Matching Items (165)
Description
The research on the topology and dynamics of complex networks is one of the most focused area in complex system science. The goals are to structure our understanding of the real-world social, economical, technological, and biological systems in the aspect of networks consisting a large number of interacting units and to develop corresponding detection, prediction, and control strategies. In this highly interdisciplinary field, my research mainly concentrates on universal estimation schemes, physical controllability, as well as mechanisms behind extreme events and cascading failure for complex networked systems.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
ContributorsChen, Yuzhong (Author) / Lai, Ying-Cheng (Thesis advisor) / Spanias, Andreas (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2016
Description
Perceptions of climate variability and change reflect local concerns and the actual impacts of climate phenomena on people's lives. Perceptions are the bases of people's decisions to act, and they determine what adaptive measures will be taken. But perceptions of climate may not always be aligned with scientific observations because they are influenced by socio-economic and ecological variables. To find sustainability solutions to climate-change challenges, researchers and policy makers need to understand people's perceptions so that they can account for likely responses. Being able to anticipate responses will increase decision-makers' capacities to create policies that support effective adaptation strategies. I analyzed Mexican maize farmers' perceptions of drought variability as a proxy for their perceptions of climate variability and change. I identified the factors that contribute to the perception of changing drought frequency among farmers in the states of Chiapas, Mexico, and Sinaloa. I conducted Chi-square tests and Logit regression analyses using data from a survey of 1092 maize-producing households in the three states. Results showed that indigenous identity, receipt of credits or loans, and maize-type planted were the variables that most strongly influenced perceptions of drought frequency. The results suggest that climate-adaptation policy will need to consider the social and institutional contexts of farmers' decision-making, as well as the agronomic options for smallholders in each state.
ContributorsRodríguez, Natalia (Author) / Eakin, Hallie (Thesis advisor) / Muneepeerakul, Rachata (Thesis advisor) / Manuel-Navarrete, David (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purpose of information source detection problem (or called rumor source detection) is to identify the source of information diffusion in networks based on available observations like the states of the nodes and the timestamps at which nodes adopted the information (or called infected). The solution of the problem can be used to answer a wide range of important questions in epidemiology, computer network security, etc. This dissertation studies the fundamental theory and the design of efficient and robust algorithms for the information source detection problem.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
ContributorsZhu, Kai (Author) / Ying, Lei (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Liu, Huan (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2015
Description
Conductance fluctuations associated with quantum transport through quantumdot systems are currently understood to depend on the nature of the corresponding classical dynamics, i.e., integrable or chaotic. There are a couple of interesting phenomena about conductance fluctuation and quantum tunneling related to geometrical shapes of graphene systems. Firstly, in graphene quantum-dot systems, when a magnetic field is present, as the Fermi energy or the magnetic flux is varied, both regular oscillations and random fluctuations in the conductance can occur, with alternating transitions between the two. Secondly, a scheme based on geometrical rotation of rectangular devices to effectively modulate the conductance fluctuations is presented. Thirdly, when graphene is placed on a substrate of heavy metal, Rashba spin-orbit interaction of substantial strength can occur. In an open system such as a quantum dot, the interaction can induce spin polarization. Finally, a problem using graphene systems with electron-electron interactions described by the Hubbard Hamiltonian in the setting of resonant tunneling is investigated.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
ContributorsYing, Lei (Author) / Lai, Ying-Cheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Chen, Tingyong (Committee member) / Yao, Yu (Committee member) / Arizona State University (Publisher)
Created2016
Description
This research investigates the dialectical relationships between water and social power. I analyze how the coupled processes of development, water privatization, and climate change have been shaping water struggles in Chile. I focus on how these hydro-struggles are reconfiguring everyday practices of water management at the community scale and the ways in which these dynamics may contribute to more democratic and sustainable modes of water governance at both regional and national scales. Using a historical-geographical and multi-sited ethnographical lens, I investigate how different geographical projects (forestry, irrigated agriculture, and hydropower) were deployed in the Biobio and Santiago regions of Chile during the last 200 hundred years. I analyze how since the 1970s, these hydro-modernization projects have been gradually privatized, which in turn has led to environmental degradation and water dispossession affecting peasants and other rural populations. I frame these transformations using the political-ecological notion of hydrosocial assemblages produced by the different stages of the hydro-modernity—Liberal, Keynesian, Socialist, Neoliberal. I detail how these stages have repeatedly reshaped Chilean hydrosocial processes. I unpack the stages through the analysis of forestry, irrigation and hydropower developments in the central and southern regions of Chile, emphasizing how they have produced both uneven socio-spatial development and growing hydrosocial metabolic rifts, particularly during neoliberal hydro-modernity (1981-2015). Hydrosocial metabolic rifts occur when people have been separated or dispossessed from direct access and control of their traditional water resources. I conclude by arguing that there is a need to overcome the current unsustainable market-led approach to water governance. I propose the notion of a 'commons hydro-modernity', which is based on growing environmental and water social movements that are promoting a socio-spatial project to reassemble Chilean hydrosocial metabolic relations in a more democratic and sustainable way.
