Social Computing and Social Media: Applications in Marketing, Learning, and Health

Digital advertising is used to leverage Internet technologies to deliver advertisements to consumers. For an advertisement to reach a large number of audience, business owners usually relay on social media influencers to deliver advertisements messages. However, there are a large number of influencers and it is critical step for business owners to select influencers to be hired. One important measure that has been used to assist the process of selecting an influencer is the influencer engagement rate. Engagement rate measure aims to evaluate how well an influencer can attract potential customers. The current engagement rate measures depend on a simple information such as number of followers, posts, or comments on an influencer account. In this paper we propose a more sophisticated engagement rate measure based on a carful analysis of potential customers reaction to an influencer advertisements posts. The new measure works only on advertisements posts. Also, it take into account the polarity of the comments on these posts, not only their count. To efficiently compute the new engagement rate measure over large size of data, we propose machine learning (ML) approaches to generate necessarily information to compute the new engagement rate measure. We use ML approaches, in particular classifications, in two stages. First, we use classification to efficiently classify a post to an advertisement and none advertisement post. Next, we use ML based sentiments analysis approach to determine the polarity of the comments on an advertisement post. The new measure could be used to measure users engagement to any post and in a wide range of social media platforms. We tested the new engagement rate measure using Instagram influencer accounts, in specific Instafamous accounts. Compared to the current measures, our results show that this new ML based engagement rate measure suggests significantly different ranked list of potential influencers. This ranked list of influencers are more aligned with the business needs and the accepted practices in measuring successful advertisers.

The problem of influencer identification is an important problem in social network analysis, due to the impact of influential users one the opinions of their audience. Most of the existing approaches to identify influencers are developed for static networks, whereas the social networks are time-sensitive and evolving over time. Therefore, identifying influencers over a dynamic, or stream, social network is more adequate for such problem. However, the amount of work proposed for dynamic networks are limited. Recent work proposed that identifying influencers with respect to some analysis-specific restrictions (e.g. influencers’ locations or Influence context) produces a more concrete analyses. Current models proposed to identify influencers are based on capturing the number of social actions triggered by an influencer’s social action. These models do not differentiate between social actions’ types and treat them indistinguishably. However, the type of an action a user select to do captures an important clues in how as user is influenced. In this paper we propose to solve Action-Aware Restricted Stream Influence Maximization (AR-SIM) problem that identifies the most influential social network users in real-time. We extend the Action-based dynamic model [5] to incorporate actions’ types into the model. The model does not only differentiate between the actions’ types, it gives the option to weight these actions differently; facilitating new approaches to identify influencers. We run the model with respect to a given set of commonly used restrictions. We adopted a sliding window to update efficiently the model in real time. The model is generic and can be used with any social network platform, actions types, and restrictions. We run our experiments using Twitter data where we differentiate between four action types: (tweet, retweet, reply and quote tweet) and with respect to location, topic and/or language restrictions. Our results shows that our new model is able to identify significantly different influencers based on the given actions wights. This should open the gate for more sophisticate and deeper understanding for influencers impact types over the social network. The model is generic and can be used in any type of social network.

To analyze successful consulting processes using multimodal analysis, the aim of this research is to develop a model for recognizing when a client is persuaded by a consultant using multimodal features. These models enable us to analyze the utterances of highly skilled professional consultants in persuading clients. For this purpose, first, we collect a multimodal counseling interaction corpus including audio and spoken dialogue content (manual transcription) on dialogue sessions between a professional beauty counselor and five clients. Second, we developed a recognition model of persuasion labels using acoustic and linguistic features that are extracted from a multimodal corpus by training a machine learning model as a binary classification task. The experimental results show that the persuasion was 0.697 for accuracy and 0.661 for F1-score with bidirectional LSTM.

