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Othman, SalemAutonomous Priority Based Routing for Online Social Networks
PHD, Kent State University, 2018, College of Arts and Sciences / Department of Computer Science
Social Routing in Online Social Networks (OSNs) is very challenging, as it must handle privacy and performance. This study proposes a Social Online Routing (SOR) protocol for OSNs that satisfies Stratified Privacy Model (SPM) core requirements and minimizes end-to-end routing delays corresponding to the social routing information elements exchanged under the SPM. SOR uses five messages (I-need Message, I-have Message, I-thank Message, I-like/dislike message, and the I-Ack Message) for carrying routing information. Forwarding models (I-need Module, I-have Module, I-thank Module, and I-ack Module) and routing algorithms (Topology aware Shortest-Path-Based routing algorithm, Social-Priority-Based routing algorithm, and Queue-aware Social-Priority-Based routing algorithm) are introduced. Four anonymization techniques are also utilized for stratified privacy. To evaluate the study’s proposed protocol, an Online Social Networks Simulator is designed and implemented. Using real datasets from Google Plus, the simulator is used to evaluate end-to-end routing delays corresponding to the social routing information elements exchanged under the SPM.

Committee:

Javed Khan, Prof. (Advisor)

Subjects:

Computer Science

Keywords:

Online social networks; Social Priority based Routing; SOR Protocol; Social routing and forwarding; Simulation; Social requests; Anonymization; Privacy leakage; Privacy Enhancing Technologies; Social based Routing; Request Dissemination; Human dynamics;

Kim, Dae WookData-Driven Network-Centric Threat Assessment
Doctor of Philosophy (PhD), Wright State University, 2017, Computer Science and Engineering PhD
As the Internet has grown increasingly popular as a communication and information sharing platform, it has given rise to two major types of Internet security threats related to two primary entities: end-users and network services. First, information leakages from networks can reveal sensitive information about end-users. Second, end-users systems can be compromised through attacks on network services, such as scanning-and-exploit attacks, spamming, drive-by downloads, and fake anti-virus software. Designing threat assessments to detect these threats is, therefore, of great importance, and a number of the detection systems have been proposed. However, these existing threat assessment systems face significant challenges in terms of i) behavioral diversity, ii) data heterogeneity, and iii) large data volume. To address the challenges of the two major threat types, this dissertation offers three unique contributions. First, we built a new system to identify network users via Domain Name System (DNS) traffic, which is one of the most important behavior-based tracking methods for addressing privacy threats. The goal of our system is to boost the effectiveness of existing user identification systems by designing effective fingerprint patterns based on semantically limited DNS queries that are missed by existing tracking efforts. Second, we built a novel system to detect fake anti-virus (AV) attacks, which represent an active trend in the distribution of Internet-based malware. Our system aims to boost the effectiveness of existing fake AV attack detection by detecting fake AV attacks in three challenging scenarios: i) fake AV webpages that require user interaction to install malware, instead of using malicious content to run automatic exploitation without users consent (e.g., shellcode); ii) fake AV webpages designed to impersonate real webpages using a few representative elements, such as the names and icons of anti-virus products from authentic anti-virus webpages; and iii) fake AV webpages that offer up-to-date solutions (e.g.,product versions and threat names) to emerging threats. Finally, we built a novel system to detect malicious online social network (OSN) accounts that participate in online promotion events. The goal of our work is to boost the effectiveness of existing detection methods, such as spammer detection and fraud detection. To achieve our goal, our framework that systematically integrates features that characterize malicious OSN accounts based on three of their characteristics: their general behaviors, their recharging patterns, and their currency usage, and then leverages statistical classifier for detection.

Committee:

Junjie Zhang, Ph.D. (Advisor); Adam Robert Bryant, Ph.D. (Committee Member); Bin Wang, Ph.D. (Committee Member); Xuetao Wei, Ph.D. (Committee Member)

Subjects:

Computer Science

Keywords:

network security; fake anti-virus software; intrusion detection; web document analysis; statistical classification; Domain Name System; behavioral fingerprints; privacy; online social networks; virtual currency; malicious accounts

Dreser, MelanieDesign, Fun and Sustainability: Utilizing Design Research Methods to Develop an Application to Inform and Motivate Students to Make Sustainable Consumer Choices
Master of Fine Arts, The Ohio State University, 2011, Industrial, Interior Visual Communication Design

Nowadays, when we talk about sustainability or environmentally friendly practices, we try to convince groups or individuals to be good citizens or good people. Especially young people do not care deeply about pursuing an environmentally conscious lifestyle if it requires an effort on their part.

What if one uses fun to influence (i.e., motivate and inform) students about sustainability in their daily life? Would this approach be more successful in changing their behavior? Can sustainability even be considered to be fun? As we already know, behavior change requires motivation and fun could be used as a motivational factor. Proposing that we need to develop programs and concepts that make a sustainable lifestyle fun instead of perceiving it as a negative influence on our quality of life provides new opportunities for projects and interventions.

When we make sustainable practices fun, the likelihood to adapt such a new behavior increases.

