Social media has created new protest spaces and has enabled people to do things differently. The focus of the research is on campaign groups, created before social media was used as a tool for protest. It has been undertaken to achieve the aim of the challenges and opportunities of incorporating new forms of social media into existing protest campaigns through a case study of anti-airport expansion groups in the UK. Social media data was obtained from three anti-airport expansion groups which included the extraction of approximately 9,000 tweets and 8,000 Facebook posts. The data were then analysed using social network analysis, time series analysis and semi-structured interviews. The results of social network analysis and time series analysis informed the development of the questions directed at the social media coordinators of each group. The main findings are that Airport Watch and HACAN Clearskies exhibit very similar Twitter networks and favour interaction with the media, similar anti-airport expansion groups and also pro-airport expansion groups. Transition Heathrow demonstrates more varied interaction patterns. All groups dominate their respective Facebook page and group networks apart from HACAN Clearskies which has non-assigned leaders controlling information dissemination in the group. Time series analysis uncovered variations in social media usage; overall for all three campaign groups Twitter was utilised more than Facebook.

abstract: In the artificial intelligence literature, three forms of reasoning are commonly employed to understand agent behavior: inductive, deductive, and abductive.  More recently, data-driven approaches leveraging ideas such as machine learning, data mining, and social network analysis have gained popularity. While data-driven variants of the aforementioned forms of reasoning have been applied separately, there is little work on how data-driven approaches across all three forms relate and lend themselves to practical applications. Given an agent behavior and the percept sequence, how one can identify a specific outcome such as the likeliest explanation? To address real-world problems, it is vital to understand the different types of reasonings which can lead to better data-driven inference.   This dissertation has laid the groundwork for studying these relationships and applying them to three real-world problems. In criminal modeling, inductive and deductive reasonings are applied to early prediction of violent criminal gang members. To address this problem the features derived from the co-arrestee social network as well as geographical and temporal features are leveraged. Then, a data-driven variant of geospatial abductive inference is studied in missing person problem to locate the missing person. Finally, induction and abduction reasonings are studied for identifying pathogenic accounts of a cascade in social networks. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

The National Park Service (NPS) strives to embody U.S. democratic ideals, conserving our collective stories and scenery for their intrinsic value and the enjoyment of current and future generations. However, although these places are conserved for all, they are not enjoyed by all. As with other conservation agencies, the NPS finds itself increasingly concerned with building relevance with diverse potential stewards. In cities, where 80% of the U.S. population and 40% of the NPS portfolio is based, there is a prime opportunity to build relevance with large, diverse, and proximate audiences. Recognizing this opportunity, the NPS initiated its Urban Agenda as a centerpiece of its 2016 centennial. The Urban Agenda seeks to connect people with proximate NPS parks and programs, primarily by using collaborations as pathways to relevance. In doing so, the agency may become a more resilient and value-added component of these larger landscapes. However, connections between relevance, resilience, and collaborations, especially at the organizational level, have rarely been addressed. This dissertation: 1) identifies perspectives on NPS relevance in the urban context; 2) examines the diversity of brokers and roles in facilitating relevance across collaborative networks; and 3) assesses areas of intra-NPS relationship-building for enhanced relevance. A multi-site, multi-methods evaluation was conducted. Detroit, Tucson, and Boston, all cities with Urban Agenda investment but representing different proximities to physical NPS parks, were selected as cases. Qualitative in-depth interviews with NPS staff and community partners were paired with quantitative social network analysis. The first phase of research identifies areas of commonality and difference among perceptions about relevance. Qualitative inquiry found that, across cities, NPS staff tended to conceptualize relevance in agency-focused ways while community partners conceptualized it on broader scales, both in audiences and goals. These differences in scale may be complementary, though, with the NPS further enhancing its relevance by recognizing the larger context and embedding its perspectives within this context. The second phase of research quantitatively examines collaborative network composition and potential, especially regarding network and broker diversity. Study results suggest that building the breadth and depth of a network, as well as targeting specific areas of desired growth, are ways to effectively build network resilience and further connections for relevance. The third phase of research examines relationships among parks, programs, and offices of the NPS. Combining qualitative and quantitative methods, this inquiry found that relationships between parks are most numerous and supported by institutional structures. However, connections to and within programs are a desired area for further connection. All relationship-building structures and language must emphasize the utility of internal connections for external relevance. Balancing relationship types while being inclusive of non-park groups may be essential in promoting organizational resilience and relevance. This evaluation contributes to theoretical understanding about and indicators of relevance and resilience. Together, results from these three phases of study can help the NPS understand specific relevance considerations in urban areas, efficiently use their resources to enhance relevance, and continue to strive toward our democratic ideals.