Brands are ubiquitous for the last years, they are present in almost every space on the web and especially in social computing, social networks and social media. Their presence is linked to different aims and accompanied by comments. The professional point of view focuses on the idea that social media provide the possibility of a conversation based on transparency, equality, and proximity. Computer systems and algorithms have been developed, refined and expressly designed to facilitate the identification of “consumers” as they navigate and supposedly allow the production and broadcasting of a tailor-made advertising message.What form of advertising is finally presented on the web? A first set appears to work more on the inventiveness than on the algorithm to reach a public between unadvertising and hyperadvertising. In both cases, advertising tends to work on the spectacular side, with complex and refined narratives. A second appears to go back to the beginning of marketing and advertising in terms of narration, design and discourse. On the web, social networks and replay and streaming platforms, advertising hype is making a great and maybe regretful comeback. On the other hand, advertising falls back on pure promotion. At the same times, advertising finds old flaws, outside the regulatory systems: we see “réclame” reappearing on social networks. This communication will aim to analyze contemporary forms of advertising forged by and for the machines of the web

Research on the use of social media has shown that it tends to influence if not alter human perceptions while purchasing and added frequently targeted marketing on these platforms has also impacted on consumer buying behavior. This paper, through a rigorous systematic literature review, evaluated the topic of Social Media Marketing and critically examines the effect it has on consumer behavior, and particularly impulse buying. The search strategy used to conduct the literature review was primarily targeted towards discovering academic publications via accepted databases and literature search engines. The basis for published literature reviewed was taken from a basket of top Information Systems journals. Several themes were found to influence impulsive purchases as driven by social media marketing. These included purchasing behaviors, social media influencers, and brand loyalty where it was found that companies often exploit the vulnerabilities of the consumer psyche to maximize successful online impulse sales using social media marketing as stimulant. Both social and eCommerce technology proved to be major contributors to this phenomenon to the extent that available research considers them to be independent impulsive purchase stimuli in their own standing.

The objective of this article is to understand the way of communicative interaction of applications currently used in the sectors of material culture food in the city of São Paulo, Brazil, in order to reflect on the types of functionalities and logics that these devices establish in the mediatization of consumption and the cultures in which they operate via processes of interaction. At the same time, one observes such applications with a new dimension of work in advertising with their institutionality and promocionalities.

Based on a relationship marketing approach, this paper studies the impact of social media use on sales performance and its underlying mechanisms. A conceptual model is proposed and empirically tested from the perspective of salespeople in B2B settings. The proposed model includes both the direct influence of social media use on sales performance, and its indirect influence through relational mediators (i.e., adaptive selling behavior and relationship quality). To test the proposed model, we use structural equation modeling with a sample of 199 French B2B salespeople. The proposed model is validated, allowing us to confirm the direct and indirect role of social media use on sales performance and to better understand the underlying mechanisms associated with relational mediators.

In Japan, the number of beauty salons has been increased and reached over 250,000 at the end of 2018. On the other hand, there are some salon management problems such as price reduction and customer decrease. In such situations, it is an important not only to serve salon services, but to promote private brand (PB) items in addition to treatments. In this study, we analyzed purchase interval of PB items and predicted the purchase in a hair salon chain. First, we created explanatory variables using ID-POS data of the hair salon chain. Secondly, we selected explanatory variables using Cox proportional hazard model. Then, we performed Bayesian survival analysis to evaluate purchase interval considering customers’ heterogeneity. As a result, we could grasp appropriate timing when customers had highly purchase motivation and applied marketing measures to effective promotion.

During a long period of marketing practice, we have decided to write this article, especially seeing the problems of entrepreneurial beginnings from Romania, and from other countries from EU. In this article are highlighted the entrepreneurial mistakes encountered during my entrepreneurial activity, but also due to a long activity in the marketing theory, that it should be thought, adapted at all entrepreneurial levels. Even if it seems difficult to understand by some investors in various fields of activity, however, entrepreneurial marketing is very complex, and requires very good knowledge in the applicability of marketing combined with other fields of economics. Thus, Romanian entrepreneurs have a relatively good thinking, but in general they only consider the short-term strategy, and from here in the same terms all other components of economic disciplines. Hence a whole series of problems that arise in the development of an enterprise, especially in the second stage, when, after entering the market and the enterprise must develop on the market. Through this article I highlight the wrong decisions from a strategic point of view, with concrete examples, which are very common in Romania, but also in other countries, in entrepreneurial practice, mistakes that are widespread. I could say that, in my practice as an entrepreneur and as a theorist, in the last years I started to give more pro bono consultancy to entrepreneurs and their startups rather than to “negotiate” something with them, at least at a first discussion to help them develop their businesses. So, through quantitative research I aim to achieve as objectives the information of entrepreneurial specialists, but also of specialists in marketing theory, about the current mistakes in the application of marketing, especially where there are mistakes of economic calculations that can be very difficult be correct later.