Behavioral change results from a combination of three factors, namely, awareness, information and motivation, which is the most important starting point for fun.

This thesis addresses the difficulties in informing and motivating students to choose a sustainable lifestyle by focusing on their consumer behavior. With a fun and playful application, the user should be able to learn and inform herself or himself about a sustainable lifestyle and be motivated to integrate it into her or his own daily life.

By offering multiple choices of action as well as the opportunity to be and act as a part of a whole group (i.e., collective action), competition and therefore motivation should be raised. This results from the idea that fun can be experienced both individually or as a group. Design Research is the main tool to develop this informational and motivational application. Research on the target group, in combination with existing case studies in design and the psychological aspects of human decision making, will lead to a design application. The resulting methodology could be used for any target group.

Committee:

Paul Nini, J (Committee Chair); Elizabeth Sanders, B.-N. (Committee Member); Carolina Gill (Committee Member)

Subjects:

Demographics; Design; Fine Arts; Sustainability; Systems Design

Keywords:

design; fun; sustainability; design research; participatory design; game; game mechanics; behavior change; Generation Y; sustainable lifestyle; human-centered; social networks; social media; co-design; motivation; information; awareness;

Ashida, SatoSocial network characteristics and intention to participate in social activity programs at a new senior center
Doctor of Philosophy, The Ohio State University, 2005, Public Health
Epidemiological studies have shown that socially integrated older adults live longer and healthier lives. Attempts have been made through organizations like senior centers to enhance social integration among older adults, but little is known about the impact of these efforts. This study investigated the characteristics of social networks among older adults living in community settings and whether these characteristics influence older adults’ intentions to participate in new social activities. A total of 126 face-to-face structured interviews were conducted with older adults between the ages of 65 and 85 living in an urban community in Columbus, OH. Addresses were randomly selected from all possible addresses in the area. Recruitment letters were sent by mail, with follow-up phone calls made when phone numbers were available. About 63.5% of the respondents were female, and 89.7% were White. The influence of social network characteristics, social support, companionship, and participation in productive activities on older adults’ intentions to participate in activities at a soon-to-open senior center was explored using hierarchical multiple linear regression. The results indicated a direct influence of social network characteristics on older adults’ intentions to participate in new activities, and some of the influence was mediated by functional features of social networks such as perceived support and companionship. Respondents who had smaller numbers of people in their networks and those with smaller proportions of network members who provided support had lower intentions to participate in new social activities, and thus should be targeted for intervention. It was also found that the construct of companionship and supportive relationship have independent associations with network characteristics and older adults’ intentions to participate in activities. Because the older adults who had lower perceived availability of companionship had higher levels of intention to participate, these individuals are likely to be recruited successfully and benefit by promoting companionship among them. Additional research is needed to investigate other possible mechanisms linking social networks and intentions to participate, such as social influence from network members.

Committee:

Catherine Heaney (Advisor)

Keywords:

Social Networks; Social Support; Older Adults

Suter, Deitra LThe Role of Religion in Predicting Recidivism: Considering Elements of Social Networking, Social Capital, and Social Learning Theories
Master of Arts (MA), Bowling Green State University, 2005, Sociology
The field of criminology has devoted little of its attention to religion, and even less to adult religiosity and its potential rehabilitative effect upon former inmates. This research combined aspects of social learning, social capital, and social networking theories to explain the ways in which religion can aid in reintegrating inmates into mainstream society. Learning theory is addressed in its more traditional differential association form, but instead of conceptualizing association as the root of criminality, association through religious institutions is conceptualized as a source of pro-social capital and legitimate social networks. These networks, and the sources of pro-social capital that they provide, allow former criminals the opportunity to undergo a “cognitive transformation” away from seeing themselves as “criminals” and towards viewing themselves as productive members of society. With this theoretical framework, religion was presented not as a conglomeration of morals and rituals, but rather as both a social phenomenon, in the Durkheimian sense, as well as a socializing mechanism by disseminating the “rules” of pro-social society. Binary logistic regression was conducted on an all male sample of criminal offenders surveyed initially when the respondents were incarcerated and subsequently three months and six years after their release. Successful reintegration into society was indexed by both self-reported and officially measured recidivism. The data showed that the social interaction and social networks provided via religious institutions were better predictors of recidivism than religious variables alone, controlling for traditional predictors of recidivism such as prior record, age, and race. The combination of religious background, legitimate networks, and acceptance from a religious group combined to be a significant moderate predictor of the likelihood of belonging to the recidivist group.

