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- Genre: Academic theses
- Creators: Arizona State University
- Creators: Grebitus, Carola
Description
This thesis proposed a novel approach to establish the trust model in a social network scenario based on users' emails. Email is one of the most important social connections nowadays. By analyzing email exchange activities among users, a social network trust model can be established to judge the trust rate between each two users. The whole trust checking process is divided into two steps: local checking and remote checking. Local checking directly contacts the email server to calculate the trust rate based on user's own email communication history. Remote checking is a distributed computing process to get help from user's social network friends and built the trust rate together. The email-based trust model is built upon a cloud computing framework called MobiCloud. Inside MobiCloud, each user occupies a virtual machine which can directly communicate with others. Based on this feature, the distributed trust model is implemented as a combination of local analysis and remote analysis in the cloud. Experiment results show that the trust evaluation model can give accurate trust rate even in a small scale social network which does not have lots of social connections. With this trust model, the security in both social network services and email communication could be improved.
ContributorsZhong, Yunji (Author) / Huang, Dijiang (Thesis advisor) / Dasgupta, Partha (Committee member) / Syrotiuk, Violet (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis deals with the analysis of interpersonal communication dynamics in online social networks and social media. Our central hypothesis is that communication dynamics between individuals manifest themselves via three key aspects: the information that is the content of communication, the social engagement i.e. the sociological framework emergent of the communication process, and the channel i.e. the media via which communication takes place. Communication dynamics have been of interest to researchers from multi-faceted domains over the past several decades. However, today we are faced with several modern capabilities encompassing a host of social media websites. These sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information, our modes of social engagement, and mechanisms of how the media characteristics impact our interactional behavior. The outcomes of this research are manifold. We present our contributions in three parts, corresponding to the three key organizing ideas. First, we have observed that user context is key to characterizing communication between a pair of individuals. However interestingly, the probability of future communication seems to be more sensitive to the context compared to the delay, which appears to be rather habitual. Further, we observe that diffusion of social actions in a network can be indicative of future information cascades; that might be attributed to social influence or homophily depending on the nature of the social action. Second, we have observed that different modes of social engagement lead to evolution of groups that have considerable predictive capability in characterizing external-world temporal occurrences, such as stock market dynamics as well as collective political sentiments. Finally, characterization of communication on rich media sites have shown that conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Based on all these outcomes, we believe that this research can make significant contribution into a better understanding of how we communicate online and how it is redefining our collective sociological behavior.
ContributorsDe Choudhury, Munmun (Author) / Sundaram, Hari (Thesis advisor) / Candan, K. Selcuk (Committee member) / Liu, Huan (Committee member) / Watts, Duncan J. (Committee member) / Seligmann, Doree D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation explores the interrelationships between periods of rapid social change and regional-scale social identities. Using archaeological data from the Cibola region of the U.S. Southwest, I examine changes in the nature and scale of social identification across a period of demographic and social upheaval (A.D. 1150-1325) marked by a shift from dispersed hamlets, to clustered villages, and eventually, to a small number of large nucleated towns. This transformation in settlement organization entailed a fundamental reconfiguration of the relationships among households and communities across an area of over 45,000 km2. This study draws on contemporary social theory focused on political mobilization and social movements to investigate how changes in the process of social identification can influence the potential for such widespread and rapid transformations. This framework suggests that social identification can be divided into two primary modes; relational identification based on networks of interaction among individuals, and categorical identification based on active expressions of affiliation with social roles or groups to which one can belong. Importantly, trajectories of social transformations are closely tied to the interrelationships between these two modes of identification. This study has three components: Social transformation, indicated by rapid demographic and settlement transitions, is documented through settlement studies drawing on a massive, regional database including over 1,500 sites. Relational identities, indicated by networks of interaction, are documented through ceramic compositional analyses of over 2,100 potsherds, technological characterizations of over 2,000 utilitarian ceramic vessels, and the distributions of different types of domestic architectural features across the region. Categorical identities are documented through stylistic comparisons of a large sample of polychrome ceramic vessels and characterizations of public architectural spaces. Contrary to assumptions underlying traditional approaches to social identity in archaeology, this study demonstrates that relational and categorical identities are not necessarily coterminous. Importantly, however, the strongest patterns of relational connections prior to the period of social transformation in the Cibola region largely predict the scale and structure of changes associated with that transformation. This suggests that the social transformation in the Cibola region, despite occurring in a non-state setting, was governed by similar dynamics to well-documented contemporary examples.
