Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item VALUE IN THE EYE OF THE BEHOLDER: THE MODERATING EFFECTS OF MANAGERS’ SOCIAL NETWORKS ON THEIR IDEA VALUATION AND IMPLEMENTATION DECISION-MAKING(2019) Lu, Shuye; Bartol, Kathryn M; Venkataramani, Vijaya; Business and Management: Management & Organization; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Many of employees’ novel ideas often cannot get appreciated or valued by their managers, thus precluding the opportunity for innovation. Drawing on the social-information-processing theory and the situated evaluation perspective, this paper investigates the moderating roles of managers’ social networks in the innovation process of idea evaluation and implementation decision-making. Through a field study with 85 managers in a ceramic company, I found that when managers evaluated product ideas proposed by employees, they manifested a disfavor to novelty. That is, idea novelty had a negative relationship with managers’ perceived value of the focal idea regarding the idea’s potential operational efficiency, likelihood of social support, and strategic fit. However, I also found that both managers’ advice network diversity and friendship network centrality mitigated the negative effect of idea novelty on their perceived value of the proposed product ideas. In addition, I found managers’ perceived value of the idea mediated the relationship between idea novelty and their decisions to implement the idea. Theoretical contributions and empirical strategies are discussed.Item Joint Optimization for Social Content Delivery in Wireless Networks(2016) Weng, Xiangnan; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Over the last decade, success of social networks has significantly reshaped how people consume information. Recommendation of contents based on user profiles is well-received. However, as users become dominantly mobile, little is done to consider the impacts of the wireless environment, especially the capacity constraints and changing channel. In this dissertation, we investigate a centralized wireless content delivery system, aiming to optimize overall user experience given the capacity constraints of the wireless networks, by deciding what contents to deliver, when and how. We propose a scheduling framework that incorporates content-based reward and deliverability. Our approach utilizes the broadcast nature of wireless communication and social nature of content, by multicasting and precaching. Results indicate this novel joint optimization approach outperforms existing layered systems that separate recommendation and delivery, especially when the wireless network is operating at maximum capacity. Utilizing limited number of transmission modes, we significantly reduce the complexity of the optimization. We also introduce the design of a hybrid system to handle transmissions for both system recommended contents ('push') and active user requests ('pull'). Further, we extend the joint optimization framework to the wireless infrastructure with multiple base stations. The problem becomes much harder in that there are many more system configurations, including but not limited to power allocation and how resources are shared among the base stations ('out-of-band' in which base stations transmit with dedicated spectrum resources, thus no interference; and 'in-band' in which they share the spectrum and need to mitigate interference). We propose a scalable two-phase scheduling framework: 1) each base station obtains delivery decisions and resource allocation individually; 2) the system consolidates the decisions and allocations, reducing redundant transmissions. Additionally, if the social network applications could provide the predictions of how the social contents disseminate, the wireless networks could schedule the transmissions accordingly and significantly improve the dissemination performance by reducing the delivery delay. We propose a novel method utilizing: 1) hybrid systems to handle active disseminating requests; and 2) predictions of dissemination dynamics from the social network applications. This method could mitigate the performance degradation for content dissemination due to wireless delivery delay. Results indicate that our proposed system design is both efficient and easy to implement.Item Diffusion Dynamics in Interconnected Communities(2015) Wei, Xiaoya; Abed, Eyad H.; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation, multi-community-based Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Susceptible (SIS) models of infection/innovation diffusion are introduced for heterogeneous social networks in which agents are viewed as belonging to one of a finite number of communities. Agents are assumed to have well-mixed interactions within and between communities. The communities are connected through a backbone graph which defines an overall network structure for the models. The models are used to determine conditions for outbreak of an initial infection. The role of the strengths of the connections between communities in the development of an outbreak as well as long-term behavior of the diffusion is also studied. Percolation theory is brought to bear on these questions as an independent approach separate from the main dynamic multi-community modeling approach of the dissertation. Results obtained using both approaches are compared and found to be in agreement in the limit of infinitely large populations in all communities. Based on the proposed models, three classes of marketing problems are formulated and studied: referral marketing, seeding marketing and dynamic marketing. It is found that referral marketing can be optimized relatively easily because the associated optimization problem can be formulated as a convex optimization. Also, both seeding marketing and dynamic marketing are shown to enjoy a useful property, namely ``continuous monotone submodularity." Based on this property, a greedy heuristic is proposed which yields solutions with approximation ratio no less than 1-1/e. Also, dynamic marketing for SIS models is reformulated into an equivalent convex