Who Will Retweet This? Automatically Identifying and Engaging Strangers on Twitter to Spread Information

There has been much effort on studying how social media sites, such as Twitter, help propagate information in different situations, including spreading alerts and SOS messages in an emergency. However, existing work has not addressed how to actively identify and engage the right strangers at the right time on social media to help effectively propagate intended information within a desired time frame. To address this problem, we have developed two models: (i) a feature-based model that leverages peoples' exhibited social behavior, including the content of their tweets and social interactions, to characterize their willingness and readiness to propagate information on Twitter via the act of retweeting; and (ii) a wait-time model based on a user's previous retweeting wait times to predict her next retweeting time when asked. Based on these two models, we build a recommender system that predicts the likelihood of a stranger to retweet information when asked, within a specific time window, and recommends the top-N qualified strangers to engage with. Our experiments, including live studies in the real world, demonstrate the effectiveness of our work

Social Media Marketing: The Effect of Information Sharing, Entertainment, Emotional Connection and Peer Pressure on the Attitude and Purchase Intentions

Instant communications trough social media platforms have enabled consumers to create, publish and share content, data and information regarding brands and products. It is crucial to examine its marketing power by investigating the user’s attitude towards the brand and purchase intentions influenced by the functions of social media. Thus, the purpose of this study to examine the effects of information sharing, peer pressure, entertainment and emotional connection in a social media setting on the user’s attitude toward a brand present in social media thereby influencing their purchase intentions from the brand

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments

Ubiquitous computing services constitute a new information technology that can be used in thousands of potential applications and environments. Ubiquitous computing is also changing the classic paradigm of information technology as it is forcing social and cultural changes. Determining factors affecting the use of ubiquitous services is essential to correctly define the characteristics of new value added services. However, this study investigates not only these factors, but also the moderating effect of previous experience. Due to the technological nature of ubiquitous services, previous experience alters the way in which potential users face these services. Findings suggest that previous experience changes the way in which antecedent relates to basic TAM constructs. The derived research models and empirical results also provide valuable indicators for future research and managerial guidelines for the successful adoption of ubiquitous computing servicesJunta de Andalucia. Consejería de Economía, Innovación, Ciencia y Empleo P12-SEJ-32

Information-seeking on the Web with Trusted Social Networks - from Theory to Systems

This research investigates how synergies between the Web and social networks can enhance the process of obtaining relevant and trustworthy information. A review of literature on personalised search, social search, recommender systems, social networks and trust propagation reveals limitations of existing technology in areas such as relevance, collaboration, task-adaptivity and trust. In response to these limitations I present a Web-based approach to information-seeking using social networks. This approach takes a source-centric perspective on the information-seeking process, aiming to identify trustworthy sources of relevant information from within the user's social network. An empirical study of source-selection decisions in information- and recommendation-seeking identified five factors that influence the choice of source, and its perceived trustworthiness. The priority given to each of these factors was found to vary according to the criticality and subjectivity of the task. A series of algorithms have been developed that operationalise three of these factors (expertise, experience, affinity) and generate from various data sources a number of trust metrics for use in social network-based information seeking. The most significant of these data sources is Revyu.com, a reviewing and rating Web site implemented as part of this research, that takes input from regular users and makes it available on the Semantic Web for easy re-use by the implemented algorithms. Output of the algorithms is used in Hoonoh.com, a Semantic Web-based system that has been developed to support users in identifying relevant and trustworthy information sources within their social networks. Evaluation of this system's ability to predict source selections showed more promising results for the experience factor than for expertise or affinity. This may be attributed to the greater demands these two factors place in terms of input data. Limitations of the work and opportunities for future research are discussed