ContributorsPeeples, Matthew A. (Author) / Kintigh, Keith W. (Thesis advisor) / Hegmon, Michelle (Thesis advisor) / Spielmann, Katherine A. (Committee member) / Arizona State University (Publisher)
Created2011
Description
In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints. Developing a framework to enable cooperative behavior adoption and to sustain it for a long period of time is a major challenge. As a part of developing this framework, I am focusing on methods to understand behavior diffusion over time. Facilitating behavior diffusion with resource constraints in a large population is qualitatively different from promoting cooperation in small groups. Previous work in social sciences has derived conditions for sustainable cooperative behavior in small homogeneous groups. However, how groups of individuals having resource constraint co-operate over extended periods of time is not well understood, and is the focus of my thesis. I develop models to analyze behavior diffusion over time through the lens of epidemic models with the condition that individuals have resource constraint. I introduce an epidemic model SVRS ( Susceptible-Volatile-Recovered-Susceptible) to accommodate multiple behavior adoption. I investigate the longitudinal effects of behavior diffusion by varying different properties of an individual such as resources,threshold and cost of behavior adoption. I also consider how behavior adoption of an individual varies with her knowledge of global adoption. I evaluate my models on several synthetic topologies like complete regular graph, preferential attachment and small-world and make some interesting observations. Periodic injection of early adopters can help in boosting the spread of behaviors and sustain it for a longer period of time. Also, behavior propagation for the classical epidemic model SIRS (Susceptible-Infected-Recovered-Susceptible) does not continue for an infinite period of time as per conventional wisdom. One interesting future direction is to investigate how behavior adoption is affected when number of individuals in a network changes. The affects on behavior adoption when availability of behavior changes with time can also be examined.
ContributorsDey, Anindita (Author) / Sundaram, Hari (Thesis advisor) / Turaga, Pavan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
In most social networking websites, users are allowed to perform interactive activities. One of the fundamental features that these sites provide is to connecting with users of their kind. On one hand, this activity makes online connections visible and tangible; on the other hand, it enables the exploration of our connections and the expansion of our social networks easier. The aggregation of people who share common interests forms social groups, which are fundamental parts of our social lives. Social behavioral analysis at a group level is an active research area and attracts many interests from the industry. Challenges of my work mainly arise from the scale and complexity of user generated behavioral data. The multiple types of interactions, highly dynamic nature of social networking and the volatile user behavior suggest that these data are complex and big in general. Effective and efficient approaches are required to analyze and interpret such data. My work provide effective channels to help connect the like-minded and, furthermore, understand user behavior at a group level. The contributions of this dissertation are in threefold: (1) proposing novel representation of collective tagging knowledge via tag networks; (2) proposing the new information spreader identification problem in egocentric soical networks; (3) defining group profiling as a systematic approach to understanding social groups. In sum, the research proposes novel concepts and approaches for connecting the like-minded, enables the understanding of user groups, and exposes interesting research opportunities.
ContributorsWang, Xufei (Author) / Liu, Huan (Thesis advisor) / Kambhampati, Subbarao (Committee member) / Sundaram, Hari (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews. I find that anonymous reviewers have a stronger effect on restaurant preference than peers. I also compare the power of negative reviews with that of positive reviews. I found that negative reviews are more powerful compared to the positive reviews on restaurant preference. More generally, I find that in an environment of high attribute uncertainty, information gained from anonymous experts through social media is likely to be more influential than information obtained from peers.
ContributorsTiwari, Ashutosh (Author) / Richards, Timothy J. (Thesis advisor) / Qiu, Yueming (Committee member) / Grebitus, Carola (Committee member) / Arizona State University (Publisher)
Created2013
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Although aggression is sometimes thought to be maladaptive, evolutionary theories of resource control and dominance posit that aggression may be used to gain and maintain high social prominence within the peer group. The success of using aggression to increase social prominence may depend on the form of aggression used (relational versus physical), the gender of the aggressor, and the prominence of the victim. Thus, the current study examined the associations between aggression and victimization and social prominence. In addition, the current study extended previous research by examining multiple forms of aggression and victimization and conceptualizing and measuring social prominence using social network analysis. Participants were 339 6th grade students from ethnically diverse backgrounds (50.4% girls). Participants completed a peer nomination measure assessing relational and physical aggression and victimization. They also nominated friends within their grade, which were used to calculate three indices of social prominence, using social network analysis. As expected, results indicated that relational aggression was associated with higher social prominence, particularly for girls, whereas physical aggression was less robustly associated with social prominence. Results for victimization were less clear, but suggested that, for girls, those at mid-levels of social prominence were most highly victimized. For boys, results indicated that those both high and low in prominence were most highly relationally victimized, and those at mid-levels of prominence were most highly physically victimized. These findings help inform intervention work focused on decreasing overall levels of aggressive behavior.