Over the last few decades, consumers’ preferences and lifestyles have changed significantly. In such market, the number of products and services aims to mass marketing have become less effective. Therefore, personalization tailored to individual characteristics, certain segments, and one-to-one marketing focusing on individuals are becoming important. Therefore, customer relationship management, retaining existing customers and costs for acquiring new customers are important for both of academic and business field. However, for that purpose, it is essential to grasp customer behavior in more detail and use it for analysis. Therefore, in this study, we estimate the potential clusters of customers and customers’ purchase behavior. Concretely, we use pLSA and XGBoost which become popular machine learning methodologies. In this study, we set the number of store visits per month for objective variable and show a prediction model of it. Then we compare the model that incorporates the result of predicting the probability of the latent cluster as an explanatory variable with the model that incorporates a general explanatory variable.

pLSA is a useful method to know the characteristics of customer or item in marketing. In this study, we proposed a method to set the initial values more efficiently than the existing method for the problem that the final solution depends on the initial values set in the EM algorithm used by pLSA to estimate the solutions. We focused on the dimensional compression and clustering that are the characteristics of pLSA, and thought that the stability of the solution of pLSA would be improved by reflecting it in the initial values. Therefore, first, we performed correspondence analysis and k-means cluster analysis on the original data to express the features of dimensional compression and clustering. Next, we compared the performance of the pLSA results with the initial values of the proposed method and the initial values of the conventional method using random numbers. As a result, it was shown that the proposed method also converges to the same log-likelihood as the conventional method, and that the proposed method is superior in terms of convergence speed and stability.

This study aims to analyze consumer behavior during Cyber Monday and Black Friday in Chile through an information technology acceptance model. An extended technology acceptance model was created to which the Technology Continuance Use Theory was incorporated. The variables used to explain continuance intention (CI) were attitude towards shopping (A), subjective norms (NS), perceived risk (PR), perceived usefulness (PU), shopping enjoyment (SE) and convenience (C). To obtain the data necessary for the structural equation model proposed, a survey was created on the SurveyMonkey platform. The survey was disseminated through social networks during May and June 2019. The results indicated that convenience (C) positively influences shopping enjoyment (SE) (.543). Then, shopping enjoyment is the variable that influences the most attitude (.496), which is directly related, with a standardized regression coefficient of .874, to the purchase continuance intention on Cyber Monday and Black Friday. Consequently, saving time and money by doing online shopping generates a pleasure or enjoyment perception in consumers, which has a positive effect on the perception of making purchases during these events and therefore on the intention to continue buying. Other results, conclusions, and theoretical and practical recommendations are further discussed along the paper.

The purpose of the study is to investigate and clarify the factors that affect Saudi higher education institutions’ adoption and formulation of effective policies on social media. A focus group was conducted to explore the critical challenges and issues preventing Saudi higher education from creating and formulating a clear social media policy. Focus group sessions were held online, which involved administrators and policy makers from the higher education in Saudi Arabia. Data were analyzed using qualitative research methodology, specifically, the manual thematic analysis approach with the support of NVivo software. Factors perceived in this study as the major reasons and challenges for not having a clear social media policy included lack of policy makers, awareness, management support, and resources. The findings suggest that Saudi higher education institutions (HEIs) need to enhance their social media policy and may need to consider outsourcing to gather the desirable resources to formulate and implement a clear social media policy.