optimization to obtain an optimal solution. Both cost minimization and trade-off of cost and profit are analyzed. Next, the proposed modeling framework is applied to study competition of multiple companies in marketing of similar products. Marketing of two classes of such products are considered, namely marketing of durable consumer goods (DCG) and fast-moving consumer goods (FMCG). It is shown that an epsilon-equilibrium exists in the DCG marketing game and a pure Nash equilibrium exists in the FMCG marketing game. The Price of Anarchy (PoA) in both marketing games is found to be bounded by 2. Also, it is shown that any two Nash equilibria for the FMCG marketing game agree almost everywhere, and a distributed algorithm converging to the Nash equilibrium is designed for the FMCG marketing game. Finally, a preliminary investigation is carried out to explore possible concepts of network centrality for diffusions. In a diffusion process, the centrality of a node should reflect the influence that the node has on the network over time. Among the preliminary observations in this work, it is found that when an infection does not break out, diffusion centrality is closely related to Katz centrality; when an infection does break out, diffusion centrality is closely related to eigenvector centrality.Item PLACE AND CASTE IDENTIFICATION: DISTANCIATION AND SPATIAL IMAGINARIES ON A CASTE-BASED SOCIAL NETWORK(2014) Sam, Jillet Sarah; Ritzer, George; Sociology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis studies the potency of place in mobilizing social categories, and its implications for both social categories and places. I use the theory of distanciation to study associations between caste identity and place. I conducted an ethnographic study of a caste-based digital group, the Cyber Thiyyars of Malabar, to understand the connections and disconnections between the Thiyya caste and Malabar from the perspectives of different sets of actors involved in the identification of caste, namely the nation-state and members of this caste-based network. The nation-state knows the Thiyya caste in a manner that is disconnected from Malabar, while the Cyber Thiyyars of Malabar seek to re-emphasize the identification of this caste through the region. Participant observation and in-depth interviews indicate that through references to Malabar, the group seeks to establish a Thiyya caste identity that is distinct from the Ezhavas, a caste group within which the nation-state subsumes them. I demonstrate that references to Malabar serve to counter the stigma that the Cyber Thiyyars of Malabar experience when the spatially abstract categorization of the Thiyyas interacts with notions of caste inferiority/superiority. Further, it serves as a mobilizational tool through which they hope to negotiate with the nation-state for greater access to affirmative action. I also demonstrate that caste identification continues to be relevant to the production of place. Place-based identification of the Thiyyas influences the manner in which the group envisions the physical boundaries of Malabar and how other social groups can belong to this region. Based on this analysis, I argue that framework of distanciation should incorporate not only the experience of place and social relations, but also how they are known and represented. This dissertation establishes that even though social categories such as caste and place are not conventionally understood to be connected to each other, it is important to study the associations between them. Although the new media and globalization may prompt to us to think that place does not matter anymore, I establish that this caste group uses the language of place to organize and mobilize itself on a stronger basis in precisely this context.Item PREDICTION IN SOCIAL MEDIA FOR MONITORING AND RECOMMENDATION(2012) Wu, Shanchan; Raschid, Louiqa; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Social media including blogs and microblogs provide a rich window into user online activity. Monitoring social media datasets can be expensive due to the scale and inherent noise in such data streams. Monitoring and prediction can provide significant benefit for many applications including brand monitoring and making recommendations. Consider a focal topic and posts on multiple blog channels on this topic. Being able to target a few potentially influential blog channels which will contain relevant posts is valuable. Once these channels have been identified, a user can proactively join the conversation themselves to encourage positive word-of-mouth and to mitigate negative word-of-mouth. Links between different blog channels, and retweets and mentions between different microblog users, are a proxy of information flow and influence. When trying to monitor where information will flow and who will be influenced by a focal user, it is valuable to predict future links, retweets and mentions. Predictions of users who will post on a focal topic or who will be influenced by a focal user can yield valuable recommendations. In this thesis we address the problem of prediction in social media to select social media channels for monitoring and recommendation. Our analysis focuses on individual authors and linkers. We address a series of prediction problems including future author prediction problem and future link prediction problem in the blogosphere, as well as prediction in microblogs such as twitter. For the future author prediction in the blogosphere, where there are network properties and content properties, we develop prediction methods inspired by information retrieval approaches that use historical posts in the blog channel for prediction. We also train a ranking support vector machine (SVM) to solve the problem, considering both network properties and content properties. We identify a number of features which have impact on prediction accuracy. For the future link prediction in the blogosphere, we compare multiple link prediction methods, and show that our proposed solution which combines the network properties of the blog with content properties does better than