abstract: Millions of users leave digital traces of their political engagements on social media platforms every day. Users form networks of interactions, produce textual content, like and share each others' content. This creates an invaluable opportunity to better understand the political engagements of internet users. In this proposal, I present three algorithmic solutions to three facets of online political networks; namely, detection of communities, antagonisms and the impact of certain types of accounts on political polarization. First, I develop a multi-view community detection algorithm to find politically pure communities. I find that word usage among other content types (i.e. hashtags, URLs) complement user interactions the best in accurately detecting communities. Second, I focus on detecting negative linkages between politically motivated social media users. Major social media platforms do not facilitate their users with built-in negative interaction options. However, many political network analysis tasks rely on not only positive but also negative linkages. Here, I present the SocLSFact framework to detect negative linkages among social media users. It utilizes three pieces of information; sentiment cues of textual interactions, positive interactions, and socially balanced triads. I evaluate the contribution of each three aspects in negative link detection performance on multiple tasks. Third, I propose an experimental setup that quantifies the polarization impact of automated accounts on Twitter retweet networks. I focus on a dataset of tragic Parkland shooting event and its aftermath. I show that when automated accounts are removed from the retweet network the network polarization decrease significantly, while a same number of accounts to the automated accounts are removed randomly the difference is not significant. I also find that prominent predictors of engagement of automatically generated content is not very different than what previous studies point out in general engaging content on social media. Last but not least, I identify accounts which self-disclose their automated nature in their profile by using expressions such as bot, chat-bot, or robot. I find that human engagement to self-disclosing accounts compared to non-disclosing automated accounts is much smaller. This observational finding can motivate further efforts into automated account detection research to prevent their unintended impact. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

Public rangelands are managed by a mixture of federal, state, and local governments. Often, these groups are charged with managing adjacent lands that are part of the same greater landscape. To do this effectively, communication and collaboration is required. This dissertation examines federal, state, and local agencies’ level of communication through three projects. The first project examined barriers to agencies adopting management tools from each other. I found that individuals within agencies were mainly staying within their own agency when seeking advice, so individuals were not communicating about tools or their findings across agencies. Furthermore, agency policies and fear of being sued restricted individuals’ ability to adopt management tools. The second project studied how land and wildlife managers in Southeastern Utah work together, or not, in managing mule deer populations that migrate to and from land managed by different agencies. I found that managers are working together to manage mule deer populations, but there are only a few individuals that tie everyone together. The third project looked at how federal, state, and local governments work together to rehabilitate lands after a wildfire that burned parts of Southwestern Idaho and Southeastern Oregon. I found that policy decisions at the federal level can heavily impact who works together and when. All three projects revealed that there are still barriers to federal, state, and local governments working together to manage the same landscape. However, the results from this dissertation also highlight opportunities for bridging the gap between agencies and, ultimately, improving management of rangelands.

Co-authorship networks are a particular sort of social networks representing authors collaborating on joint publications. Such networks are studied within the fields of bibliometrics and scientometrics. While it is possible to analyze co-authorship networks in their entirety, certain analytical tasks would benefit from representing such networks as dynamic graphs, which incorporate a temporal dimension and capture structural transformations unfolding over time. The importance of dynamic graphs has emerged in recent years, in graph theory at large as well as within application domains such as social sciences, for instance.Research regarding dynamic graphs has been identified as one of the major challenges within network theory since they are particularly useful for describing real-world systems.This thesis project revolves around dynamic co-authorship network analysis algorithms, which aim to extract various temporal aspects regarding author collaborations.It is the result of a proposal by the ISOVIS group at Linnaeus University, which is active within the fields of exploratory data analysis and information visualization, including the problem of visual analysis of scientific publication data. The algorithms developed in this project extract analytical data such as (1) joint publications among pairs of authors, (2) temporal trends on connected components (groups of authors) along with network centrality measurements, and (3) major events regarding emergence, mergers, and splits of connected components over time. Together with domain experts, the analysis regarding usability, performance, and scalability of the algorithms took place as part of the evaluation process to assure that the result met the needs which instigated this thesis project. The application of the algorithms on real data sets provided by the ISOVIS group was useful concerning the evaluation of the usability domain. In contrast, customized synthetic data sets was an excellent tool for evaluating performance and scalability.