ContributorsAndrews, Naomi C. Z (Author) / Hanish, Laura D. (Thesis advisor) / Martin, Carol Lynn (Committee member) / Updegraff, Kimberly A (Committee member) / Arizona State University (Publisher)
Created2013
Description
With more than 70 percent of the world's population expected to live in cities by 2050, it behooves us to understand urban sustainability and improve the capacity of city planners and policymakers to achieve sustainable goals. Producing and linking knowledge to action is a key tenet of sustainability science. This dissertation examines how knowledge-action systems -- the networks of actors involved in the production, sharing and use of policy-relevant knowledge -- work in order to inform what capacities are necessary to effectively attain sustainable outcomes. Little is known about how knowledge-action systems work in cities and how they should be designed to address their complexity. I examined this question in the context of land use and green area governance in San Juan, Puerto Rico, where political conflict exists over extensive development, particularly over the city's remaining green areas. I developed and applied an interdisciplinary framework -- the Knowledge-Action System Analysis (KASA) Framework --that integrates concepts of social network analysis and knowledge co-production (i.e., epistemic cultures and boundary work). Implementation of the framework involved multiple methods --surveys, interviews, participant observations, and document--to gather and analyze quantitative and qualitative data. Results from the analysis revealed a diverse network of actors contributing different types of knowledge, thus showing a potential in governance for creativity and innovation. These capacities, however, are hindered by various political and cultural factors, such as: 1) breakdown in vertical knowledge flow between state, city, and local actors; 2) four divergent visions of San Juan's future emerging from distinct epistemic cultures; 3) extensive boundary work by multiple actors to separate knowledge and planning activities, and attain legitimacy and credibility in the process; 4) and hierarchies of knowledge where outside expertise (e.g., private planning and architectural firms) is privileged over others, thus reflecting competing knowledge systems in land use and green area planning in San Juan. I propose a set of criteria for building just and effective knowledge-action systems for cities, including: context and inclusiveness, adaptability and reflexivity, and polycentricity. In this way, this study also makes theoretical contributions to the knowledge systems literature specifically, and urban sustainability in general.
ContributorsMuñoz-Erickson, Tischa A (Author) / Larson, Kelli L. (Thesis advisor) / Redman, Charles L. (Thesis advisor) / Miller, Clark A. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Access control is one of the most fundamental security mechanisms used in the design and management of modern information systems. However, there still exists an open question on how formal access control models can be automatically analyzed and fully realized in secure system development. Furthermore, specifying and managing access control policies are often error-prone due to the lack of effective analysis mechanisms and tools. In this dissertation, I present an Assurance Management Framework (AMF) that is designed to cope with various assurance management requirements from both access control system development and policy-based computing. On one hand, the AMF framework facilitates comprehensive analysis and thorough realization of formal access control models in secure system development. I demonstrate how this method can be applied to build role-based access control systems by adopting the NIST/ANSI RBAC standard as an underlying security model. On the other hand, the AMF framework ensures the correctness of access control policies in policy-based computing through automated reasoning techniques and anomaly management mechanisms. A systematic method is presented to formulate XACML in Answer Set Programming (ASP) that allows users to leverage off-the-shelf ASP solvers for a variety of analysis services. In addition, I introduce a novel anomaly management mechanism, along with a grid-based visualization approach, which enables systematic and effective detection and resolution of policy anomalies. I further evaluate the AMF framework through modeling and analyzing multiparty access control in Online Social Networks (OSNs). A MultiParty Access Control (MPAC) model is formulated to capture the essence of multiparty authorization requirements in OSNs. In particular, I show how AMF can be applied to OSNs for identifying and resolving privacy conflicts, and representing and reasoning about MPAC model and policy. To demonstrate the feasibility of the proposed methodology, a suite of proof-of-concept prototype systems is implemented as well.
ContributorsHu, Hongxin (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Dasgupta, Partha (Committee member) / Ye, Nong (Committee member) / Arizona State University (Publisher)
Created2012