Transdisciplinary food systems research aims to merge insights from multiple fields, often revealing confounding, complex interactions. Computational modeling offers a means to discover patterns and formulate novel solutions to such systems-level problems. The best models serve as hubs—or boundary objects—which ground and unify a collaborative, iterative, and transdisciplinary process of stakeholder engagement. This dissertation demonstrates the application of agent-based modeling, network analytics, and evolutionary computational optimization to the pressing food systems problem areas of livestock epidemiology and global food security. It is comprised of a methodological introduction, an executive summary, three journal-article formatted chapters, and an overarching discussion section. Chapter One employs an agent-based computer model (RUSH-PNBM v.1.1) developed to study the potential impact of the trend toward increased producer specialization on resilience to catastrophic epidemics within livestock production chains. In each run, an infection is introduced and may spread according to probabilities associated with the various modes of contact between hog producer, feed mill, and slaughter plant agents. Experimental data reveal that more-specialized systems are vulnerable to outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outcomes; suggesting that reworking network structures may represent a viable means to increase biosecurity. Chapter Two uses a calibrated, spatially-explicit version of RUSH-PNBM (v.1.2) to model the hog production chains within three U.S. states. Key metrics are calculated after each run, some of which pertain to overall network structures, while others describe each actor’s positionality within the network. A genetic programming algorithm is then employed to search for mathematical relationships between multiple individual indicators that effectively predict each node’s vulnerability. This “meta-metric” approach could be applied to aid livestock epidemiologists in the targeting of biosecurity interventions and may also be useful to study a wide range of complex network phenomena. Chapter Three focuses on food insecurity resulting from the projected gap between global food supply and demand over the coming decades. While no single solution has been identified, scholars suggest that investments into multiple interventions may stack together to solve the problem. However, formulating an effective plan of action requires knowledge about the level of change resulting from a given investment into each wedge, the time before that effect unfolds, the expected baseline change, and the maximum possible level of change. This chapter details an evolutionary-computational algorithm to optimize investment schedules according to the twin goals of maximizing global food security and minimizing cost. Future work will involve parameterizing the model through an expert informant advisory process to develop the existing framework into a practicable food policy decision-support tool.

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The thesis deals with theme of social networks especially from the view of companies. The thesis is divided into two main parts -- theoretical and practical. There is a necessary knowledge base of social networks and its use from perspective of a company in the theoretical part. There is also mentioned the topic of social networks analytics because it's the main theme of the practical part of the thesis. The research in the practical part analyzes the companies from Czech Republic, Germany and United States of America. The research is aimed on their behavior on Facebook and their company presentations there. There are two methods used in the practical part. One method compares the list of companies during the time period of 3 year (90 days of 2011 compared to 90 days of 2014). The other one compares the list of companies from geographical point of view. The goal of the practical part of the thesis if evaluation of pre-defined hypotheses.

In der Netzwerkgesellschaft des 21. Jahrhunderts gilt die kollaborative Verteilung und Nutzung von Information und Wissen als Schlüsselstrategie für den webbasierten Informations- und Wissenstransfer. Durch die technologischen Möglichkeiten werden technische Zugangsbarrieren weitestgehend überwunden und traditionelle Formen der Wissensvermittlung durch moderne webbasierte Lernumgebungen ergänzt. Der Umgang mit kollaborativen Lehr- und Lernszenarien im dynamischen Informations- und Wissenstransfer bildet die Grundlage für den soziokulturellen Fortschritt innerhalb der Bildungsforschung. Der Schwerpunkt dieser Arbeit lag auf der strukturellen und relationalen Analyse sozialer Organisationsstrukturen innerhalb von Wissensnetzwerken. Ziel war es, Einflussfaktoren offenzulegen, die sich auf das Innovations- und Distributionspotential von Information und Wissen innerhalb von kollaborativen Wissensnetzwerken auswirken. Es wurden dazu Interaktionsprozesse von Teilnehmern innerhalb von Diskussionsforen am Beispiel der Lernplattform OPAL – dem aktuell populärsten Lernmanagementsystem in der Hochschulbildung Sachsens, Deutschland – untersucht. Unter der Annahme, dass soziale Interaktion besonders im Umgang mit kollaborativen Medien den Bildungsablauf und der Aufbau von Wissensnetzwerken die Lehr- und Lernprozesse beeinflusst, wurden in dieser Arbeit die strukturellen Bedingungen des kollaborativen Wissensnetzwerkes in OPAL exploriert und soziale Rollenkonstrukte relational identifiziert, um die Auswirkungen kollaborativer Aktivitäten auf den Informations- und Wissenstransfer in Wissensnetzwerken zu erklären. Es wurden vornehmlich beziehungsorientierte kommunikationstheoretische Modelle zugrunde gelegt und relationale Forschungsmethoden wie SNA (Social Network Analysis) und DNA (Dynamic Network Analysis) angewandt, um eine Basis für die weiterführende Implementierung sozial vernetzter Lehr- und Lernstrategien in der Bildungsforschung zu schaffen. […] / In the network society of the 21st century, a key strategy for web-based exchange of information and knowledge is their collaborative distribution and use. Technical hurdles of access are mostly being overcome with technological advances and traditional forms of passing on knowledge are being complemented by modern, e-learning environments. Within research into education, the foundation for socio-cultural progress is formed by involvement with collaborative teaching and learning scenarios in a dynamic exchange of information and knowledge. The emphasis of this work lay in the analysis of structures and relationships of social organisations within knowledge networks. The aim was to describe the exchange of information and knowledge in collaborative learning systems and to explore its influence on the potential for innovation and distribution of information and knowledge. A study was undertaken of the interaction of participants in discussion forums as exemplified by the learning platform OPAL – currently the most popular learning management system in secondary school education in Saxony, Germany. On the assumption that social interaction, particularly involving collaborative media, the progress of education and the construction of knowledge networks do influence teaching and learning processes, this work explored the structural conditions of OPAL's collaborative knowledge network and identified relationships between social role constructs in order to explain the effect of collaborative activities on the process of diffusion of information and knowledge in knowledge networks. Primarily the study was based on relationship oriented sociological models and communication theory models, and research methods for relationships, including SNA (Social Network Analysis) and DNA (Dynamic Network Analysis) were applied, so as to create a basis for further implementation of social network teaching and learning strategies in educational research. [...]