Committee:

Stephen Cernkovich (Advisor)

Subjects:

Sociology, Criminology and Penology

Keywords:

Recidivism; Religion; Social Networks; Social Capital; Reintegration

Wang, JingThe Role of Social Networks in the Success of Open Source Systems: A Theoretical Framework and an Empirical Investigation
PHD, Kent State University, 2007, College of Business Administration / Department of Management and Information Systems
Open Source Software (OSS) plays an increasingly important role in the social and economic development of countries, corporations, and individuals. Thus, it is important to understand the elements that affect OSS success. But, little is known on why certain projects succeed while others fail. Here, we draw on research in social network theory, and advance a conceptual model for project success in OSS systems. The current literature is dominated by a view that conceptualizes OSS projects as independent entities. This is inadequate in addressing issues related to the OSS, where each project is embedded in networks of relationships with other projects. Such relationship networks can be enduring and of strategic importance for OSS projects. We argue that the success of an OSS project can be more fully understood by adopting a network, rather than an independent, approach. Our model conceptualizes an OSS project as existing in a larger network of many related projects and identifies measurable network structures that are likely to distinguish successful OSS projects from less successful ones. We empirically evaluate the proposed model by analyzing panels of data from the world’s largest OSS development data repository, sourceforge.net.

Committee:

Murali Shanker (Advisor)

Subjects:

Business Administration, General

Keywords:

Open-source; Social Networks; Software Success

Srinivasan, Nikhil S.The Long-Tails in Content Services: How the Structure of Hybrid Networks Shape Content Popularity and Related Decision-Making
Doctor of Philosophy, Case Western Reserve University, 2013, Management Information and Decision Systems

This thesis examines the role that socio-technical networks that drive content popularity. Socio-technical networks are conceptualized as the infrastructure through which distributed individuals make and share cognition. This making and sharing of cognition through socio-technical networks results in an emergent distributed decision-making process. This emergent distributed decision-making process is embedded within the context of the socio-technical networks and consequently the structure of the networks influences it. The emergent distributed decision-making process influences the popularity of content. This thesis examines the question about which factors of socio-technical networks influence the popularity of content.

I explore this question through the use of a combination of a case study and quantitative field study. The multi-method approach allows us to use a combination of approaches to explore the static and dynamic factors that influence popularity of content embedded within socio-technical networks. I find that technical artifacts play an important role in the sharing of cognition within content networks and socio-technical networks structures influence both the popularity of content and the duration that content takes to emerge as popular.

This thesis has implications for both research and practice. It moves beyond an examination of the consequences and implications of long-tail behaviors to the structural characteristics that underlie such distributions. It also serves the knowledge management community by emphasizing the role of representational or classification systems in managing and disseminating knowledge. It adds to the IT literature by elaborating on the description of long tail characteristics of IT mediated networks. The implications for managers on the basis of this work are clear. Managers should focus on bridging large networks and making sure that participants in these networks have relationships with each other. While we might appreciate the phrase “let a thousand flowers bloom”, managers must not forget the forest for the trees. This work suggests that managers in addition to encouraging the growth of new ideas should also ensure that these ideas are disseminated as widely as possible through cohesive and connected networks.

Committee:

Kalle Lyytinen, PhD (Committee Chair); Youngjin Yoo, PhD (Committee Member); Fred Collopy, PhD (Committee Member); Samer Faraj, PhD (Committee Member); Jagdip Singh, PhD (Committee Member)

Subjects:

Information Systems

Keywords:

popularity; content; social networks; affiliation networks; tags

Edgar, PerezDeveloping a Resilient Network Ambidexterity Scale
Ph.D., Antioch University, 2018, Leadership and Change
The purpose of this study was to develop a resilient network ambidexterity scale. While numerous research efforts have considered the dimensions of social capital, resilience, and adaptive capacity to evaluate organizations and communities, few have explored social network indicators within organizations that can be used to mobilize ambidextrous strategies during times of disruption. The emphasis here was to understand the tendencies and behaviors that networks possess to sustain or achieve success along the parallel strategies of optimization and exploration. This study progressed in three specific phases toward filling this void in organizational development literature, using a mixed-methods approach. Phase 1 was the development of the item pool and analysis of the scale to establish face and content validity. Phase 2 included administering an online survey to 344 participants. Data collected were analyzed using exploratory factor analysis, followed by a partial confirmatory factor analysis These revealed a two-factor solution central to identifying resilient network ambidexterity: Optimizing Organizational Boundaries and Exploring Novelty. Phase 3 involved getting feedback on the revised scale from organizational leaders and practitioners working in innovative fields to refine the final RNA instrument. This research made connections between resilience and ambidexterity in organizations through ongoing inquiry on ways that fusing distinct paradigms impacts organizational outcomes. The development of this scale can serve as a useful tool for organizations to assess their level of resilience and mobilize the features of optimization and exploration. This dissertation is available in open access at AURA: Antioch University Repository and Archive, http://aura.antioch.edu/ and OhioLINK ETD Center, https://etd.ohiolink.edu/

Committee:

Mitchell Kusy, Ph.D. (Committee Chair); Donna Chrobot-Mason, Ph.D. (Committee Member); Elizabeth Holloway, Ph.D. (Committee Member)

Subjects:

Organization Theory; Organizational Behavior

Keywords:

Adaptive capacity, Ambidexterity, Mixed methods, Social networks, Social capital, Resilience, Scale development, Organizations

Young, Meghan AlyssaSocial Media Use and Happiness Among Adults 45 Years and Older
Master of Gerontological Studies, Miami University, 2018, Gerontology
Older adults are the fastest growing group to adopt and use social media. Social media allows individuals to remain socially connected when face-to-face contact becomes difficult. Previous research shows happiness may spread through face-to-face social networks. Since older adults may experience changes in their social networks over time, examining whether happiness is also related to online networks is important to understand. The purpose of this study was to examine the relationship between the use of multiple social media sites and happiness among n=870 adults age 45 years and older. Data from the 2016 wave of the General Social Survey was used to conduct cross-sectional binary logistic regression analyses. Fifty-six percent of participants used at least one social media site. Findings indicate the two predictor variables of interest (amount of time spent on the internet/web-enabled applications and number of social media sites used) had no significant relationship with happiness. Happiness was significantly related to number of children, marital status, total family income, and having a graduate degree. Future research in this area can develop new theories and explore how happiness is derived through a network by comparing an individual’s in-person and online network.