This thesis addresses the relationship between institutions and foreign direct investments (FDI). While the issue of how institutions attract FDI (selection) is quite well-researched, the empirical evidence for institutions spreading through FDI (influence) is more ambiguous. We argue that past studies have neglected issues of endogeneity and interdependence in their modelling. We amend these issues by using a Stochastic Actor-Oriented network model which allows for interdependent and endogenous processes. The thesis also addresses the mechanisms governing the general relation between FDI and institutions and what these can tell us about institutional change and the process of globalisation. The model provides no evidence that FDI helps to spread institutions from home to host countries, but it does provide evidence that the selection effect can be an important dynamic between FDI and a certain set of institutions. Finally, we argue that FDI does not seem to be a contributory factor to institutional convergence.

Att skaffa arbete i ett nytt land kan inte vara enkelt, för människor med utländsk bakgrund som migrerat till Sverige består ofta de första åren av någon biståndsform. Det sociala nätverket är en viktig kanal för att komma ut i arbetslivet och med tanke på problematiken med att få arbete som människor med utländsk bakgrund utan nätverk har uppsatsen som syfte med denna att undersöka på vilket sätt nätverk har haft betydelse för individerna i arbetsmarknads etableringen som kommit till Sverige från Kosovo. Undersökningsfrågorna som kommer att besvaras under arbetet är på vilket sätt har nätverk påverkat människor med utländsk bakgrunders karriärval i Sverige? Och Vilka olika typer av socialt kapital har haft betydelse i arbetsmarknadsetablering? Syfte och frågeställningar grundar sig i Milnet, Migrants Labour Networks. Detta är ett nytt forskningsprojekt som undersöker vilka former av nätverk personer från forna Jugoslavien rör sig i.Uppsatsen tar utgångspunkt i begreppen socialt samt överbryggande och anknytande kapital av Bourdieu samt Hodkinson & Sparkes brytpunkter. Vidare bygger uppsatsen på en social nätverksanalys och innehållsanalys.Några av de centrala resultaten är att informanterna har genomgått olika brytpunkter och att dessa har påverkat deras karriär på olika vis, samt att våra informanter har ett anknytande socialt kapital och börjat utveckla ett överbryggande socialt kapital. / Obtaining a job in a foreign country is not an easy task. People who have immigrated to Sweden are often dependent on government support during the first year. Therefore, social networking is an important factor in becoming a part of society and settling into the work-life. Considering how difficult it is to get a job without any connections, we have decided to examine how the social network has played a role in the lives of individuals who have immigrated from Kosovo to Sweden. Further, we will discuss how it has affected them in the labor market. The inquiry questions that will be answered in this essay are: How have social networks affected those with foreign backgrounds with their career choices and which types of social capitals have played an important role in their work establishment? The purpose and the questions of the issue are based in Milnet, Migrants Labour Networks. This is a new research project which examines the different types of networks that individuals from Yugoslavia move in. The essay has its starting point in the concepts of social together with superstructure and relating capital of Bourdieu and Hodkinson & Sparkes. Further, this essay is based on social network analysis, as well as content analysis. Some of the main results are that the informants have undergone different inflection points and that these have affected their careers in various ways. Further, the results have shown that our informants have a relating social capital and have started to develop an overworked social capital.