In der Netzwerkgesellschaft des 21. Jahrhunderts gilt die kollaborative Verteilung und Nutzung von Information und Wissen als Schlüsselstrategie für den webbasierten Informations- und Wissenstransfer. Durch die technologischen Möglichkeiten werden technische Zugangsbarrieren weitestgehend überwunden und traditionelle Formen der Wissensvermittlung durch moderne webbasierte Lernumgebungen ergänzt. Der Umgang mit kollaborativen Lehr- und Lernszenarien im dynamischen Informations- und Wissenstransfer bildet die Grundlage für den soziokulturellen Fortschritt innerhalb der Bildungsforschung. Der Schwerpunkt dieser Arbeit lag auf der strukturellen und relationalen Analyse sozialer Organisationsstrukturen innerhalb von Wissensnetzwerken. Ziel war es, Einflussfaktoren offenzulegen, die sich auf das Innovations- und Distributionspotential von Information und Wissen innerhalb von kollaborativen Wissensnetzwerken auswirken. Es wurden dazu Interaktionsprozesse von Teilnehmern innerhalb von Diskussionsforen am Beispiel der Lernplattform OPAL – dem aktuell populärsten Lernmanagementsystem in der Hochschulbildung Sachsens, Deutschland – untersucht. Unter der Annahme, dass soziale Interaktion besonders im Umgang mit kollaborativen Medien den Bildungsablauf und der Aufbau von Wissensnetzwerken die Lehr- und Lernprozesse beeinflusst, wurden in dieser Arbeit die strukturellen Bedingungen des kollaborativen Wissensnetzwerkes in OPAL exploriert und soziale Rollenkonstrukte relational identifiziert, um die Auswirkungen kollaborativer Aktivitäten auf den Informations- und Wissenstransfer in Wissensnetzwerken zu erklären. Es wurden vornehmlich beziehungsorientierte kommunikationstheoretische Modelle zugrunde gelegt und relationale Forschungsmethoden wie SNA (Social Network Analysis) und DNA (Dynamic Network Analysis) angewandt, um eine Basis für die weiterführende Implementierung sozial vernetzter Lehr- und Lernstrategien in der Bildungsforschung zu schaffen. […] / In the network society of the 21st century, a key strategy for web-based exchange of information and knowledge is their collaborative distribution and use. Technical hurdles of access are mostly being overcome with technological advances and traditional forms of passing on knowledge are being complemented by modern, e-learning environments. Within research into education, the foundation for socio-cultural progress is formed by involvement with collaborative teaching and learning scenarios in a dynamic exchange of information and knowledge. The emphasis of this work lay in the analysis of structures and relationships of social organisations within knowledge networks. The aim was to describe the exchange of information and knowledge in collaborative learning systems and to explore its influence on the potential for innovation and distribution of information and knowledge. A study was undertaken of the interaction of participants in discussion forums as exemplified by the learning platform OPAL – currently the most popular learning management system in secondary school education in Saxony, Germany. On the assumption that social interaction, particularly involving collaborative media, the progress of education and the construction of knowledge networks do influence teaching and learning processes, this work explored the structural conditions of OPAL's collaborative knowledge network and identified relationships between social role constructs in order to explain the effect of collaborative activities on the process of diffusion of information and knowledge in knowledge networks. Primarily the study was based on relationship oriented sociological models and communication theory models, and research methods for relationships, including SNA (Social Network Analysis) and DNA (Dynamic Network Analysis) were applied, so as to create a basis for further implementation of social network teaching and learning strategies in educational research. [...]