Social Media Networks: The Social Influence of Sentiment Content in Online Conversations on Dynamic Patterns of Adoption and Diffusion

The current study is focusing on diffusion and adoption of new digital artifacts. The goal is to explore the social role of user-generated content (UGC) during the diffusion process of digital artifacts in the context of online social networks. The study spans a wide range of analytics methods and tools such as predictive modeling, latent sentiment analysis, data retrieval, and other tools of time-series analysis & visualization. Data collection is conducted on 260 new digital products and more than 105 thousand social network nodes. Results of the study provide a deeper insight into the influence of textual UGC sentiment on new product diffusion and how such a web system (i.e.: online social networks) can help to enable a process of value co-creation. The overall finding shows that Volume of Post and UGC Sentiment have a dynamic impact on Diffusion (Adoption Rate) of digital products. But, the relationships among them depend on certain situations. Specifically, UGC Sentiment has a dynamic impact on Adoption Rate in the early stage of the diffusion process. That is UGC Sentiment and Adoption Rate have a reciprocal relationship during the early stage. However, this relationship was faded out in the later stage. Volume of Post has a positive impact on Adoption Rate throughout the process. Both UGC Sentiment and Volume of Post are also more likely to influence on a single-generation and successful product than a multiple-generation product. Surprisingly, Depth of Post and Ratings did not play a significant role in the diffusion process. The study sheds light on the crowding power and the long-tail effect in online social networks. Findings also offer valuable implications for organizations to set up their strategic vision in terms of targeted marketing, customer relationship management, and information dissemination

Artificial Intelligence for Cybersecurity: A Review

The next generation of Artificial Intelligence (AI) and Machine Learning (ML) are increasingly incorporated in cybersecurity solutions. Experts predict that, over time, companies will incorporate AI into every cybersecurity product portfolio. While AI and ML increase the defenders’ capability to detect and prevent abnormal behavior patterns, attackers are also using AI and ML to learn about a target’s vulnerabilities and launch attacks. The purpose of this study is to conduct a literature review on a series of original research papers, both theoretical and empirical, to identify current challenges and issues of AI aid, misuse and threat in cybersecurity in different contexts such as business, healthcare, education, politics, and economics. To this end, the paper classifies previous AI studies into four different categories: Artificial Neural Network applications, Intelligent Agent applications, Artificial Immune System applications, Genetic Algorithm and Fuzzy Sets applications. The paper conducts a review of these applications on three main criteria: system response, system robustness and system resilience. The assessment shows that, regarding the system response, AI will improve the response capabilities and countering measures of cyber-defense systems. At the same time, it will expand the targeting ability of attackers, enabling them to use more complex and richer attacks. As more separate AI systems are connected to, the risk of serious consequences from malevolent interference may increase. Regarding the system robustness, AI can improve software design to a new level that is capable of self-testing and self- healing. However, as AI systems to make deductions and decisions without human involvements, they could be compromised and go undetected for a long time. Besides, delegating software design and testing to AI could lead to a complete deskilling of experts who need to keep testing systems so that they still can detect abnormal if AI can’t or gets it wrong. To be resilient, security systems need a huge data volume from scanning of every mouse click, monitor files, emails, mobile and endpoint devices, or even traffic data on a network to train their pattern recognition. This implies that AI can improve system resilience to attacks, but this requires extensive monitoring of the system and comprehensive data collection. This makes the system itself prone to attack even more. The paper concludes with recommendations to improve the response, robustness and resilience capability of AI systems

A Social Relational Model for Firm-Hosted Virtual Communities: The Role of Firm Support

