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The aim of this research is to identify the characteristics that give rise to motivations to use social apps in light of behavioral concepts related to consumers’ desires and emotional values.

Netnography is used as the main methodology to analyze and categorize user profiles of online social networks. These profiles are presented through conceptual headlines, which highlight the main characteristics of each user group.

The results of the study show that many users have become dependent on the WhatsApp application, either for technological reasons or for social reasons related to fashion and status.

Few consumers actually explained the ways they use mobile social networks in the context of the procedures and level of communication performed. However, the influence of social contexts in the consumer environment is changing perceived values focusing on prestige and status to technological elements that the majority of consumers use.

Practical implications are directly related to forming business connections in a less formal and more hedonic environment, improving market results while fostering user enjoyment. In addition, the ongoing updates to WhatsApp have brought new functionalities and improvements to previously weak features.

Although other applications offer means by which to talk and send messages, WhatsApp continues to be (as of early 2021) the most used platform for conversation in Brazil. The sovereignty of WhatsApp is directly linked to its social value, which is related to the number of consumers who daily interact via the network.

Job-related social networking websites (e.g. LinkedIn) are often used in the recruitment process because the profiles contain valuable information such as education level and work experience. The purpose of this paper is to investigate whether people can accurately infer a profile owner’s self-rated personality traits based on the profile on a job-related social networking site.

In two studies, raters inferred personality traits (the Big Five and self-presentation) from LinkedIn profiles (total n=275). The authors related those inferences to self-rated personality by the profile owner to test if the inferences were accurate.

Using information gained from a LinkedIn profile allowed for better inferences of extraversion and self-presentation of the profile owner (r’s of 0.24-0.29).

When using a LinkedIn profile to estimate trait extraversion or self-presentation, one becomes 1.5 times as likely to actually select the person with higher trait extraversion compared to the person with lower trait extraversion.

Although prior research tested whether profiles of social networking sites (such as Facebook) can be used to accurately infer self-rated personality, this was not yet tested for job-related social networking sites (such as LinkedIn). The results indicate that profiles at job-related social networks, in spite of containing only relatively standardized information, “leak” information about the owner’s personality.

This research shows how social media has affected learning at present during the COVID-19 pandemic and how it has become the largest and most convenient area of communication. In the current scenario, it seems that social networking sites not only had a profound impact on our social structure and intra-social interaction, but also affected education in general and learning English language in particular. It has been proven that these various social media platforms have created a realm of digital environment in today's new-age learning. Social media platforms are social networking sites through which people interact and communicate with each other easily and conveniently. Undoubtedly and unquestionably, social networking has been proven to be a global phenomenon that has caused a vast paradigm shift in the world of Learning and education during the current pandemic. Therefore, the present study aims to reach the extent of the impact of the various social media platforms on learning English language during the COVID-19 pandemic from the students' point of view.

The study was conducted at the undergraduate level for English language learners. The sample comprised 166 undergraduate students at Najran University. A survey questionnaire was administered to find out the impact of various social media platforms and social networking sites on learning English language in the academic year of 2020 due to the COVID-19 pandemic and to highlight possible suggestions for improving future virtual language learning.

The findings of the study contributed to the area of online learning of English language during the COVID-19 pandemic. Final results confirmed that the utilization of social media has been significantly perceived to have positively impacted learning English language in terms of writing style, reading skills, listening and lexical variation, communication skills and grammar usage.

The findings of the study can serve as fundamental indicators to implement prompt pedagogical reformations, for which a number of pedagogical implications can be proposed. Another equally important pedagogical implication is to design and provide professional development and training sessions to both students and educators on the ultimate utilization of social media as instructional technologies in the context of English language teaching and learning.

This research provides insights in developing policies to assist with the integration and utilization of social media platforms as instructional technologies in the context of English language teaching and learning and how institutions can respond to the advent of advancing technology, especially during and after the COVID-19 era. A model to improve online English language learning process is recommended as a guideline for all educators offering online learning.

To evaluate some of the current discussions about the possible impacts of social networks on the development of gastronomy in the Republic of Serbia. There could be either positive and/or negative impacts and this viewpoint provides some reflection on what the future might hold for some if not many tourism destinations in Serbia and the region when the tourism industry restarts after the pandemic of Covid-19 virus.