Committee:

Katherine Abbott, PhD (Committee Chair); J. Scott Brown, PhD (Committee Member); Sara McLaughlin, PhD (Committee Member)

Subjects:

Gerontology

Keywords:

aging; older adults; social media; internet use; social networks; happiness; subjective well-being

Hoffman, AnnaThe John Oliver Effect: Political Satire and Political Participation Through Social Networks
BA, Kent State University, 2015, College of Communication and Information / School of Communication Studies
Since the recent exit of John Stewart and Stephen Colbert from their shows that topped the genre of political satire (The Daily Show and The Colbert Report), little research has been done about the new shows primed to take their spot, including Last Week Tonight with John Oliver (LWT). LWT brings an interesting addition to the genre: its frequent social-media focused call to actions given at the end of longer, in-depth reporting segments. While political participation among the viewers of political satire has been researched before, the measures have focused on traditional forms of participation, rather than newer forms of participation via social media. These newer forms may better reflect participation patterns of the young adult population, which these shows have a large following from. Students from a large, Midwestern university received a video clip of a segment of LWT with or without the call to action (or no clip at all) using a between subjects experimental design. The results of this study suggest that shows like LWT can increase viewers’ intent to participate politically through social networks, even after viewing only a single clip. Results also suggest humor may play an important motivating role.

Committee:

Catherine Goodall, Dr. (Advisor); Richard Robyn, Dr. (Committee Member); J. D. Ponder, Dr. (Committee Member); Candace Bowen (Committee Member)

Subjects:

Communication; Journalism; Mass Communications; Mass Media; Political Science

Keywords:

political satire; politics; communication; Last Week Tonight with John Oliver; social networks; political participation; social media; The Daily Show; The Colbert Report; humor; comedy; journalism

Kim, SungminCommunity Detection in Directed Networks and its Application to Analysis of Social Networks
Doctor of Philosophy, The Ohio State University, 2014, Statistics
Community detection has been one of the central problems in network studies. Detecting communities in a directed network is particularly challenging due to the directionality in its links. In this thesis, we show that incorporating the direction of links reveals new perspectives on communities regarding to two different roles, source and terminal, that a node may play in a community. A novel concept of a community in a directed network, called directional community, is proposed, and its relation to a connectivity in directed networks and a quality measure of a community are investigated. Intriguingly, directional communities appear to be closely related to a unique spectral property of the graph Laplacian matrix and we exploit this connection using regularized SVD methods. We propose harvesting algorithms, coupled with the regularized SVDs, that are linearly scalable for efficient identification of directional communities in a massive directed network. In addition, we construct another class of algorithms that exploits the connectivity in directed networks and makes use of existing community detection algorithms intended for undirected networks. The proposed algorithms show remarkable performance and scalability on simulated benchmark networks and successfully recover communities in real network applications with more than millions of nodes. The actual running time of the algorithms for a network with a million links is less than an hour. The algorithms are applied to the task of analyzing community structures in massive social networks, which is of particular interest since a community in a social network reflects a group of users that demonstrates dense interactions within the group. Our proposed algorithms address two challenges in community detection in a large social network, 1) how to incorporate the directions of interactions, 2) how to search for communities in networks of millions of users. As an effort to obtain a social network with intrinsic community structures, the social interactions of sports fans, particularly of NCAA college football teams, are collected from a popular social media service, Twitter. The obtained social interaction network is a large directed network, which has about a half-million nodes and links. Proposed algorithms successfully identified the communities of the fans of each football team. In comparison to the existing community detection algorithms, our proposed methods successfully distinguish the two different roles of fans, celebrity types and supporters types.