methods which examine network properties or content properties in isolation. Most of the previous work has only looked at either one or the other. For the prediction in microblogs, where there are follower network, retweet network, and mention network, we propose a prediction model to utilize the hybrid network for prediction. In this model, we define a potential function that reflects the likelihood of a candidate user having a specific type of link to a focal user in the future and identify an optimization problem by the principle of maximum likelihood to determine the parameters in the model. We propose different approximate approaches based on the prediction model. Our approaches are demonstrated to outperform the baseline methods which only consider one network or utilize hybrid networks in a naive way. The prediction model can be applied to other similar problems where hybrid networks exist.Item USING AND MANIPULATING PROBABILISTIC CONNECTIVITY IN SOCIAL NETWORKS(2011) DuBois, Thomas M.; Srinivasan, Aravind; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Probabilistic connectivity problems arise naturally in many social networks. In particular the spread of an epidemic across a population and social trust inference motivate much of our work. We examine problems where some property, such as an infection or influence, starts from some initially seeded set of nodes and every affected node transmits the property to its neighbors with a probability determined by the connecting edge. Many problems in this area involve connectivity in a random- graph - the probability of a node being affected is the probability that there is a path to it in the random-graph from one of the seed nodes. We may wish to aid, disrupt, or simply monitor this connectivity. In our core applications, public health officials wish to minimize an epidemic's spread over a population, and connectivity in a social network suggests how closely tied its users are. In support of these and other applications, we study several combinatorial optimization problems on random-graphs. We derive algorithms and demonstrate their effectiveness through simulation, mathematical proof, or both.Item UTILIZING SOCIAL NETWORKS ANALYSIS IN THE CHARACTERIZATION OF AFRICAN UNGULATE SOCIAL STRUCTURE(2010) Carpenter, Leah Danielle; Ottinger, Mary Ann; Thompson, Katerina V; Behavior, Ecology, Evolution and Systematics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Social networks analysis tools were used to investigate the social structures of two African ungulate species. Captive herds of addra gazelle (Gazella dama) and roan antelope (Hipptragus equinus) were observed. Social networks were constructed of each herd's affiliative (socially cohesive) interactions and nearest-neighbor (closest individual within 2 body lengths) associations during three time periods. I evaluated whether network measures could be explained by individual, dyadic or sub-group attributes at three levels of social network organization. Both roan and addra males were very central to their networks, and in some time periods so were juveniles. Roan and addra partner preferences differed, with addra tending to affiliate by age class while roan were more variable in their partner preferences. Matrilinealy-related sub-groups were also identified in addra. This networks analysis approach has broad applicability for characterizing animal social organizations as well monitoring captive populations.Item Behavior Modeling and Forensics for Multimedia Social Networks(2009) Lin, Wan-Yi; Liu, K.J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Within the past decades, the explosive combination of multimedia signal processing, communications and networking technologies has facilitated the sharing of digital multimedia data and enabled pervasive digital media distribution over all kinds of networks. People involved in the sharing and distribution of multimedia contents form \emph{multimedia social networks} in which users share and exchange multimedia content, as well as other resources. Users in a multimedia social network have different objectives and influence each other's decision and performance. It is of ample importance to understand how users interact with and respond to each other and analyze the impact of human factors on multimedia systems. This thesis illustrates various aspects of issues and problems in multimedia social networks via two case studies of human behavior in multimedia fingerprinting and peer-to-peer live streaming. Since media security and content protection is a major issue in current multimedia systems, this thesis first studies the user dynamics of multimedia fingerprinting social networks. We investigate the side information which improves the traitor-tracing performance and provide the optimal strategies for both users (fingerprint detector and the colluders) in the multimedia fingerprinting social network. Furthermore, before a collusion being successfully mounted, the colluders must be stimulated to cooperate with each other and all colluders have to agree on the attack strategy. Therefore, not all types of collusion are possible. We reduce the possible collusion set by analyzing the incentives and bargaining behavior among colluders. We show that the optimal strategies designed based on human behavior can provide more information to the fingerprint detector and effectively improve the collusion resistance. The second part of this thesis focuses on understanding modelling and analyzing user dynamics for users in various types of peer-to-peer live streaming social networks. We stimulate user cooperation by designing the optimal, cheat-proof, and attack-resistant strategies for peer-to-peer live streaming social networks over Internet as well as wireless networks. Also, as more and more smart-phone users subscribe to the live-streaming service, a reasonable market price has to be set to prevent the users from reselling the live video. We start from analyzing the equilibrium between the users who want to resell the video and the potential buyers to provide the optimal price for the content owner.