Since the ease of participation and the usefulness of information provided by online groups continue to proliferate in the World Wide Web, people increasingly participate in different forms of virtual community (i.e. online forums, bulletin boards, message boards, chat rooms) for their purposes, such as solving problems, building social relationships, sharing passions, developing professionals. Accordingly, an increasing number of companies are now attempting to exploit this phenomenon by hosting and supporting their own online community for commercial and non-commercial purposes, such as building relationships with their customers, getting their feedback, strengthening the brand, and reducing customer service costs by enabling customer-to-customer problem solving (e.g. Wiertz and Ruyter, 2007). Typical examples of these firm-hosted online communities are Dell Community, Lego® Message Boards, Manhattan GMAT Forums, Ford Forums, iPod (Apple) Discussions, etc. The purpose of this study is to examine factors such as consumers\u27 feelings (sense of community, trust) and the host firm\u27s supports that motivate consumers to exhibit their voluntary contributions and continue their membership in a firm-hosted online community. This dissertation conceptualizes a relational social model in which sense of virtual community and virtual community loyalty are hypothesized to influence customer trust in the host firm and customer citizenship performance (loyalty intention to the host firm, voluntary participation, voluntary cooperation), respectively. Three components of the firm\u27s support to the virtual community—support for member communication, content enhancement and recognition for contribution—are theorized to moderate the relationships between sense of virtual community and trust, and between virtual community loyalty and customer citizenship performance. The overall finding that emerges from the dissertation is that customer citizenship performance is impacted by a customer\u27s sense of virtual community, loyalty to the community, and customer trust in the host firm. Of the three firm support variables, only support for member communication moderates the relationship between virtual community loyalty and voluntary participation. The dissertation makes four theoretical and managerial contributions. First, the paper presents an interdisciplinary review of extant literature on firm-hosted virtual communities and builds on it to develop a conceptualization of relationships between customer-customer social outcomes and customer-business relational outcomes. Second, while previous research has predominantly focused on firm support as an antecedent of trust in customer-business dyadic relationships (Porter, 2004), this research investigates the role of firm support as a moderator of social relational relationships. Third, the study extends the notion of relationship marketing to include customer-customer relationships which has been forgotten in the marketing literature (Clark & Martin, 1994). The implication is that the host firm can use customers themselves to build long-term customer relationships, and based on it to maintain and increase the firm\u27s market share. Finally, from a managerial perspective, this study proposes a general framework that can enable companies to better understand some of the key aspects that define and drive loyalty in online communities. Since sense of community is unique to a specific community, this dissertation also illustrates that a virtual community is an inimitable asset which can be used as a strategic tool to build competitive advantage by a firm in an online environment

Sense of Community: A Missing Link to Understand Users’ Performance in Firm-hosted Online Communities

We extended the current research stream about online communities by introducing sense of community as a new construct tounderstand the motivations of online collective and relational actions and highlight users’ loyal promotion to both the onlinecommunity and the host firm. In addition, through the lens of organizational citizenship behavior (OCB), membershipperformance was presented as a form of users’ voluntary participation, voluntary cooperation, and firm-hosted loyalty,indicating users’ total contribution to the online community and the host firm. We then examined the relationships betweenmembership performance and its potential drivers. The research model was empirically tested using self-reported data from247 users of four firm-hosted online communities. Overall, we found that sense of community, trust in the host firm, andcommunity loyalty have either full or partial effects on membership performance

Knowledge-Related Barriers to Communication and Coordination in Disaster Response: Adelphi Study

Multi-organizational ad hoc knowledge networks have the potential to improve the effectiveness of disaster response and recovery by helping organizations share information, coordinate their activities and leverage participants\u27 expertise. This paper reports an exploratory study to identify the major barriers to effectiveness in ad hoc knowledge networks in disaster response. The research methodology is a multi-panel Delphi survey, with each panel comprised of experienced emergency response professionals from different types of response organizations (e.g., fire fighters, EOC (emergency operations center) directors, law enforcement professionals). The study is currently in progress, and results from the first two panels are reported

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Modeling Adoption and Diffusion: A Multiple-Relation Approach

Previous studies on adoption and diffusion of a new product in a social network commonly assumed a single tie between a pair of actors. That means they only looked at one type of relation, while analyzing a diffusion process. However, we may have multiple ties between a pair of actors as multiple relations can arise from different modes of interaction or because of different roles people play within a network setting. Building on the IS literature on adoption and diffusion, the statistical literature on social network analysis, and the sociology literature on multiple relationships, this study proposes a new approach to develop a dynamic adoption model in a context of multiple relations. To this end, the study remodels the three well-discussed social forces of the diffusion process, including network effect, neighborhood effect and adopter effect (the self-influence by the potential adopter) in a way that reflects a significant role of the multiple-relation context

The Internet of Things: Can a Tree Talk to You?

Farm productivity is essential for meeting the growing demand for food that is fueled by rapid population growth around the world. Farming practices can obtain the greatest optimization and profitability through “smart agriculture” which adapts farming techniques to specific conditions via enabling technologies that are often based on an Internet of Things (IoT). This paper presents a case study of an IoT innovation in an unexpected location – a rural farm in Vietnam. A practical, low-cost, and environmental friendly system was developed that help farmers manage their crops with more precision in the first IoT application for the Vietnamese agriculture industry. The pilot implementation were promising and farmer feedback was positive. After some modifications, the system has been widely deployed in different provinces in Vietnam. We believe that the system would be able to help millions of farmers to get on the IoT train and that adopting IoT to initiate smart agriculture in Vietnam has sent a strong message “To be successful, the technological innovation has to integrate into local culture”