terms of food identity impact the effects of specific image-based features on emotions and visual engagement.

The study focuses on only two visual social semiotics features – narrativity and dynamism – and therefore, only partially captures the potentialities of images in digital communications.

This study provides professionals with empirical evidence and insights for effectively planning a visual social media strategy.

This paper contributes to the stream of research in social media communications by investigating the visual social semiotic features of images published online by a food company.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

As adults and young adults have become increasingly active on social media, public libraries have incorporated social media alongside their more traditional services. However, libraries are faced with the challenging task of determining how to successfully engage with their users through social media. This chapter examines research literature from both social media and information studies to explore evidence-based results on providing popular information services and resources for adult and young adult users in social spaces. Key elements of social media use by libraries identified in this review include promotion of information resources and services, participation and engagement, social care, pastoral care, outreach, cocreation and motivation of users, advocacy and crowdsourcing, and measurement and assessment. Based on results from current research, best practices and assessment methods for social media are discussed which offer practical considerations for selecting social media platforms appropriate to a library’s mission, goals, and objectives, with examples relevant to a variety of social media platforms. The chapter also offers a review of social media platforms, practices, and assessment designed to inform librarians and library managers in decision-making about library social media efforts.

This paper demonstrates how #50+ fashion Instagram influencers contribute to the social construction of cognitive age through their aesthetic digital labours.

Non-participative netnography was used in the form of visual and textual analysis of over 300 Instagram posts including images, captions and comments.

Findings reveal how outfit selection, background choices and bodily poses redefine expressions of look age through forms of aesthetic labour. Post-construction, hashtag and emoji usage illustrates how influencers refrain from directly posting about the fashion brands that they endorse. Instead, image and personality work visually attracts followers to politically charged posts which directly impact upon the social and cultural contexts where influencers are active. This ties into present-day wider societal discourses.

50+ fashion influencers have high spending power. Fashion brands should refrain from using #brand and collaborate in more subtle ways and concentrate on challenging the negativity of the old-age cliché.

The study advances theory on the social construction of age in fashion studies by combining cognitive age with aesthetic labour to identify the characteristics of the social phenomenon of the 50+ Instagram influencer. It applies principles from critical visual analysis to digital context, thereby advancing the qualitative netnographic toolkit.

Digital technologies are changing the ways in which the meanings and identity of both consumers and brands are constructed. This research aims to extend knowledge of how consumer-made “selfie” images shared in social media might contribute to the destabilization of brands as assemblages.

Insights are drawn from a critical visual content analysis of three popular champagne brand accounts and consumer-made selfies featuring these brands in Instagram.

This study shows how brands and branded selves intersect through “heterotopian selfie practices”. Accentuated by the rise of attention economy and “consumer microcelebrity”, the authors argue that these proliferating selfie images can destabilize spatial, temporal, symbolic and material properties of brand assemblages.

The implications include a consideration of how selfie practices engender new challenges for brand design and brand management.

This study illustrates how a brand assemblage approach can guide investigations of brands at multiple scales of analysis. In particular, this paper extends knowledge of visual brand-related user-generated content in terms of how consumers express, visualize and share selfies and how the heterotopian quality of this sharing consequently shapes brand assemblages.

The purpose of this paper is to introduce and define social food pleasure as a new conceptual framework that can promote pleasurable and healthy food experiences.

By reviewing the literature related to food well-being and pleasure primarily from marketing and management fields and by looking at current trends appealing to food consumers and food enjoyers, the authors propose a new conceptual framework of social food pleasure.

The authors conceptualize social food pleasure as “the enjoyment derived from the acts of sharing food experiences offline, online, and for society at large, that positively contributes to consumers’ overall pleasure and satisfaction with consumer’s food consumption”. Moreover, the authors identify three key contexts of applications of social food pleasure. Sharing offline relates to the social activities that can help achieve pleasure with food. Sharing online concerns new media tools which allow for the connection between consumers and food to enhance food pleasure. Sharing for society considers the current pleasure of consumers derived from having a positive social experience based on food consumption.

By defining social food pleasure and proposing a conceptual framework of the three contexts of application, the authors advance the understanding of what constitutes pleasurable food experiences, connecting it to healthy food choices and well-being.