African youths and the dangers of social networking: a culture-centered approach to using social media

With rising numbers of Facebook, Twitter and MXit users, Africa is increasingly gaining prominence in the sphere of social networking. Social media is increasingly becoming main stream; serving as important tools for facilitating interpersonal communication, business and educational activities. Qualitative analyses of relevant secondary data show that children and youths aged between 13 and 30 constitute Africa’s heaviest users of social media. Media reports have revealed cases of abuse on social media by youths. Social networks have severally been used as tools for perpetuating crimes such as; cyberbullying and violence against girls and women. This study proposes a ‘Culture-centered Approach’ to the use of social media in a bid to minimize these cybercrimes and encourage the responsible use of social media amongst African youths. The Culture-centered Approach, which incorporates the tenets of Information Ethics, stresses the need for the respect of the dignity and rights of other online users as well the application of good cultural values and ethical behavior while on social media platforms.     

SocConnect: A personalized social network aggregator and recommender

Users of Social Networking Sites (SNSs) like Facebook, LinkedIn or Twitter, are facing two problems: (1) it is difficult for them to keep track of their social friendships and friends’ social activities scattered across different SNSs; and (2) they are often overwhelmed by the huge amount of social data (friends’ updates and other activities). To address these two problems, we propose a user-centric system called “SocConnect” (Social Connect) for aggregating social data from different SNSs and allowing users to create personalized social and semantic contexts for their social data. Users can blend and group friends on different SNSs, and rate the friends and their activities as favourite, neutral or disliked. SocConnect then provides personalized recommendation of friends’ activities that may be interesting to each user, using machine learning techniques. A prototype is also implemented to demonstrate these functionalities of SocConnect. Evaluation on real users confirms that users generally like the proposed functionalities of our system, and machine learning can be effectively applied to provide personalized recommendation of friends’ activities and help users deal with cognitive overload.     

Social media competitive analysis and text mining: A case study in the pizza industry

Social media have been adopted by many businesses. More and more companies are using social media tools such as Facebook and Twitter to provide various services and interact with customers. As a result, a large amount of user-generated content is freely available on social media sites. To increase competitive advantage and effectively assess the competitive environment of businesses, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the textual information on their competitors’ social media sites. In an effort to help companies understand how to perform a social media competitive analysis and transform social media data into knowledge for decision makers and e-marketers, this paper describes an in-depth case study which applies text mining to analyze unstructured text content on Facebook and Twitter sites of the three largest pizza chains: Pizza Hut, Domino's Pizza and Papa John's Pizza. The results reveal the value of social media competitive analysis and the power of text mining as an effective technique to extract business value from the vast amount of available social media data. Recommendations are also provided to help companies develop their social media competitive analysis strategy.     

Big data-assisted social media analytics for business model for business decision making system competitive analysis

Business is based on manufacturing, purchasing, selling a product, and earning or making profits. Social media analytics collect and analyze data from various social networks such as Facebook, Instagram, and Twitter. Social media data analysis can help companies identify consumer desires and preferences, improve customer service and market analytics on social networks, and smarter product development and marketing investments. The business decision-making process is a step-by-step process that enables employees to resolve challenges by weighing evidence, evaluating possible solutions, and selecting a route. In this paper, Big Data-assisted Social Media Analytics for Business (BD-SMAB) Model increases awareness and affects decision-makers in marketing strategies. Companies can use big data analytics in many ways to enhance management. It can evaluate its competitors in real-time and change prices, make deals better than its competitors' sales, analyze competitors' unfavorable feedback and see if they can outperform that competitor. The proposed method examines social media analysis impacts on different areas such as real estate, organizations, and beauty trade fairs. This diversity of these companies shows the effects of social media and how positive decisions can be developed. Take better marketing decisions and develop a strategic approach. As a result, the BD-SMAB method enhance customer satisfaction and experience and develop brand awareness.     