ContributorsTorres Salinas, Robinson (Author) / Bolin, Bob (Thesis advisor) / Manuel-Navarrete, David (Committee member) / Larson, Kelli (Committee member) / Arizona State University (Publisher)
Created2016
Description
Public participation is considered an essential process for achieving sustainable urban development. Often, however, insufficient attention is paid to the design of public participation, and processes are formulaic. Then, participation may not match the local context of the communities within which a project is conducted. As a result, participation may become co-optative or coercive, stakeholders may lose trust, and outcomes may favor special interests or be unsustainable, among other shortcomings.
In this research, urban public participation is a collaborative decision-making process between residents, businesses, experts, public officials, and other stakeholders. When processes are not attuned with the local context (participant lifestyles, needs, interests, and capacities) misalignments between process and context arise around living conditions and personal circumstances, stakeholder trust, civic engagement, collaborative capacity, and sustainability literacy, among others.
This dissertation asks (1) what challenges arise when the public participation process does not match the local context, (2) what are key elements of public participation processes that are aligned with the local context, (3) what are ways to design public participation that align with specific local contexts, and (4) what societal qualities and conditions are necessary for meaningful participatory processes?
These questions are answered through four interrelated studies. Study 1 analyzes the current state of the problem by reviewing public participation processes and categorizing common misalignments with the local context. Study 2 envisions a future in which the problem is solved by identifying the features of well-aligned processes. Studies 3 and 4 test interventions for achieving the vision.
This dissertation presents a framework for analyzing the local context in urban development projects and designing public participation processes to meet this context. This work envisions public participation processes aligned with their local context, and it presents directives for designing deliberative decision-making processes for sustainable urban development. The dissertation applies a systems perspective to the social process of public participation, and it provides empirical support for theoretical debates on public participation while creating actionable knowledge for planners and practitioners.
In this research, urban public participation is a collaborative decision-making process between residents, businesses, experts, public officials, and other stakeholders. When processes are not attuned with the local context (participant lifestyles, needs, interests, and capacities) misalignments between process and context arise around living conditions and personal circumstances, stakeholder trust, civic engagement, collaborative capacity, and sustainability literacy, among others.
This dissertation asks (1) what challenges arise when the public participation process does not match the local context, (2) what are key elements of public participation processes that are aligned with the local context, (3) what are ways to design public participation that align with specific local contexts, and (4) what societal qualities and conditions are necessary for meaningful participatory processes?
These questions are answered through four interrelated studies. Study 1 analyzes the current state of the problem by reviewing public participation processes and categorizing common misalignments with the local context. Study 2 envisions a future in which the problem is solved by identifying the features of well-aligned processes. Studies 3 and 4 test interventions for achieving the vision.