<p>The growing role of communication using computers in people’s everyday lives is reflected by the debates about massive multiplayer online role playing games (MMOs) like World of Warcraft and the Internet as a whole. While people may be driven by the same psychological drives that have spurred interaction between people in the past, this interaction is increasingly facilitated with the use of computer mediated communication (CMC). Can strong relations form between people that are separated by great distances in space using CMC? The presence of strong relations in MMOs could open the possibility for MMO communities to thrive.</p><p>A social network analysis of a MMO guild with 50 members was conducted using an online survey, which produced a non-response rate of 50 percent. Participants were asked about their age, the time they had spent in the guild and their gender in order to explain the social structure of the networks. They were then asked to state the strength of their relations with each of the other members of the guild on a scale from ―one, neutral‖ to ―five, strong friendship‖. The social network analysis program Pajek was used to investigate the characteristics of the social network using so called sociograms.</p><p>The essay concludes that numerous strong relations exist within the guild and that a long time spent in the guild increases the number of strong relations a guild member has. The results show that guilds may form the cohesive backbone of MMO communities and proposes that future research be conducted on the brokerage between guilds in MMO communities in order to produce a comprehensive view of the social structure of MMO communities.</p>

This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time. A social network is conceived as being a structure consisting of actors and their social interaction with each other. A common conceptualisation of social networks is to let the actors be represented by nodes in a graph with edges between pairs of nodes that are relationally tied to each other according to some definition. Statistical analysis of social networks is to a large extent concerned with modelling of these relational ties, which lends itself to empirical evaluation. The first paper deals with a family of statistical models for social networks called exponential random graphs that takes various structural features of the network into account. In general, the likelihood functions of exponential random graphs are only known up to a constant of proportionality. A procedure for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods is presented. The algorithm consists of two basic steps, one in which an ordinary Metropolis-Hastings up-dating step is used, and another in which an importance sampling scheme is used to calculate the acceptance probability of the Metropolis-Hastings step. In paper number two a method for modelling reports given by actors (or other informants) on their social interaction with others is investigated in a Bayesian framework. The model contains two basic ingredients: the unknown network structure and functions that link this unknown network structure to the reports given by the actors. These functions take the form of probit link functions. An intrinsic problem is that the model is not identified, meaning that there are combinations of values on the unknown structure and the parameters in the probit link functions that are observationally equivalent. Instead of using restrictions for achieving identification, it is proposed that the different observationally equivalent combinations of parameters and unknown structure be investigated a posteriori. Estimation of parameters is carried out using Gibbs sampling with a switching devise that enables transitions between posterior modal regions. The main goal of the procedures is to provide tools for comparisons of different model specifications. Papers 3 and 4, propose Bayesian methods for longitudinal social networks. The premise of the models investigated is that overall change in social networks occurs as a consequence of sequences of incremental changes. Models for the evolution of social networks using continuos-time Markov chains are meant to capture these dynamics. Paper 3 presents an MCMC algorithm for exploring the posteriors of parameters for such Markov chains. More specifically, the unobserved evolution of the network in-between observations is explicitly modelled thereby avoiding the need to deal with explicit formulas for the transition probabilities. This enables likelihood based parameter inference in a wider class of network evolution models than has been available before. Paper 4 builds on the proposed inference procedure of Paper 3 and demonstrates how to perform model selection for a class of network evolution models.

The growing role of communication using computers in people’s everyday lives is reflected by the debates about massive multiplayer online role playing games (MMOs) like World of Warcraft and the Internet as a whole. While people may be driven by the same psychological drives that have spurred interaction between people in the past, this interaction is increasingly facilitated with the use of computer mediated communication (CMC). Can strong relations form between people that are separated by great distances in space using CMC? The presence of strong relations in MMOs could open the possibility for MMO communities to thrive. A social network analysis of a MMO guild with 50 members was conducted using an online survey, which produced a non-response rate of 50 percent. Participants were asked about their age, the time they had spent in the guild and their gender in order to explain the social structure of the networks. They were then asked to state the strength of their relations with each of the other members of the guild on a scale from ―one, neutral‖ to ―five, strong friendship‖. The social network analysis program Pajek was used to investigate the characteristics of the social network using so called sociograms. The essay concludes that numerous strong relations exist within the guild and that a long time spent in the guild increases the number of strong relations a guild member has. The results show that guilds may form the cohesive backbone of MMO communities and proposes that future research be conducted on the brokerage between guilds in MMO communities in order to produce a comprehensive view of the social structure of MMO communities.