Committee:

Tao Shi, Dr. (Advisor); Yoonkyong Lee, Dr. (Committee Member); Vince Vu, Dr. (Committee Member)

Subjects:

Statistics

Keywords:

Community extraction, Graph Laplacian, Regularized SVD, Scalable algorithm, Social networks

McLaughlin, Marc D.Developmental Assets in Urban Youths’ Mentoring Networks: Relationships with Important Adults
Doctor of Philosophy, Miami University, 2008, Psychology
This research involved the school-based, internet-administered assessment of external developmental assets among 197 urban ninth-grade students. Through a generalized survey and a series of daily-log surveys, students reported on the growth-enhancing resources and experiences – i.e., “external” assets – provided to them by the six “most important” adults in their lives. Four research questions were addressed: (1) Who are the important adults in urban early adolescents’ lives? (2) Do different types of adults provide assets differently? (3) What is the connection between external assets and youth outcomes? (4) What is the usefulness of this type of methodology and is it feasible? In regard to Question 1, youth nominated important adults who occupied a wide variety of relational roles, parents and other kin were prominently nominated as important adults, and most of the important adults in the six-adult networks were non-residential figures. Whereas girls were more likely to nominate important adults of their own gender, boys’ important adults were about equally likely to be female as male. In regard to Questions 2 and 4, analyses revealed substantial differences in both the patterns and intensity of asset provision between residential adults and non-residential adults. Also, biological/adoptive mothers differed from biological/adoptive fathers in the intensity and outcome-predictive potency of asset provision. Question 3 was addressed with analyses of the depth of asset provision by adults in the mentoring networks. Results of these analyses suggested that for a variety of assets the depth of provision significantly predicted youth outcomes. Questions 2 and 3 also were addressed with regression analyses on asset-factor scores, and results indicated that certain asset-factors combined to predict outcomes in multivariate models. In regard to Question 4, there was a trend for daily-log-based measures of asset-provision to predict outcomes better than generalized-survey-based measures, but differentials rarely were statistically significant. Findings also suggested that the methodology could be useful in developing normative daily-dosage correlates of the provision levels indicated on generalized-survey assessments, but that these correlates would be more accurately produced for residential, as opposed to non-residential, important adults. It was concluded that the methodology, overall, may be a useful and feasible approach for future, school-based applied asset research, given sufficient infrastructure for management and analysis of the data. Recommendations are made for further development of the method, and implications are discussed for applied research in schools and communities.

Committee:

Carl E. Paternite, PhD (Committee Chair); Karen M. Schilling, PhD (Committee Member); Paul D. Flaspohler, PhD (Committee Member); Patricia K. Kerig, PhD (Committee Member); Rose M. Ward, PhD (Committee Member); Keith J. Zullig, PhD (Committee Member)

Subjects:

Behaviorial Sciences; Gender; Personal Relationships; Psychology; School Administration; Social Work

Keywords:

developmental assets; external assets; adjustment; early adolescence; urban, African American youth; important adults; non-related adults; parent figures; kinship networks; social networks; support systems; mentoring/mentors; protective factors

Light, RyanPower, Inequality, and Resistance: Responses to Subordination in the American Slave Narrative, 1800-1930
Doctor of Philosophy, The Ohio State University, 2009, Sociology

Power is central to sociological discussions of inequality, but often remains in the background veiled by structural concerns and definitional ambiguities. This dissertation aims to center the discussion of power and inequality by focusing on how power is experienced and contested by the most vulnerable actors. Building on the case of American slavery, I turn to the voices of the enslaved themselves in one of the first sociological analyses exploring the rich and harrowing stories told by formerly enslaved narrators.

Slavery is defined by the enforced condition of natal alienation or the removal of all meaningful familial and community ties. This natal alienation contributes to the social death of the enslaved (Patterson 1982). I outline how natal alienation and social death fit into the wider discussion of inequality by tracing the recent genealogy of power within social theory from a one-dimensional view of raw physical and economic domination to more cultural and multidimensional conceptualizations. Despite the dominance endemic to slave systems, historical research grounded in the voices of the formerly enslaved emphasizes the everyday forms of resistance in which the enslaved engage; however, the everyday resistance frame remains contentious for at least two reasons: First, critics question the issue of intentionality – or the notion that subordinate actors are in “constant rebellion” (Tilly 1991:598). Second, scholars have challenged the material effect of everyday forms of resistance.

I rebuild the notion of everyday resistance through Bourdieu’s concept of an independent, but overlapping symbolic field. Symbolic contestation, to Bourdieu, is both connected to and separate from other fields, such as the economic and social. Actors struggle over symbolic resources with the tools available to them. I specify the location and content of these struggles by clarifying the centrality of micropractices of power in the maintenance of power relations and by briefly building upon theories of recognition and status. In addition to more structural and material constraints, inequality is perpetuated and contested through symbolic practices at a more proximate level. I specify a continuum for understanding the heterogeneity of subordinates’ responses, including those described by the formerly enslaved themselves.

To capture a holistic picture of the heterogeneity of subordinate response, I employ methods that facilitate casting a wide net to capture a diversity of subordinate actors’ voices. I use innovative tools developed in computational linguistics and the information sciences to systematically and formally analyze the 130 slave narratives published between 1800 and 1930 accumulated in this corpus. I specifically construct a word network map. This map reveals prominent clusters of words through their cumulative appearances in different narratives. I use the word network map as an index for qualitative exploration cross-referencing terms identified in the network with the narratives themselves.