Do Populist Radical Right Parties have an impact on the attitudes of other parties? Despite drawing much attention from the general public as well as academics, there is no clear answer to this conundrum. In this paper I examine how mainstream political parties change their positions in parliamentary debates on immigration and refugees after Populist Radical Right Parties enter parliament. In order to do this, I use theoretical concepts such as discourse coalitions and storylines in combination with network methodology to map out how parties in the Swedish parliament relate to one another through their attitudes towards key themes in the debate on immigration and refugees. This paper focuses on the relations between parties through language by applying Discourse Network Analysis on parliamentary debates. Thus, it contributes with a new relational aspect and methodological tool on a relatively underutilised material. The findings indicate that there is a change in other parties’ attitudes towards immigration and refugees, with two mainstream right parties moving closer to the Populist Radical Right Party. However, the datatype does not support causal language and the findings are limited due to small amounts of data.

abstract: This dissertation focuses on creating a pluralistic approach to understanding and measuring interdisciplinarity at various scales to further the study of the evolution of knowledge and innovation. Interdisciplinarity is considered an important research component and is closely linked to higher rates of innovation. If the goal is to create more innovative research, we must understand how interdisciplinarity operates. I begin by examining interdisciplinarity with a small scope, the research university. This study uses metadata to create co-authorship networks and examine how a change in university policies to increase interdisciplinarity can be successful. The New American University Initiative (NAUI) at Arizona State University (ASU) set forth the goal of making ASU a world hub for interdisciplinary research. This kind of interdisciplinarity is produced from a deliberate, engineered, reorganization of the individuals within the university and the knowledge they contain. By using a set of social network analysis measurements, I created an algorithm to measure the changes to the co-authorship networks that resulted from increased university support for interdisciplinary research. The second case study increases the scope of interdisciplinarity from individual universities to a single scientific discourse, the Anthropocene. The idea of the Anthropocene began as an idea about the need for a new geological epoch and underwent unsupervised interdisciplinary expansion due to climate change integrating itself into the core of the discourse. In contrast to the NAUI which was specifically engineered to increase interdisciplinarity, the I use keyword co-occurrence networks to measure how the Anthropocene discourse increases its interdisciplinarity through unsupervised expansion after climate change becomes a core keyword within the network and behaves as an anchor point for new disciplines to connect and join the discourse. The scope of interdisciplinarity increases again with the final case study about the field of evolutionary medicine. Evolutionary medicine is a case of engineered interdisciplinary integration between evolutionary biology and medicine. The primary goal of evolutionary medicine is to better understand "why we get sick" through the lens of evolutionary biology. This makes it an excellent candidate to understand large-scale interdisciplinarity. I show through multiple type of networks and metadata analyses that evolutionary medicine successfully integrates the concepts of evolutionary biology into medicine. By increasing our knowledge of interdisciplinarity at various scales and how it behaves in different initial conditions, we are better able to understand the elusive nature of innovation. Interdisciplinary can mean different things depending on how its defined. I show that a pluralistic approach to defining and measuring interdisciplinarity is not only appropriate but necessary if our goal is to increase interdisciplinarity, the frequency of innovations, and our understanding of the evolution of knowledge. / Dissertation/Thesis / Doctoral Dissertation Biology 2019