Customer eXperience (CX) refers to people’s expectations and perceptions when interacting with a brand/company, through systems, products and services that this offers. Student eXperience (SX) is a particular case of CX, as students interact with several products, systems and services that an educational institution offers. This article presents a review of the literature published during the last 10 years (from 2011 to 2020), indexed in three databases (Scopus, Science Direct, and IEEE Xplore). We are analyzing the SX concept, its dimensions, and the SX evaluation methods. We focused our study on undergraduate higher education students, trying to answer three research questions: what is SX?, what are the SX dimensions?, and what methods are used to evaluate SX? Literature related to SX is abundant and it shows a growing tendency. Most of the studies are related to the Social Science field. Our study offers an overview of the research on SX and offers a basis for future, specific research.

Many factors contribute to student success in college-level courses. One major factor is student access to required course materials. There is a growing number of students who, for several reasons, do not have access to materials or choose not to purchase textbooks. The negative impact of textbook cost is well known and documented and often a significant contributor to not purchasing course materials. In this paper, we explore the use of an inclusive textbook access program for several computer courses at a large community college. As part of this project, we present student feedback on this initiative and examine perceptions on textbook use and purchasing habits. The research helps gain insight into having the textbook built into the cost of the course and the impact of having access to a digital copy of the text on the very first day of class.

The end of the new normal that has resulted from the pandemic is uncertain. Meanwhile the effects of the introduction of new ways of doing things in the field of academic pedagogy are being studied from different perspectives. Within the series of trials and errors in the introduction of new technological teaching systems, greater amount of research is required, especially in populations of adult students who have suffered a deeper impact due to the pandemic, since their lives have changed by carrying out parenting, study and work processes from their homes.Initially, a review of various models that study learning acceptance and student satisfaction was carried out. From them, a series of variables and dimensions were selected developing 5 hypotheses that were arranged to be measured by an information collection instrument that was applied through an online survey to a non-probabilistic sample of 148 adult students. Then, a structural equation model was used to explore online learning acceptance and satisfaction. The model utilizes 3 dimensions: perceived online support services, perceived ease of use, and perceived utility.The main results made evident the key role of the perceived utility of online learning acceptance and student satisfaction. A second finding was the low importance of perceived ease-of-use in accepting online learning and student satisfaction. The authors concluded that several changes can be observed in the perception of students and in how they accomplish satisfaction and learning acceptance, if these are compared to previous studies.

In order to supplement the decreasing working population, there are more and more foreigner workers working in Japanese society. In such a situation where small numbers of foreigner workers need to work with Japanese people as the majority, inefficiency of the group occurs due to language or cultural barriers. This work-in-progress project collects a data corpus for understanding the problems may occur in this “unbalanced” group work and aims to provide computer aided support in the future. We collected 8.5 h of the task-oriented conversation of small groups in the following settings: one Chinese speaker/three Japanese talking in Japanese (C-J), four Chinese speakers talking in Chinese (C-C), and four Japanese talking in Japanese (J-J). In this specific paper, we analyzed a subset (9 15-min discussion sessions) of the data corpus to see the activity changes between C-J and C-C settings.

Development logs and video game streaming can be used as a tool to improve the quality of student projects and create a high-quality product that can be utilized by a general audience for STEM engagement purposes. University of Baltimore’s Lunar Surface navigation simulator was designed to fulfill NASA SUITS 2021 challenge requirements. Our goal was to design a user interface that could help lost individuals navigate through unknown terrain while using augmented reality. Participants were prompted to explore a virtual world using a menu designed for augmented reality technology and later leave feedback to help our team refine the design. This experience shows how the effort associated with collecting feedback through live streaming and remote user testing can lead students to have an improved educational experience and produce a high-quality final product.

This paper discusses the challenges faced by Emirati students enrolled in a private university in the United Arab Emirates. In particular, the study focuses on the development of their academic writing skills. It uses data collected from composition papers written in a semester through the online platform. The data was collected from undergraduate engineering and information technology students and it reports findings of a study examining the effectiveness of promoting Arabic speakers’ development of critical and analytical thinking skills using a content with a content-based approach. The data is discussed in relation to development of academic language in an English course through application of skills in an essay format. This study attempts to highlight the value of content-based approach through instructional practices and designing of online authentic assessment tasks. Two groups of engineering and computer science students participated in three different written assessments in the study. Six essay topics were designed considering students linguistic and societal factors. Data were collected via online assessments. The findings revealed significant improvements in the students’ academic writing scores and considerable reduction in plagiarism cases was also found. The quantitative and qualitative examination show positive impact of active participation in the online learning platform. Based on these findings, instructional suggestions and caveats are provided.