Results indicate the presence of six emergent themes in the word network map: polemics, religion, reading and writing, crime and escape, everyday life, and the master-slave relationship. The word network map coupled with the qualitative analysis derived from it contributes to our understanding of American slavery in at least three ways. First, the network analysis reveals the centrality of the master-slave and everyday life clusters emphasizing their role in connecting themes to one another. Moreover, the everyday life cluster, identified as the primary location of symbolic struggle, is proximate to the master-slave cluster: physical violence and symbolic struggle are linked. Second, contrary to more monolithic constructions of resistance, qualitative analyses reveal the heterogeneity of responses to the enslaved condition as narrators describe quiescence, projective agency, everyday resistance, and more formal resistance to the primary conditions of natal alienation and social death. Third, we can also observe the extent to which the master class develops parallel symbolic strategies to maintain these conditions.

I conclude by situating the notion of social death in the broader context of a moral sociology of inequality. The broader struggle for recognition offers analytic direction for the future exploration of the role that symbolic struggles play in provoking societal change. I further highlight how the incorporation of text data through the increasingly more sophisticated analytic tools can open the door for large-scale analyses of hundreds of diverse actors’ voices. Recent theoretical and analytic developments promise a more complete picture of subordination and inequality, including but not limited to enslaved life, by using broad strokes to guide our detailed understanding of the heterogeneity of response to material and symbolic forms of subordination.

Committee:

Dr. Vincent Roscigno (Committee Chair); Dr. Pamela Paxton (Committee Member); Dr. Andrew Martin (Committee Member); Dr. James Moody (Committee Member)

Subjects:

African Americans; Black History; History; Social Research; Sociology

Keywords:

slave narratives; power; subordination; resistance; text analysis; social networks; cultural sociology; social inequality

Vedanarayanan, Srinivasa RaghavanAgents of Influence in Social Networks
MS, University of Cincinnati, 2012, Engineering and Applied Science: Computer Engineering
Influence propagation in social networks has been studied extensively in recent years, but in rather ad-hoc or simplistic frameworks. This thesis presents a multi-agent social network model where both the connectivity patterns and the interaction behaviors of agents are taken from a real-world network. Additionally, the agents modeled have plausible cognitive and social characteristics that determine the degree to which they can be influenced by other agents. The agents are classified into different classes based on their relative frequency of interaction with other neighboring agents. Opinions are injected into the system by agents of specific classes and their spread is tracked by propagating tags. The resulting data is used to analyze the influence of agents from each class in the viral spread of ideas under various conditions. The analysis also shows what behavioral factors, at the agent level, have the most significant impact on the spreading of ideas.

Committee:

Ali Minai, PhD (Committee Chair); Raj Bhatnagar, PhD (Committee Member); Karen Davis, PhD (Committee Member)

Subjects:

Computer Engineering

Keywords:

Agents of Influence;Social Networks;Idea Propagation;Influence;Probabilistic Model;Facebook;

Tan, EnhuaSpam Analysis and Detection for User Generated Content in Online Social Networks
Doctor of Philosophy, The Ohio State University, 2013, Computer Science and Engineering
Recent years have witnessed the success of a number of online social networks (OSNs) and explosive increasing of social media. These social networking and social media sites have attracted a significant number of participants that contribute various types of contents on the Internet, which are generally referred as user generated content (UGC). A well designed UGC network can utilize the wisdom of crowds to collect, organize, and vote user contributed content to generate high quality knowledge with a relatively low cost. However, the open environment of UGC system also makes it easy to be polluted and attacked by spammers and malicious users. How users participate in UGC networks, especially how users contribute content and share content with their friends and other users, is fundamental to spam detection and high quality knowledge discovery. In this dissertation, we investigate two important research issues: (1) discovering user content generation patterns in OSNs, focusing on publicly available content (knowledge sharing), and (2) detecting spam in user generated content based on our discovered patterns. With the access to three large OSN user activity logs, including Yahoo! Blogs, Yahoo! Answers, and Yahoo! Del.icio.us, for a duration of up to 4.5 years, we are able to well analyze the patterns of content generation patterns of social network users in detail. Our analysis consistently shows that users' posting behavior in these networks exhibits strong daily and weekly patterns, but the user active time in these OSNs does not follow commonly assumed exponential distributions. We also show that the user posting behavior in these OSNs follows stretched exponential distributions instead of widely accepted power law distributions. Our discovery lays a foundation for user behavior analysis in social networks, and serves as a ground truth for anomaly detection and anti-spam. Applying the user posting behavior distribution pattern, we further conducted a comprehensive analysis of spamming activities on a large commercial social blog UGC site in 325 days covering over 6 million posts and nearly 400 thousand users. Observing power law distribution instead of our discovered stretched exponential distribution on user contributions, we find it actually indicates serious UGC spam attack activities. Our analysis shows that UGC spammers exhibit unique non-textual patterns, such as posting activities, advertised spam link metrics, and spam hosting behaviors. Based on these non-textual features, we show with commonly used classification methods that a high detection rate could be achieved offline. These results further motivate us to develop a runtime scheme, BARS, to detect spam posts based on these spamming patterns. The experimental results demonstrate the effectiveness and robustness of BARS. To timely detect spam in large social network sites, it is desirable to discover self-tuned, unsupervised schemes that can save the training cost of supervised classification schemes. Identifying the limitations of existing unsupervised detection schemes due to assumptions of spammer behaviors that no longer hold, we design an unsupervised spam detection scheme, called UNIK. Instead of picking out spammers directly, UNIK leverages both the connection-based social graph and the content-based user-link graph to remove non-spammers from the network first, and then clusters spammers with the landing pages they are trying to advertise. Based on highly accurate detection results of UNIK, we further analyze a number of spam campaigns. The result shows that different spammer clusters demonstrate distinct characteristics, implying the ability of UNIK to automatically extract spam signatures.