The research was conducted in December 2021, on a total of 244 respondents in three cities in Serbia. SPSS software was used, version 26.00, and the obtained data were analyzed by descriptive statistics. Then, to determine the structure of the questionnaire and the percentage of variance, an exploratory factor analysis was performed together with a higher order factor analysis, in order to obtain the desired number of factors. Subsequently, the authors used multiple regression analysis to confirm the significance of the predictors. The goal of the research was to determine whether, and to what extent, social networks can predict the choice of restaurants and gastronomic offers in Serbia. Serbian gastronomy has a great influence on the development of tourism, so this research has a wide scientific and practical contribution.

This paper provides a context and viewpoint on the possible implications of impacts of social networks on the development of gastronomy in the Republic of Serbia in the future. It has been proven that social networks can have an impact on the development of gastronomy and tourism itself.

To examine the impact of social networks on the development of gastronomy, the authors conducted a survey online due to the current Covid-19 pandemic. The limitation of this research was precisely that the authors did not have the opportunity to conduct the research live due to the Covid-19 pandemic. It is recommended that such surveys be conducted live in direct contact with respondents in the future in order to obtain a larger sample with fully completed questionnaires.

The importance of social networks is increasingly a topic of study of world research, especially when it comes to gastronomy, which is becoming increasingly important as an activity in the tourism industry. The results indicate that the greatest importance in predicting the choice of restaurants and gastronomic offers has social networks and marketing. The importance of the work is reflected in the recognition of the importance of social networks, in order to better place Serbian gastronomy.

This paper offers a synthesis of views that fosters an understanding of the possibility of impacts of social networks on the development of gastronomy in the Republic of Serbia before and after the Covid-19 pandemic.

The viewpoint proffered in this paper provides scope for a rapid evaluation of the current status of gastronomy tourism in Serbia which can help practitioners and researchers in the faster and better development of gastronomy and tourism.

The purpose of this paper is to analyse the individual’s experience during the use of Pinterest in a marketing learning process. This experience is a fundamental starting point from which to develop marketing learning processes that flow naturally. Thus, it is necessary to examine the components that determine the individual’s experience and to explore consequences such as collaborative learning and marketing learning performance.

To conceptualise the individual’s experience, this study focuses on her/his state of cognitive absorption (CA) and establishes a second-order formative structure made up of five components: heightened enjoyment, curiosity, control, temporal dissociation and focused immersion. The model is estimated with partial least squares modelling, using SmartPLS 2.0 software.

The results confirm the significant weights of the components, with the exception of focused immersion, and support the influence of overall CA on the proposed outcomes. They also confirm that collaborative learning exerts a positive influence on the individual’s performance.

This study makes three contributions. First, it holistically examines the individual’s experience during marketing learning and the importance of its constituent components. Second, it establishes what the consequences of the marketing learning experience are, taking into account both social and individual factors, that is, collaborative learning and individual performance. Third, Pinterest is proposed as a social network with great potential in marketing learning. It is a well-known network which includes very interesting features for learning contexts. Nevertheless, it has been little studied in research.

El objetivo de la presente investigación es analizar la experiencia del individuo durante el uso de Pinterest en un proceso de aprendizaje de marketing. Este experiencia es un punto de partida fundamental para que el proceso de aprendizaje de marketing se desarrolle de manera fluída. Así, es preciso examinar los componentes que determinan la experiencia del individuo y explorar las consecuencias, como por ejemplo, el aprendizaje colaborativo y los resultados del aprendizaje de marketing.

Con el objeto de conceptualizar la experiencia del individuo, este studio centra su atención en la absorción cognitiva (AC) y propone una estructura formativa de segundo orden compuesta por cinco componentes: mayor disfrute, curiosidad, control, disociación temporal e inmersión enfocada. El modelo es estimado mediante el uso de Modelización de Mínimos Cuadrados Parciales, empleando el software SmartPLS 2.0.

Los resultados confirman el significativo peso de los componentes, con la excepción de la inmensión enfocada, y apoya la influencia de la AC general sobre las consecuencias propuestas. Estos resultados también confirman que el aprendizaje colaborativo tiene una influencia positiva sobre los resultados del individuo.

Este estudio ofrece tres contribuciones. En primer lugar, se examina de manera holística la experiencia del individuo durante el aprendizaje de marketing y la importancia de sus componentes. En segundo lugar, se establece cuales son las consecuencias de la experiencia de aprendizaje de marketing, teniendo en cuenta factores sociales e individuales, es decir, aprendizaje colaborativo y resultados individuales. En tercer lugar, se propone a Pinterest como una red social con un gran potencial en el aprendizaje de marketing. Se trata de una conocida red que incluye interesantes características para los contextos de aprendizaje. A pesar de ello, ha sido escasamente estudiada por los investigadores.