Group work in online classes can be a challenging task for both teachers and students. Teachers need to make sure that the group task is designed carefully to achieve its learning objectives, and students need to learn how to work efficiently as members in a group to achieve their targets and meet deadlines. This paper addresses the efficacy of group work in academic writing online classes, and it aims at exploring multicultural students’ attitudes towards working in groups in online academic writing classes. Fifty-nine students were surveyed using a Likert-scale survey, from which five students were interviewed using semi-structured interviews to explore their attitudes towards group work in the online writing classes. The findings revealed that students generally had positive attitudes towards group work in online academic writing classes; however, some students reported that technical issues caused problems at times. Results also revealed that the benefits of this experience outweighed the disadvantages. The study’s findings can be useful for practitioners and curriculum designers as they shed light on the benefits of group work in online academic writing classes and the challenges students may face during these classes.

Recent Chilean legislation established a curriculum focused on children with cognitive deficits, adapting the original English curriculum to a specialized one that can be used in Special Education Needs (SEN) schools. However, currently, Chilean SEN schools are not making use of these methods to support students to learn a new language such as English. Furthermore, the research of similar mobile applications available indicated a focus on native English speaking children with intellectual disabilities, however, did not support Spanish speaking children. Therefore, this study was created to observe the impact of mobile activities in English language instruction in the setting of a Chilean SEN school. The proposed solution was designed, developed, and implemented in conjunction with specialist teachers. Prototypes of the mobile application were installed on tablets specifically for this study and deployed in an experimental group. Students were assigned to two groups, control and experimental, where the same pre and post-tests were conducted. This included activities such as writing an English word from the image displayed, matching an image with the associated English word, and completing the missing letters of an English word (which was proven to be the most difficult activity). This experiment resulted in a significant impact on the learning achieved in the experimental group. The Cohen D resulted in 0.92 with a p-value of <0.001. Furthermore, the analysis of the standard deviation of time usage in each activity provided insights into the difficulty levels supporting modifications of future activities.

Customer eXperience (CX) includes all physical and emotional responses during the interactions with the products, systems and services that a company or an organization offers. We can consider a student as a particular case of customer, and Student eXperience (SX) as a particular case of CX. Higher education students are using not only the educational service, but they are interacting with a wide range of products, systems and services that a university offers. Chile was affected by crises since October 2019: a social outbreak crisis first, then the COVID-19 pandemic crisis. They have influenced the way in which students and universities interact, and consequently the SX. We carried out an exploratory study in order to identify how these crises have impacted the SX in the particular case of Escuela de Ingeniería Informática (School of Informatics Engineering) of the Pontificia Universidad Católica de Valparaíso (PUCV), in Chile. The paper presents our preliminary findings.

Since the start of coronavirus disease 2019 (COVID-19) pandemic, social media platforms have been filled with discussions about the global health crisis. Meanwhile, the World Health Organization (WHO) has highlighted the importance of seeking credible sources of information on social media regarding COVID-19. In this study, we conducted an in-depth analysis of Twitter posts about COVID-19 during the early days of the COVID-19 pandemic to identify influential sources of COVID-19 information and understand the characteristics of these sources. We identified influential accounts based on an information diffusion network representing the interactions of Twitter users who discussed COVID-19 in the United States over a 24-h period. The network analysis revealed 11 influential accounts that we categorized as: 1) political authorities (elected government officials), 2) news organizations, and 3) personal accounts. Our findings showed that while verified accounts with a large following tended to be the most influential users, smaller personal accounts also emerged as influencers. Our analysis revealed that other users often interacted with influential accounts in response to news about COVID-19 cases and strongly contested political arguments received the most interactions overall. These findings suggest that political polarization was a major factor in COVID-19 information diffusion. We discussed the implications of political polarization on social media for COVID-19 communication.