The applications of social commerce constructs

Social commerce has evolved quickly in practice and gained attention in the IS discipline. However, trust has remained a vital component and is dominantly worth investigating. The purpose of this study, therefore, is to examine the roles of social commerce constructs and social support constructs (i.e., emotional support and informational support) in establishing trust on online community platforms. The study will apply the theoretical foundation of social commerce constructs proposed by Hajli. In order to provide a detailed understanding of the proposed model, a quantitative study involving a survey data gathered from online communities in Malaysia, including Facebook, Trip Advisor and LinkedIn was conducted. The data was analyzed and hypotheses were tested with structural equation modeling (SEM). Our results shed some lights on social commerce literature. The findings show that there are significant effect of social commerce constructs on social support, namely the emotional and informational support, and in turn, on trust- building.     

Investigating consumers’ online social shopping intention: An information processing perspective

Online social media is transforming the way customers communicate and exchange product information with others. Consumers increasingly rely on the opinions and recommendations from social media members when making purchasing decisions. However, information received from social media may have different meanings and social implications for consumers. Based on the theory of informational social influence and heuristic-systematic model (HSM), we develop a model to understand the relative importance of informational social influence, normative social influence, and perceived information quality on the consumer’s social shopping intention under different levels of product involvement. The results of the structural equation modeling (SEM) using a sample of 503 consumers in the Facebook brand fan pages indicate that social influences have a greater impact on the consumer’s social shopping intention than perceived information quality. Three social interactional factors (perceived similarity, familiarity, and expertise) have a positive effect on social shopping intention via the mediation of informational, normative social influence and perceive information quality. The multiple-group analysis suggests that high product-involved consumers are motivated to exert more cognitive effort to evaluate the product information. In contrast, low product-involved consumers are more susceptible to informational social influence. We draw on these findings to offer implications for researchers and practitioners.     

Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India

Increasingly firms are looking to use social media to connect with different stakeholders as plans on building presence on such platforms are becoming part of top-level strategy. The purpose of this study is to identify the factors that would help the Small and Medium Enterprises (SMEs) of India to adopt Social Media Marketing (SMM) mechanisms for improving their business impact. Adoption of SMM by SMEs has considerable impact on the improvement of business outcome of the SMEs. A theoretical model has been developed with the help of theory borrowed from TAM and UTAUT2 with some modifications to explore this impact through business performance, sales, connect with customers, identify customer' needs and creativity of the employees. The theoretical model has been validated empirically using a survey of 310 firms and subsequent analysis have been carried out using structured equation modelling. The results highlight that perceived usefulness, perceived ease of use and compatibility positively affect impact of SMM after adoption by the SMEs. The facilitating conditions have insignificant impact whereas cost has a significant but negative impact on the use of SMM by SMEs. Since there are a few studies in this context, the study contributes to existing literature on the impact of SMM in SMEs in an emerging economy.     

Do your social media lead you to make social deal purchases? Consumer-generated social referrals for sales via social commerce

The advent of social commerce has resulted in a new business model for e-commerce. Although studies on this business model have increased over time, they have paid less attention to its core business model: consumer-generated social influence on sales on a social commerce site. Therefore, in this paper, we examine the effect on sales of social sharing, such as Facebook “likes” and Twitter tweets, which generate social influence, using data from major social commerce companies. We find that consumer-generated social referrals regarding deals significantly boost sales in social commerce. When we examine deals involved in national sales, this finding holds only for Facebook but not for tweets. These findings have the implication for managers that not all social referrals are meaningful in increasing sales for their business.     

How social media live streams affect online buyers: A uses and gratifications perspective

Social media live streams (SMLSs) are becoming mainstream e-commerce platforms, especially for direct selling, offering online retailers (e-tailers) immense consumer interaction and engagement levels. Despite their growing prevalence, e-tailers face difficulties capitalising on this platform to enhance retail operations. This paper explores how SMLSs affect consumers' purchase intentions by exploring their motivations for participating in e-commerce SMLSs. To this end, we used the uses and gratifications (U&G) theory to explain how using SMLSs to satisfy consumers' needs could lead to high or low purchase intentions. It was done by collecting cross-sectional data from 795 consumers who have participated in e-commerce SMLSs. The data were analysed using partial least squares-structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). Our findings revealed that people use SMLSs to satisfy their need for value, social identification, and the medium's attributes. Based on these findings, we show six configurations that lead to high or low purchase intentions and make corresponding theoretical propositions. Thus, our study contributes to the research and practice of using SMLSs for online shopping.     

Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities,Challenges, and Future Directions

People increasingly use Social Media (SM) platforms such as Twitter and Facebook during disasters and emergencies to post situational updates including reports of injured or dead people, infrastructure damage, requests of urgent needs, and the like. Information on SM comes in many forms, such as textual messages, images, and videos. Several studies have shown the utility of SM information for disaster response and management, which encouraged humanitarian organizations to start incorporating SM data sources into their workflows. However, several challenges prevent these organizations from using SM data for response efforts. These challenges include near-real-time information processing, information overload, information extraction, summarization, and verification of both textual and visual content. We highlight various applications and opportunities of SM multimodal data, latest advancements, current challenges, and future directions for the crisis informatics and other related research fields.     

Put your money where your mouth is: Using deep learning to identify consumer tribes from word usage

Internet and social media offer firms novel ways of managing their marketing strategy and gain competitive advantage. The groups of users expressing themselves on the Internet about a particular topic, product, or brand are frequently called a virtual tribe or E-tribe. However, there are no automatic tools for identifying and studying the characteristics of these virtual tribes. Towards this aim, this paper presents Tribefinder, a system to reveal Twitter users’ tribal affiliations, by analyzing their tweets and language use. To show the potential of this instrument, we provide an example considering three specific tribal macro-categories: alternative realities, lifestyle, and recreation. In addition, we discuss the different characteristics of each identified tribe, in terms of use of language and social interaction metrics. Tribefinder illustrates the importance of adopting a new lens for studying virtual tribes, which is crucial for firms to properly design their marketing strategy, and for scholars to extend prior marketing research.     

Flourishing on facebook: virtue friendship & new social media

The widespread and growing use of new social media, especially social networking sites such as Facebook and Twitter, invites sustained ethical reflection on emerging forms of online friendship. Social scientists and psychologists are gathering a wealth of empirical data on these trends, yet philosophical analysis of their ethical implications remains comparatively impoverished. In particular, there have been few attempts to explore how traditional ethical theories might be brought to bear upon these developments, or what insights they might offer, if any. In attempting to address this lacuna in applied ethical research, this paper investigates the ethical significance of online friendship by means of an Aristotelian theory of the good life, which holds that human flourishing is chiefly realized through ??complete?? friendships of virtue. Here, four key dimensions of ??virtue friendship?? are examined in relation to online social media: reciprocity, empathy, self-knowledge and the shared life. Online social media support and strengthen friendship in ways that mirror these four dimensions, particularly when used to supplement rather than substitute for face-to-face interactions. However, deeper reflection on the meaning of the shared life (suzên) for Aristotle raises important and troubling questions about the capacity of online social media to support complete friendships of virtue in the contemporary world, along with significant concerns about the enduring relevance of this Aristotelian ideal for the good life in the 21st century.     

Influence of social media on operational efficiency of national scenic spots in china based on three-stage DEA model

An increasing number of national scenic spots around the world use social media, such as micro-blogs and Twitter, to promote their popularity and improve their operational performance. National scenic spots may adopt different social media behaviors that lead to unbalanced operational performance. This study takes the perspective of social media adoption in national scenic spots by looking into the influence of social media adoption behaviors on operational performance based on the three-stage data envelopment analysis model. We found that most of the national scenic spots in China have low pure technical efficiency and that operational performance, including social media popularity and operational performance, is significantly determined by various social media adoption behaviors.     

Consumer engagement via interactive artificial intelligence and mixed reality

The use of immersive technologies has changed the consumption environment in which retailers provide services. We present findings from a study designed to investigate consumer responses toward a $17 million AI-embedded mixed reality (MR) exhibit in a retail/entertainment complex which combines advanced technology entertainment with retail shopping. Findings from our study demonstrate that the quality of AI (i.e., speech recognition and synthesis via machine learning) associated with an augmented object increases MR immersion associated with spatial immersion, MR enjoyment, and consumers’ perceptions of novel experiences. Collectively, these increase consumer engagement, and positively influence behavioral responses—specifically, purchase intentions and intentions to share experiences with social groups. Overall, findings from this study show that interactive AI and MR technology open new avenues to promote consumer engagement.     