This dissertation presents a framework for analyzing the local context in urban development projects and designing public participation processes to meet this context. This work envisions public participation processes aligned with their local context, and it presents directives for designing deliberative decision-making processes for sustainable urban development. The dissertation applies a systems perspective to the social process of public participation, and it provides empirical support for theoretical debates on public participation while creating actionable knowledge for planners and practitioners.
ContributorsCohen, Matthew Charles (Author) / Wiek, Arnim (Thesis advisor) / Manuel-Navarrete, David (Thesis advisor) / Schugurensky, Daniel, 1958- (Committee member) / Arizona State University (Publisher)
Created2015
Description
City governments are increasingly incorporating urban and peri-urban agriculture into their policies and programs, a trend seen as advancing sustainability, development, and food security. Urban governance can provide new opportunities for farmers, but it also creates structures to control their activities, lands, and purposes.
This study focused on Mexico City, which is celebrated for its agricultural traditions and policies. The study examined: 1) the functions of urban and peri-urban agriculture that the Government of Mexico City (GMC) manages and prioritizes; 2) how the GMC’s policies have framed farmers, and how that framing affects farmers’ identity and purpose; and 3) how the inclusion of agrarian activities and lands in the city’s climate-change adaptation plan has created opportunities and obstacles for farmers. Data was collected through participant observation of agricultural and conservation events, informal and semi-structured interviews with government and agrarian actors, and analysis of government documents and budgets.
Analysis of policy documents revealed that the GMC manages agriculture as an instrument for achieving urban objectives largely unrelated to food: to conserve the city’s watershed and provide environmental services. Current policies negatively frame peri-urban agriculture as unproductive and a source of environmental contamination, but associate urban agriculture with positive outcomes for development and sustainability. Peri-urban farmers have resisted this framing, asserting that the GMC inadequately supports farmers’ watershed conservation efforts, and lacks understanding of and concern for farmers’ needs and interests. The city’s climate plan implicitly considers farmers to be private providers of public adaptation benefits, but the plan’s programs do not sufficiently address the socioeconomic changes responsible for agriculture’s decline, and therefore may undermine the government’s climate adaptation objectives.
The findings illuminate the challenges for urban governance of agriculture. Farms do not become instruments for urban sustainability, development, and food security simply because the government creates policies for them. Urban governments will be more likely to achieve their goals for agriculture by being transparent about their objectives, honestly evaluating how well those objectives fit with farmers’ needs and interests, cultivating genuine partnerships with farmers, and appropriately compensating farmers for the public benefits they provide.
This study focused on Mexico City, which is celebrated for its agricultural traditions and policies. The study examined: 1) the functions of urban and peri-urban agriculture that the Government of Mexico City (GMC) manages and prioritizes; 2) how the GMC’s policies have framed farmers, and how that framing affects farmers’ identity and purpose; and 3) how the inclusion of agrarian activities and lands in the city’s climate-change adaptation plan has created opportunities and obstacles for farmers. Data was collected through participant observation of agricultural and conservation events, informal and semi-structured interviews with government and agrarian actors, and analysis of government documents and budgets.
Analysis of policy documents revealed that the GMC manages agriculture as an instrument for achieving urban objectives largely unrelated to food: to conserve the city’s watershed and provide environmental services. Current policies negatively frame peri-urban agriculture as unproductive and a source of environmental contamination, but associate urban agriculture with positive outcomes for development and sustainability. Peri-urban farmers have resisted this framing, asserting that the GMC inadequately supports farmers’ watershed conservation efforts, and lacks understanding of and concern for farmers’ needs and interests. The city’s climate plan implicitly considers farmers to be private providers of public adaptation benefits, but the plan’s programs do not sufficiently address the socioeconomic changes responsible for agriculture’s decline, and therefore may undermine the government’s climate adaptation objectives.
The findings illuminate the challenges for urban governance of agriculture. Farms do not become instruments for urban sustainability, development, and food security simply because the government creates policies for them. Urban governments will be more likely to achieve their goals for agriculture by being transparent about their objectives, honestly evaluating how well those objectives fit with farmers’ needs and interests, cultivating genuine partnerships with farmers, and appropriately compensating farmers for the public benefits they provide.