The Covid-19 pandemic offers a spectacular case of disaster management. In this literature, the paradigm of participation is fundamental: the mitigation of the impact of the disaster, the quality of the preparation and the resilience of the society, which facilitate the reconstruction, depend on the participation of the populations. Being able to observe and measure the state of mental health of the population (anxiety, confidence, expectations, ...) and to identify the points of controversy and the content of the discourse, are necessary to support measures designed to encourage this participation. Social media, and in particular Twitter, offer valuable resources for researching this discourse.The objective of this empirical study is to reconstruct a micro history of users’ reactions to the pandemic as they share them on social networks. The general method used comes from new processing techniques derived from Natural Language Processing (NLP). Three analysis methods are used to process the corpus: analysis of the temporal evolution of term occurrences; creation of dynamic semantic maps to identify co-occurrences; analysis of topics using the SVM method.The main empirical result is that the mask emerges as a central figure of discourse, at least in the discourse produced by certain social media. The retrospective analysis of the phenomenon allows us to explain what made the mask a focal point not only in conversation, but also in behaviors. Its value resides less in its functional qualities than in its ability to fix attention and organize living conditions under the threat of pandemic.

The shift in educational strategies and modalities brought on by the COVID-19 pandemic has intensified the need for innovative teaching methods. Both students and educators faced numerous challenges caused or exacerbated by the shift to different learning modalities and compounded by limited services and other restrictions. Adding to this complexity is the diversity in student skillset and technology literacy within the community college environment. At the same time, instructors had to manage their own issues related to the pandemic while juggling critical changes in their courses. In this paper, the authors discuss challenges in teaching several computing courses during the shift to an online format during the COVID-19 pandemic. Several challenges and strategies for supporting students in the computer science/information technology department at a large community college will be discussed, in addition to initial feedback gained from students.

Population is now aging at an unprecedented rate worldwide, which has caused an important concern about the sustainability of health, pension and social protection systems in developed and developing countries. Promoting active aging policies and practices which would improve older adults’ autonomy, independency and health status has become one of the priorities of many politicians and practitioners across the globe. In this sense, the new technologies and, more specifically, the field of Human-Computer Interaction can and should play an important role in the promotion of an active aging model within society. Nevertheless, today there is still a very limited amount of devices or services adapted to the characteristics and needs of the elderly, especially in less developed countries. The aim of this research was to introduce a new easy-to-use and accessible mobile application to promote the active aging through the integration of physical, cognitive and social activities for older adults. The proposed mobile application showed an adequate ability to assist end users in achieving a healthier and more participative way of life at older ages, which is essential to foster older adults’ empowerment within any society.

Self-reflection is an essential part of personal well-being and development. One of the strategies to support reflective thinking is to revisit personal recordings. Existing and emerging social media platforms are powerful mediums for self-reflection. However, additional mechanisms may be necessary to support deepening reflective thinking through social media use. We explore the concept; Layer Zero, a tool that helps users record reflective logs when they share on Instagram through a question set, and present them later for reflection. This paper focuses on the data collection phase of Layer Zero. We conducted 2 user studies through Instagram with a total of 29 participants to understand the potential of Instagram shares for reflection and measure the effectiveness of questions on self-reflection. We found that our approach can help users engage in deeper reflective thinking about their motivations, actions and thought processes. The results indicate various design insights for future social media reflection tools.

The COVID-19 pandemic has accelerated demand for screen-mediated social connections. The drivers of digitization of socialization are often young and social-media savvy individuals who wish to alleviate the stress of social isolation for seniors. To design successful programs, it is important to first consider intergenerational differences in both the experience of COVID-19 stress, and the affordances of technology. In this mixed-methods study, we aimed to investigate perceptual differences in how social media can assist older adults (65+) to cope with the COVID-19 stress. Data was obtained from two sources: A snow-ball survey (conducted between April - Sept 2020, n = 595); and scraping the public comments on mainstream media’s articles focusing on senior’s coping with the COVID-19 (7 sources, and 3390 valid comments). Quantitative analyses of age-related differences in attitudes towards social media, and changes in media usage after pandemic (in <25, 25–34, 35–54, 55–65, 65+ groups), indicated significant differences in what, why and how different age groups used the social media. Qualitative analyses of the comments revealed some intergenerational misunderstandings about one another’s coping needs. In general, older adults were less vulnerable to COVID-19 stress than were the younger, and technology was not their main resource for coping with social isolation. Nevertheless, communication technologies such as Zoom were important for connecting to older parents and grandchildren. These independent studies show that although technology plays an important role in keeping older adults connected, it does not address the stress of losing time to be together in person. These findings suggest that with the exception of Zoom, the usage of other social media for older adults has not changed from before the pandemic.

