A framework for the forensic investigation of unstructured email relationship data

Our continued reliance on email communications ensures that it remains a major source of evidence during a digital investigation. Emails comprise both structured and unstructured data. Structured data provides qualitative information to the forensics examiner and is typically viewed through existing tools. Unstructured data is more complex as it comprises information associated with social networks, such as relationships within the network, identification of key actors and power relations, and there are currently no standardised tools for its forensic analysis. Moreover, email investigations may involve many hundreds of actors and thousands of messages. This paper posits a framework for the forensic investigation of email data. In particular, it focuses on the triage and analysis of unstructured data to identify key actors and relationships within an email network. This paper demonstrates the applicability of the approach by applying relevant stages of the framework to the Enron email corpus. The paper illustrates the advantage of triaging this data to identify (and discount) actors and potential sources of further evidence. It then applies social network analysis techniques to key actors within the data set. This paper posits that visualisation of unstructured data can greatly aid the examiner in their analysis of evidence discovered during an investigation

Graph Theory and Networks in Biology

In this paper, we present a survey of the use of graph theoretical techniques in Biology. In particular, we discuss recent work on identifying and modelling the structure of bio-molecular networks, as well as the application of centrality measures to interaction networks and research on the hierarchical structure of such networks and network motifs. Work on the link between structural network properties and dynamics is also described, with emphasis on synchronization and disease propagation.Comment: 52 pages, 5 figures, Survey Pape

Connecting the Dots: Leveraging Social Network Analysis to Understand and Optimize Collaborative Dynamics Within the Global Film Production Network

In recent years, the global film industry has observed a notable surge in international cooperation and cross-border investments. However, a comprehensive overview of these collaborative investments within the industry is lacking. This study employs social network analysis to delve into the possibilities that lie in collaborative efforts and joint investments within the film sector. The research constructs a network of 150 countries based on shared creative elements in their film productions, comprising over 7800 interconnected links. Employing measures of centrality, certain pivotal nations such as the United States, China, and England emerge as influential nodes, showcasing a strong potential to steer industry growth through collaborative engagement. Through a more detailed exploration involving community identification, distinct clusters centered around thematic commonalities that have converged through joint creative endeavors become evident. For example, the "Global Thrill Seekers" community focuses on action films, whereas the "Cultural-Social Cinema Group" addresses worldwide cultural and social issues. Each of these communities presents distinctive perspectives for international cooperation and the collaborative creation of content. This analysis significantly enhances our understanding of the global film network's structure and dynamics, while concurrently highlighting promising pathways for future investment and collaborative initiatives. The research underscores the critical role of leveraging social network analysis methodologies to optimize informed decision-making concerning collaborative investments, thereby paving the way for anticipatory outcomes. This study not only contributes insights but also serves as a model for investigating data-centric participation within the creative industries

Effects of Donor- and Supporter-Based Campaign Networks on Crowdfunding Campaign Success

Driven by the increasing popularity of crowdfunding, academic researchers have examined the impacts of internal social capital accumulated on crowdfunding platforms and external social capital formed through online and offline friend networks on campaign success. However, no research has examined the impacts of social networks from a structural perspective. In the current research, we investigate the extent to which donor- and supporter-based campaign network centralities affect the amount of capital a fundraising campaign is able to generate. Using a panel data set collected from a donation-based crowdfunding platform, Fundly, we reveal that campaign network centralities based on strong ties (shared donors) and weak ties (shared supporters) are more important predictors of fundraising success than the number of donors a campaign has