Diplomatic summits serve as critical opportunities for national leaders to interact and mobilize the political will needed to address the world’s greatest challenges. Yet, summits have a checkered past with both successes and failures. Consequently, summit diplomacy has been equated with highly publicized photo opportunities for heads of government and grandiose communiqués with vague commitments that are never fully realized. Due to concerns about their effectiveness, legitimacy, and representation, summits are in a period of transition. These trends and challenges are especially evident in the G8, and scholars have recognized that the G8 summit has evolved to include more actors than the past. Although acknowledged as a potential site of networked governance, empirical evidence of such activity is limited. Research has yet to identify the actors involved, the structures of the relationships, and the impact of networked approaches on the preparatory process. This research specifically explores the question of how a global level network affects the priorities adopted by the G8. Using the 2010 G8 Summit as a case to examine the increased prevalence of networked activity, this study focuses on the Summit’s signature initiative: maternal, newborn and child health (MNCH). MNCH is a longstanding global problem and despite efforts such as the Millennium Development Goals, poor health outcomes persist in regions throughout the world. But to understand the selection and shaping of MNCH as the signature initiative of the 2010 G8 Summit, a mixed method approach is used. Social network analysis provides a detailed description of the actors involved in networked governance in summit diplomacy for the G8, and the structure of their relationships with one another. Qualitative data analysis of 63 in depth interviews of network members illuminates the rich and varied perspectives of the participants, which yields insight about why and how actors engage each other in order to achieve individual and collective goals. The study demonstrated that networked governance contributed to the political prioritization and substantive policy content of summit agenda items, determined during the 2010 G8 Summit preparatory process. In the case of MNCH, while the network was found to include of a diverse range of state and non-state actors, a core group of bureaucratic, political, and NGO actors played a prominent role in the selection and shaping of the MNCH initiative. Yet, the role, values and contributions of actors within the network were contested by network members during the preparatory process, demonstrating that shared goals and norms were not a dominant feature of the network. Moreover, the networked governance process has not entirely escaped the confines of geographical boundaries, given the most central actors in the network met face-to-face on a regular basis and were located in close geographical proximity. Actors from regions where MNCH problems persist most severely remained marginalized in the networked approach. While financial capital is an essential ingredient for the MNCH programs and interventions proposed for the G8 initiative, social capital was a neglected factor that is critical for building the capacity to generate new ideas and solutions. Actors within the 2010 G8 preparatory network for MNCH adopted various strategies to build and mobilize social capital. Specifically, a group of Canadian-based NGOs and an international organization formed a coalition in order to strategically advance the MNCH issue on the summit agenda. Conversely, government actors did not invest in developing and mobilizing social capital. Ultimately, informal strategies proved more valuable for breaking down hierarchical barriers and exerting influence than formal processes designed by government. Networked governance was a key factor that contributed to the political prioritization and shaping of the MNCH signature initiative for the 2010 G8 Summit and increased the inclusiveness of the summit’s preparatory process. However, while important, networked governance was not sufficient to fully explain the final outcomes – other factors such as domestic and global political contexts and the characteristics of the MNCH issue influenced the process and outcomes. Moreover, G8 summit diplomacy moved beyond being solely a state-based process in the case of MNCH, but the presence of a network of interconnected actors did not equate to better problem-solving. Although scholars and practitioners agree that integrated horizontal and vertical approaches are required for addressing the complexity of MNCH challenges, the networked approach failed to enable a move beyond conventional solutions to address the systemic nature of MNCH challenges. The findings of the study have important implications for policy and governance processes, where widespread cooperation among a network of state and non-state actors will be required for resolving intractable global problems.