Population ageing has raised major concerns about the prevalence of age-related mental health deterioration which is further intensified amid the COVID-19 pandemic. Mobile health (mHealth) interventions bear promising impacts on alleviating the mental health burden of this vulnerable group. However, mHealth solutions often report a high drop-out rate suggesting a lack of motivation and engagement among users. Also, the limited number of clinically validated mHealth applications indicates an urgent demand for empirical evidence on the subject. This paper proposes a design framework for gamified mHealth activities to enhance mental and cognitive well-being of the elderly. Further, the paper outlines a research protocol to investigate the impacts of the framework on a cohort of 250 older adults in a developing country under a single-subject experimental design. Our social experiment may reveal valuable insights into the potential of mHealth solutions and gamification in this domain.

The article is devoted to the reaction of the Russian-speaking audience to news reports about the pandemic in large news groups on the VKontakte platform. Based on five scenarios for the development of discussions, the authors qualitatively researched the messages and comments to them in 30 groups devoted to the local agenda of 10 different Russian regions. The found trends were confirmed by experts from these regions. As a theoretical premise, we used the texts of classic media researchers of our time (such as Jaron Lanier, Geert Lovink and John Keane) and an analysis of how emotions, such as fear and hope, actually manifest themselves in social networks during pandemic. We also used our previous work to reflect the specifics of the Russian-speaking social media ecosystem. The study shows that in both April and November, the dominant scenarios remained the utopian, denying the presence of the virus or its danger, and the realistic scenarios. At the same time, the decrease in general interest in the pandemic agenda did not affect the fact that the emotional context of its discussion became more positive.

Coaching is a novel integrative method to help older adults with little prior experience with digital technology to interact properly with health games. However, coaching as a practice is rather case-specific and none has attempted to apply coaching into health games. This paper presents a formalized, integrative coaching model that infuses Goal Net with Propp’s functions to outline a flow of events that eventually assemble into a “coached gameplay session”. With the formalization of the Goal-Oriented Storytelling Model, the role of the coach in a health game session becomes clearer. The study presented in this paper validates GSM-driven coaching as an effective approach to bolster confidence among older adults when they interact with health games. The GSM also makes a generalizable, scalable solution to health game enjoyment possible through facilitating the creation of future digital health game coaches.

This study explores the extent to which social media manages to meet the relational needs of individuals diagnosed with Autism Spectrum Disorder (ASD) during Italy’s first COVID-19 lockdown (March – May, 2020). To this end 22 caregivers of people with ASD completed a questionnaire investigating the living conditions of the affected people during this time, their use of social media/communication tools, their anxiety levels, their perception of the usefulness of social media, and the types of cognitive and/or relational dysfunction. The results show that social media did not prove useful, even in situations of obvious need such as those experienced during the lockdown. Caregivers, however, viewed social media in a positive light only for those individuals with ASD who had used them already prior to the lockdown. Further studies are therefore needed to better design social media for the needs of people with ASD.

The treatment of chronic diseases commonly includes the long-term use of medication. However, patients typically do not accurately or continuously take their medications as prescribed. Building on medication reminders, this paper conceptualizes the term “Motivational Reminders” for enhancing reminders’ effects among unmotivated people who may “intentionally” forget to adhere to their medication. The design approach pulls in existing practices and arranges them on the internalization process outlined in the Organismic Integration Theory (OIT), one of the sub-theories of Self-Determination Theory (SDT). Based on the proposed motivation reminder system, we designed a prototype that helps the users internalize the new behavior of taking medications regularly, timely and persistently.