Committee:

Xiaodong Zhang (Advisor); Feng Qin (Committee Member); Ten H. (Steve) Lai (Committee Member)

Subjects:

Computer Engineering; Computer Science

Keywords:

user generated content; online social networks; user behavior; stretched exponential distribution; spam filtering; spam detection; spam classification; decision tree; social graph; user-link graph; Sybil attack; community detection; BARS; UNIK

McMahon, Eileen MarieProfessionalism in teaching: an individual level measure for a structural theory
Doctor of Philosophy, The Ohio State University, 2007, Educational Policy and Leadership
Although much has been written about such important topics as teacher quality and professionalism, few discussions of these concepts draw upon theoretically integrated and empirically grounded formulations of professionalism in teaching. Most considerations of professionalism focus on individual-level characteristics rather than on properties of the organizations that contextualize the actual work of teaching. This exploratory study seeks to establish a theoretically grounded construct of teacher professionalism that can be validly and reliably measured. Both qualitative and quantitative data were collected from two dissimilar Midwestern high schools for the purposes of this exploration. Findings validated an individual level measure of teacher professionalism, and established its usability in future research of the construct at the organizational level.

Committee:

Wayne Hoy (Advisor)

Subjects:

Education, Administration

Keywords:

professionalism; teaching; high school; social networks; mixed methods research

Rawashdeh, AhmadSemantic Similarity of Node Profiles in Social Networks
PhD, University of Cincinnati, 2015, Engineering and Applied Science: Computer Science and Engineering
It can be said, without exaggeration, that social networks have taken a large segment of population by a storm. Regardless of the actual geographical location, of socio-economic status, as long as access to an internet connected computer is available, a person has access to the whole world, and to a multitude of social networks. By being able to share, comment, and post on various social networks sites, a user of social networks becomes a "citizen of the world", ensuring presence across boundaries (be they geographic, or socio-economic boundaries). At the same time social networks have brought forward many issues interesting from computing point of view. One of these issue is that of evaluating similarity between nodes/profiles in a social network. Such evaluation is not only interesting, but important, as the similarity underlies the formation of communities (in real life or on the web), of acquisition of friends (in real life and on the web). In this thesis, several methods for finding similarity, including semantic similarity, are investigated, and a new approach, Wordnet-Cosine similarity is proposed. The Wordnet-Cosine similarity (and associated distance measure) combines both a lexical database, Wordnet, with Cosine similarity (from information retrieval) to find possible similar profiles in a network. In order to assess the performance of Wordnet-Cosine similarity measure, two experiments have been conducted. The first experiment illustrates the use for Wordnet-Cosine similarity in community formation. Communities are considered to be clusters of profiles. The results of using Wordnet-Cosine are compared with those using four other similarity measures (also described in this thesis). In the second set of experiments, Wordnet-Cosine was applied to the problem of link prediction. Its performance of predicting links in a random social graph was compared with a random link predictor and was found to achieve better accuracy.

Committee:

Anca Ralescu, Ph.D. (Committee Chair); Irene Diaz, Ph.D. (Committee Member); Rehab M. Duwairi, Ph.D. (Committee Member); Kenneth Berman, Ph.D. (Committee Member); Chia Han, Ph.D. (Committee Member); Dan Ralescu, Ph.D. (Committee Member)

Subjects:

Computer Science

Keywords:

Social Networks;Wordnet;Semantic;Machine Learning;Link Prediction

Afsahi, AfshanSocial Networking Dilemmas for Psychologists: Privacy, Professionalism, Boundary Issues, and Policies
Psy. D., Antioch University, 2015, Antioch New England: Clinical Psychology
Technological advancements have had positive and negative effects on the clinical practice of psychology. Increasing use of social networking websites has created new ethical issues concerning privacy and confidentiality, professionalism, and therapeutic boundaries. Due to the ever-changing nature of social media, there are no clear practice rules or guidelines set by the American Psychological Association (APA) for psychologists’ use of the Internet and social networks. This research took a closer look at psychology graduate students and psychologists’ use of privacy settings; their awareness, beliefs, and practices as they relate to their own and others’ online behaviors; their preparedness to have discussions with their clients about how they handle online “friend requests;” whether they are more likely to engage in online behaviors if they work with a younger population; and whether or not psychologists have developed their own ethical professional policy or they believe the APA should implement policies regarding psychologists’ use of social network. A total of 486 individuals visited the website for the survey and 445 participants completed the survey. Of the 445 participants, 22% (99) were male and 78% (346) were female. The mean age of participants in this study was 37.13, with ages ranging from 21 to 72. Approximately 86% (383) of participants reported that they maintain a personal profile on a social networking website, and 14% (61) of participants reported that they do not maintain a personal profile. This research seeks to inform better use of social networking websites such as Facebook by psychologists through an online survey.