ContributorsBausch, Julia Christine (Author) / Eakin, Hallie C (Thesis advisor) / Lerner, Amy M (Committee member) / Manuel-Navarrete, David (Committee member) / Redman, Charles L. (Committee member) / Arizona State University (Publisher)
Created2017
Description
This dissertation treats a number of related problems in control and data analysis of complex networks.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
ContributorsWang, Lezhi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Papandreoou-Suppappola, Antonia (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
Studies of governance have focused on the interactions among diverse actors while implicitly recognizing the role of power within those relationships. Explicit power analyses of water governance coordination are needed to better understand the conditions for and barriers to sustainability. I therefore utilized a novel conceptual framework to analyze vertical and horizontal governance, along with power, to address how governance interactions affect water sustainability in terms of (1) interactions among governance actors across local to state levels; (2) coordination among actors at the local level; and (3) the exercise of power among assorted actors. I adopted a qualitative case study methodology that involved triangulating interview transcripts, policy documents, and other data in the case study area of Prescott, Arizona.
Across governance scales, my analysis found that informational and contentious interactions occur around water management plans, groundwater withdrawal fees, and growth debates due to the stipulations of Arizona’s Groundwater Management Act. Locally, municipalities in different groundwater basins coordinate by pooling resources for water development due to shared growth visions. However, municipalities within the same groundwater basin are divided in their pursuit of the state-mandated goal of safe yield due to discontent arising from differing growth visions, libertarian values of water control, and unequal responsibilities among actors in conserving water or monitoring use. Finally, local and state actors exercise power through litigation, legislation, and political processes to pursue their interests, thereby limiting coordination for water sustainability.
My explicit analysis of power reveals that coordination occurs not just because of water policies but due to interest-based water narratives (growth and libertarian). The emphasis of growth proponents on supply augmentation and libertarian opposition to regulations pose significant barriers to water sustainability. Successful policy-based pursuits of water sustainability will, thus, require an acknowledgment of these management asymmetries and commitments to addressing them.
Across governance scales, my analysis found that informational and contentious interactions occur around water management plans, groundwater withdrawal fees, and growth debates due to the stipulations of Arizona’s Groundwater Management Act. Locally, municipalities in different groundwater basins coordinate by pooling resources for water development due to shared growth visions. However, municipalities within the same groundwater basin are divided in their pursuit of the state-mandated goal of safe yield due to discontent arising from differing growth visions, libertarian values of water control, and unequal responsibilities among actors in conserving water or monitoring use. Finally, local and state actors exercise power through litigation, legislation, and political processes to pursue their interests, thereby limiting coordination for water sustainability.
My explicit analysis of power reveals that coordination occurs not just because of water policies but due to interest-based water narratives (growth and libertarian). The emphasis of growth proponents on supply augmentation and libertarian opposition to regulations pose significant barriers to water sustainability. Successful policy-based pursuits of water sustainability will, thus, require an acknowledgment of these management asymmetries and commitments to addressing them.
ContributorsAyodele, Deborah Olufunmilola (Author) / Larson, Kelli L (Thesis advisor) / Bolin, Robert (Committee member) / Manuel-Navarrete, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
Online social media is popular due to its real-time nature, extensive connectivity and a large user base. This motivates users to employ social media for seeking information by reaching out to their large number of social connections. Information seeking can manifest in the form of requests for personal and time-critical information or gathering perspectives on important issues. Social media platforms are not designed for resource seeking and experience large volumes of messages, leading to requests not being fulfilled satisfactorily. Designing frameworks to facilitate efficient information seeking in social media will help users to obtain appropriate assistance for their needs
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
ContributorsRanganath, Suhas (Author) / Liu, Huan (Thesis advisor) / Lai, Ying-Cheng (Thesis advisor) / Tong, Hanghang (Committee member) / Vaculin, Roman (Committee member) / Arizona State University (Publisher)
Created2017