Searching the Web involves more than sifting through a huge graph of pages and hyperlinks. Specific collaboration networks have emerged that serve domain-specific queries better by exploiting the principles and patterns that apply there. We continue this trend by suggesting heuristics and algorithms to mine the evolution of collaboration networks, to discover interesting roles played by entities. The first section of the dissertation introduces the concept of nurturers using the computer science research community as a case study, while the second section formulates three roles - scouts, promoters and connectors, played by ratings in collaborative filtering systems. Nurturers: Nurturing, a pervasive mammalian trait, naturally extends to most association networks that involve humans. The increased availability of digital and online data about associations lets researchers experiment with algorithms to gain insight into such phenomena. Consider some examples of nurturing: • Slashdot endorsement. Slashdot was not the first site to link to Firefox, but the publicity Firefox received from this association surely helped it become popular quickly. The phenomenon of many small websites crashing due to publicity received through Slashdot has become well known as the Slashdot Effect. • A VC (Venture Capitalist) seed-funding a new startup. This event has a high nurturing value if the startup’s valuation increases rapidly after the funding. • A blogger writing about a topic. Kim Cameron has nurtured the “Laws of Identity” topic if it later becomes the buzz in blog circles. A nurturer need not always be the innovator or originator. The evangelist who adopts a prodigal idea and launches it on its way to success can also be a nurturer. • A professor guiding his student through the art of scientific research and bootstrapping him into a vibrant research community. New nodes not only emerge around these nurturers, but also become important in the network. Knowing nurturers is useful especially in vertical search, where algorithms exploit the structure of specialized collaboration networks to make search more relevant: knowing early adopters of good web pages can make web-search fresher; a list of VCs ranked by their nurturing value is useful to people with new startup ideas; the list of top nurturers in computer science is a valuable resource for a student seeking to do research. This dissertation presents a framework for discovering nurturers by mining the evolution of an association network, and discusses heuristics and customizations that can be applied through a case study: finding the Best Nurturers in Computer Science Research. Roles of Ratings in Collaborative Filtering: Recommender systems aggregate individual user ratings into predictions of products or services that might interest visitors. The quality of this aggregation process crucially affects user experience and hence the effectiveness of recommenders in e-commerce. The dissertation presents a novel study that disaggregates global recommender performance metrics into contributions made by each individual rating, allowing us to characterize the many roles played by ratings in nearest neighbor collaborative filtering. In particular, we formulate three roles - scouts, promoters, and connectors that capture how users receive recommendations, how items get recommended, and how ratings of these two types are themselves connected (respectively). These roles find direct uses in improving recommendations for users, in better targeting of items, and most impor -tantly, in helping monitor the health of the system as a whole. For instance, they can be used to track the evolution of neighborhoods, to identify rating subspaces that do not contribute (or contribute negatively) to system performance, to enumerate users who are in danger of leaving, and to assess the susceptibility of the System to attacks such as shilling. The three rating roles presented here provide broad primitives to manage a recommender system and its community.

Using social network analysis as a theoretical framework, the current study examined the associations between self-reported egocentric network characteristics and depression among a sample of United States college students. It is important to understand factors related to depression among this population due to the severity of its potential outcomes (e.g., suicide and interpersonal problems at school). Drawing inspiration from a recent study conducted by Christina Falci and Clea McNeely (2009), the current investigation used OLS regression to test for both linear and curvilinear relationships between egocentric network size and depression. Potential interactions between network size, density, and gender were also explored. As an additional line of inquiry, this project examined whether or not (and to what extent) perceptions of reciprocity mediate the relationships between network characteristics and depression. Data were collected using an online survey, which was proctored to students enrolled in three large undergraduate sociology courses during the fall 2010 semester. In contrast to findings reported by Falci and McNeely (2009), no significant relationships were observed between network characteristics and mental health. However, support reciprocity was found to be a significant predictor of depression at the multivariate level. Additional research will be necessary in order to confirm (or refute) the results of Falci and McNeely (2009) and to further assess the mediating effects of perceived equity.

Ecotourism from its genesis and founding theories has been set out to conserve and preserve the environment through sustainable operation that includes surrounding communities in efforts to reduce their poverty levels. Over the years ecotourism has been hypothesized to have departed from this ideal with several researchers, through social, qualitative analyses, have said that these non-sustainable ecotourism operations are simply due to poor management. This work sought to test this central hypothesis as a first approach to quantitatively linking ecotourism activities to management with surface water quality as the key indicator of sustainable ecotourism as a complex system through systems thinking. This pilot work was done by the use of two study sites in the Caribbean: Iwokrama, Guyana and Greencastle, Jamaica. From General Systems Theory, before systems dynamics can be applied there is a need to first observe components of the system in a reductionist view. This approach had to be taken also since the required data inputs for the systems approach were not available, as is the norm throughout the Caribbean. Thus by creating simple, easy-touse and transferrable sustainability indicator based reductionist-type assessment tools relevant data on ecotourism activities, management and water quality can be obtained in the future and acts as a start to understanding the true systems dynamics among these three entities. The creation of these quantitative reductionist tools utilized social surveying onsite, target plots, sustainability indicators and Social Network Analysis. Tools created were tested through what-if scenarios, with sensitivity analyses, and determined to be able to respond to societal, environmental and economic changes. The basic findings of these reductionist tools were used to establish and initial pathway for quantification inclusive of a framework in STELLA® for the numerical linking of ecotourism management, water quality and sustainability indicators in the Caribbean. This work also established water quality baselines for both study sites through in situ water sampling and testing and further ex situ analysis. As an indirect systems approach to linking sustainable development and the Caribbean, an audit of the Caribbean’s primary and secondary school’s system was conducted and recommendations suggested for the infusion of sustainability into formal education both during and after the United Nations Decade for Education for Sustainable Development (2005-2014).