Leveraging social grouping for trust building in foreign electronic commerce firms: An exploratory study

Internet development has fueled e-commerce firms’ globalization efforts, but many have met with only limited success. This often stems from the foreign firms’ limited understanding of a focal country's local culture and idiosyncrasies. Foreign firms are usually viewed as out-group entities, which lowers consumers’ trust in them. The extent of such a phenomenon varies. In locations where people are more skeptical of out-groups, a critical question is whether it is possible to transform such foreign out-group firms into in-groups, specifically with the support of popular social networking media. Based on Social Identity Theory and Trust Transference Process, five strategies leveraging social grouping and social ties to build trust for foreign electronic commerce firms were proposed. A survey was conducted to examine their effectiveness. The results suggest that social-grouping strategies are useful for in-grouping foreign out-group entities to build trust, and the effectiveness of strategies is determined by the social similarity and psychological distance between the consumer and the endorser. This has important implications for scholars and practitioners, both local and abroad, to leverage social grouping to boost Internet sales.     

Others Share this Message,So We Can Trust It? An Examination of Bandwagon Cues on Organizational Trust in Risk

Consideration of social media use for issues of risk communication has received rapid attention in the scholarly literature. However, specific features of social media and their relevance for risk communication warrant continued investigation. The current study examines how system-generated cues available in social media impact perceptions of trust at the organizational level. After viewing one of three mock Twitter pages from an organization that varied the number of retweets concerning the risk of contaminated food in grocery stores, participants were asked to report their perceived trust in the organization. Data indicate a reverse bandwagon or snob effect, such that having too many retweets results in lower judgments of organizational trust. Results are discussed in addition to limitations and future directions for research.     

Facebook usage and mental health: An empirical study of role of non-directional social comparisons in the UK

The present paper explores the relationship between nature of Facebook usage, non-directional comparisons and depressive syndromes. The extant research on linkage between social media usage and mental health is inconclusive. The paper uses data collected through an online survey of 399 Facebook users in the UK. A Facebook frequency rating scale was developed and validated as a part of the study. The Iowa-Netherlands Comparison Orientation Measure was modified and used to measure social comparison. The depressive syndromes were captured by the modified Center for Epidemiological Studies Depression Scale. The Rank Theory of Depression was used a guiding framework. The data collection had focused on the 20–29 year olds, as justified by the literature.The study found a negative relationship between active Facebook use and non-directional social comparisons. The relationship was reversed in the case of passive usage. There is small but significant causal linkage between increased non-directional social comparisons and depressive symptoms among the users.     

Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning

Social commerce mediated by social media and social network platforms has led to the development of new business models in e-commerce and digitized the consumer decision journey. Social interaction is considered as a prerequisite for successful social commerce since consumers now expect an interactive and social experience while making purchase decisions. Drawing on word of mouth (WOM) and observational learning theories, we conceptualize social interactions in social commerce environments into two forms: WOM communication and observing other consumers’ purchases, and examine their impact on consumer purchase intention and actual purchase behavior. Analyzing primary data (n = 217) collected from surveyed active consumers within social commerce sites at two stages (pre-purchase and post-purchase), we found that positive and negative valence WOM, WOM content, and observing other consumers’ purchases significantly affect consumers’ intention to buy a product, thereby increasing the likelihood of actual buying and sharing product information with others on social commerce sites.     

Understanding the dynamics of politicians' visibility in traditional and social media

This study examines the extent to which politicians' visibility in traditional news coverage explains individual politicians' visibility on social media, and vice versa. We also explore whether these relationships depend on commonly identified characteristics of individual politicians. We collected data for all elected candidates from the 2012 Dutch national elections covering each 15 days prior to the election day (N = 2250). This includes 2736 newspaper articles and 77,597 mentions on Facebook and Twitter. Our results show that the traditional news agenda and social media agenda impact each other, but that the reciprocal influence is not independent of politician characteristics.