Experiencia, Absorción cognitiva, Pinterest, Resultados de aprendizaje de marketing, Redes sociales

Artículo de investigación

The study seeks to understand what teachers know about students’ friend networks and how they use that information for instruction.

This qualitative study relied on interviews and sociograms that teachers drew of students’ friend networks.

Our data suggest that teachers’ awareness of their students’ friend networks varies by their experience and their exposure to students. Also, their use of this information for instruction coalesces around dimensions of grouping and social support.

This study took place at one school. To more deeply understand what teachers perceive about their students’ friend networks and how they use that information for instruction, more studies could be done with teachers in more schools.

Implications might suggest developing teachers’ social competence to support their students’ learning and development.

While studies cited in this paper have explored teachers’ knowledge of students’ social networks, this study builds on this work by exploring how that information can be useful for instruction. In addition, this study explores the use of teachers drawing sociograms as representations of what they know about students’ friend networks.

The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics.

A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model.

The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods.

This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.

This paper aims to investigate how actors in the farmer’s network influence the adoption of smart farming technology (SFT) and to understand how social media affects this adoption process, in particular focusing on the influence of social media on trust in knowledge dissemination within the network.

The methodology used a two-stage process, with semi-structured interviews of farmers, augmented by a netnographic approach appropriate to the social media context.

The analysis illustrates the key role of the farmer network in the dissemination of SFT knowledge, bringing insight into an important B2B context. While social media emerges as a valuable way to connect farmers and promote discussion, it remains underused in knowledge dissemination on SFT. Also, farmers exhibit more trust in the content from peers online rather than from SFT vendors.

Novel insights are gained into the influence of the farming network on the accelerated adoption of SFT, including the potential role of social media in mitigating the homophilous nature of peer-to-peer interactions among farmers through exposure to more diverse actors and information. The use of a social network theory lens has provided new insights into the role of trust in shaping social media influence on the farmer, with variances in farmer trust of information from technology vendors and from peers.

The purpose of this study is to understand the role of the migrant entrepreneur’s social capital and specifically their family social capital in the success of their crowdfunding ventures.

This paper develops an exploratory single case study of the Persu Bag started by a Chinese migrant entrepreneur in the USA, which was documented through in-depth interviews, email communication, social media interactions and secondary documents publicly available. This paper draws on crowdfunding and social capital literature to fulfil the purpose and adopt the perspective of the migrant entrepreneur in the study.

The study shows that the crowdfunding migrant entrepreneur’s family network contributes with their operand and operant resources from both the country of residence and country of origin. Besides having financial capacity, institutional knowledge and experience from both the host and home countries, the family network in both countries make the crowdfunding immigrant entrepreneur’s families more resourceful, providing additional benefits to the crowdfunding migrant entrepreneurs in the development of the campaign and crowdfunded venture.

This study broadens the understanding of the ways migrant entrepreneurs can rely on their family social capital for building financial capacity and starting a crowdfunded venture.

This study aims to assess the effect of updating the Phase I data – to enhance the parameters' estimates – on the control charts' detection power designed to monitor social networks.

A dynamic version of the degree corrected stochastic block model (DCSBM) is used to model the network. Both the Shewhart and exponentially weighted moving average (EWMA) control charts are used to monitor the model parameters. A performance comparison is conducted for each chart when designed using both fixed and moving windows of networks.

Our results show that continuously updating the parameters' estimates during the monitoring phase delays the Shewhart chart's detection of networks' anomalies; as compared to the fixed window approach. While the EWMA chart performance is either indifferent or worse, based on the updating technique, as compared to the fixed window approach. Generally, the EWMA chart performs uniformly better than the Shewhart chart for all shift sizes. We recommend the use of the EWMA chart when monitoring networks modeled with the DCSBM, with sufficiently small to moderate fixed window size to estimate the unknown model parameters.

This study shows that the excessive recommendations in literature regarding the continuous updating of Phase I data during the monitoring phase to enhance the control chart performance cannot generally be extended to social network monitoring; especially when using the DCSBM. That is to say, the effect of continuously updating the parameters' estimates highly depends on the nature of the process being monitored.