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Natural resources and rural livelihoods in Africa are under pressure due to climate change and ineffective management. It particularly affects countries where most of the population depends on natural resources for their livelihood, like Ethiopia. Even though, there is scientific and local knowledge on environmental management in the form of national strategies, stakeholders, and actions at multiple governance levels, it is lacking a proper interlinkage and public communication. This research aims to contribute to narrow gaps between knowledge systems and enhance adaptive capacity by understanding barriers and drivers for knowledge generation and management in climate change adaptation. The study interlinks political ecology and social theoretical concepts for climate change adaptation and knowledge management in a multi-level governance framework representing one country. Ethiopia is focused on in this study because it is and will be greatly affected by climate change and has elaborated a national strategy to become a climate resilient middle-income country by 2025. The governance levels are analyzed with (1) determining the institutional framework, stakeholders, and networks at national level, (2) analyzing the structure, role and capacity of the extension system, (3) investigating local capacities and thresholds for access and participation in knowledge and governance processes for natural resource management. A focus is put on (4) area closures, as an example for an applied and common intervention of natural resource management in Ethiopia, which can serve as contribution to cope with climate change consequences. In a final step (5) interlinkages and compatibility of the governance levels in Ethiopia are evaluated to draw conclusions for a generalization of obstacles and potentials. A two-level case study design was applied incorporating the national and local level of Ethiopia:Acknowledgements I Abstract III Zusammenfassung V Table of Content VII List of Abbreviations X List of Figures XII List of Tables XIV List of Appendices XV 1. Introduction 1 1.1. Social and Governance Limits to Climate Change Adaptation 1 1.2. Justification of the Study and Focus on Knowledge Management 3 1.3. Objectives and Structure of the Study 6 2. Theoretical Framework 9 2.1. State of Scientific Knowledge: Multi-Level Governance and Knowledge in Environmental Management in Africa 9 2.1.1. Multi-Level Governance for Environmental Management 9 2.1.2. Knowledge Systems and Social Dimensions in Climate Change Adaptation and Governance in Africa 11 2.1.3. Environmental Situation and Governance in Ethiopia 14 2.1.4. Area Closures for Climate Change Adaptation and Governance in Ethiopia 16 2.2. Conceptual Framework: Knowledge Management for Climate Change Adaptation in a Multi-Level Governance System 17 3. Methodology 19 3.1. Research Design and Concept 19 3.1.1. Multi-Level Case Study Design for Multi-Level Social Research 19 3.1.2. Description of the Case Study Country and Local Sites in Ethiopia 21 3.1.3. Research Matrix and Phases 23 3.2. Data Collection Methods & Materials 27 3.2.1. Secondary Literature and Data Review 27 3.2.2. Interviewing Techniques with Organizations 27 3.2.3. Community Survey 30 3.2.4. Observation 34 3.3. Data Analysis 35 3.3.1. Data base and processing 35 3.3.2. Qualitative Content Analysis 35 3.3.3. Statistical Evaluation 38 3.3.4. Social Network Analysis 38 3.4. Research Ethics and Limitations of the Study 40 4. Climate Change Adaptation at Country Level in Ethiopia 43 4.1. Legal Framework and Perceptions of Activities tackling Climate Change and Adaptation in Ethiopia 43 4.2. Organizational, Collaboration and Communication Structures 48 4.3. The Extension System: Function and Performance 57 4.4. Institutionalization and Perception of Area Closure Management 63 5. Knowledge Systems and Natural Resource Management at Local Level in Rural Ethiopia 67 5.1. Case Study I: Adami Tulu Jido Kombolcha Woreda, Oromia Region 67 5.1.1. Facts and Description of the Study Area 67 5.1.2. Climatic and Environment Change: Perceptions and Activities 72 5.1.3. Information, Communication, and Social Networks 76 5.1.4. Development and Extension Structure and Processes 84 5.1.5. Organizational Capacities and Collaboration Structures 90 5.1.6. Management and Performance of Area Closures 95 5.2. Case Study II: Wogera Woreda, Amhara Region 104 5.2.1. Facts and Description of the Study Area 104 5.2.2. Climatic and Environment Change: Perceptions and Activities 107 5.2.3. Information Access, Communication, and Social Networks 111 5.2.4. Development and Extension Structure and Processes 115 5.2.5. Organizational Capacities and Collaboration Structures 121 5.2.6. Management and Performance of Area Closures 126 5.3. Synopsis of the Local Case Studies 132 5.3.1. Comparative Analysis of the Woredas ATJK and Wogera 132 5.3.2. Conclusions on Structures and Conditions for Knowledge Generation and Management at Local Level 138 6. Synthesis: Knowledge Management for Climate Change Adaptation 143 6.1. (In)Compatibility of National Visions and Local Reality in Ethiopia 143 6.2. Future Pathways: Three Scenarios for Knowledge Management and Climate Change Adaptation in Ethiopia 146 6.2.1. Scenario I: Business-As-Usual 146 6.2.2. Scenario II: Collective Action at Community Level 148 6.2.3. Scenario III: Multi-Level Stakeholder Dialogue 150 6.2.4. Recommendations for Actions in Ethiopia 152 6.3. Framework of Multi-Level Governance for Strengthening Knowledge Management on Climate Change Adaptation 155 7. Conclusion 159 7.1. Lessons Learned 159 7.2. Methodological critique and suggestions for further research 160 References 161 Appendices 177