Committee:

Roger L. Peterson, PhD, ABPP (Committee Chair); Susan Hawes, PhD (Committee Member); David Hamolsky, PsyD (Committee Member)

Subjects:

Clinical Psychology

Keywords:

privacy; professionalism; therapeutic boundaries; policies; social networks

Holeva, Paul D.Growing Social Capital: Investigating the Relationship between Farmers' Markets and the Development of Community Support Networks in Ann Arbor, MI
Master of Arts, Miami University, 2009, Geography
Since the 1950's each generation of American citizen has engaged in less social interaction than the generation before, leading to a decline in social capital that has been, and continues to be, a contributing factor in the decline of the American City. In an effort to combat these declines this project utilized primary survey, informal interview, and participant observation methodologies to explore the potential development of urban public farmers' markets as an institutional space designed to encourage diverse social interaction, and therefore social capital, at the local level. While survey and interview results showed that market patrons are more apt to engage new individuals within the market space rather than nonfunctional public spaces, demographic and interview data suggests that social pressures and local government regulations limit the diversity of the public, restrict political action, and limit the spatial extent of social capital networks developed within the market space. While these constraints currently prevent the market from reaching its full potential as a social capital development tool, the data also suggests that the market space does serve a major role in the development of local community support networks and that the restructuring of market policies could allow for a more inclusive public to benefit from the market's social networking capability.

Committee:

Dr. Bruce D'Arcus, PhD (Advisor); Dr. David Prytherch, PhD (Committee Member); Dr. Marcia England, PhD (Committee Member)

Subjects:

Geography; Social Research; Urban Planning

Keywords:

social capital; public space; community development; social networks

Yoon, Dong-YeolThe relationships among the extent of participant involvement in cross-cultural learning activities, individual differences of participants, and adaptation of expatriate managers to the host country in a Korean multinational corporation
Doctor of Philosophy, The Ohio State University, 2011, EDU Physical Activity and Educational Services
The purpose of this study is to investigate the relationships among the extent of participant involvement in cross-cultural learning activities, individual differences of participants, and adaptation of expatriate managers to the host country in a Korean multinational corporation. Correlational research was used to investigate the relationships among the above variables. This study is ex post facto in nature. The treatment, cross-cultural learning activities, had already occurred, and expatriate managers self-reported their degrees of adaptation. The data for the quantitative research were collected from an online survey questionnaire. The potential respondents for this study were expatriate managers of a global manufacturing corporation. The total number of respondents was 136 (40.12%) out of 339 randomly selected employees who were working as expatriates in the overseas subsidiaries at the time of the survey. The survey data was analyzed with the PASW Statistic 18. Both descriptive and correlational statistics were used according to the nature of the research questions. This study provides implications for future research and practices in CCL and HRD.

Committee:

Ronald Jacobs (Advisor); Joshua Hawley (Committee Member); Shad Morris (Committee Member)

Subjects:

Adult Education; Business Administration; Business Education; Education

Keywords:

Cross-cultural learning (CCL); workplace learning; expatriate adaptation; human resource development (HRD); social networks; cross-cultural training (CCT)

Sokhey, Anand EdwardMotivation and the Social Information Search
Doctor of Philosophy, The Ohio State University, 2009, Political Science

Despite its many contributions, the current generation of network research has left the intricacies and assumptions of interpersonal political communication empirically under-examined; this has left us with a limited understanding of how voters actually experience campaigns through their micro-environments, and of how individuals use their networks to acquire and process political information. The goal of this dissertation is to tackle these problems through new approaches to measurement, design, and theory. Triangulating on the results from multiple original survey data sources, it provides fresh insights into every-day political talk and new considerations of old assumptions, all while addressing questions grounded in traditional approaches to the study of elections and political behavior.

Chapter 1 serves as an overview, outlining the major challenges facing scholars studying social influence and introducing the data sets used throughout the remainder of the project. Chapter 2 investigates the content of everyday political discussion, unveiling new measures designed to capture the diversity and quality of the information being carried in citizens’ networks. A matching analysis is performed, and the results suggest that exposure to diverse (“complete”) discussion has causal effects, reducing voters’ levels of attitudinal ambivalence over the course of a presidential campaign.

Chapter 3 addresses two key questions plaguing the social influence literature: what factors motivate individuals to use their networks, and when does social influence play a greater role in political decision-making? Using new measures designed to tap the ways in which individuals allocate discussion among their core discussants, the results suggest that individuals care about maintaining harmonious relationships but are more concerned with seeking out knowledgeable discussants. The results from the second portion of the chapter indicate that social influence plays a larger role in voters’ decisional calculi under the conditions of a primary election, where the dominant cue of partisanship is largely absent.

The last two chapters build upon the notions of conversational content and network usage introduced in the first half of the dissertation, while pursuing a series of more specific questions related to elections and political behavior. Chapter 4 investigates the role that social support plays in shaping perceptions of candidate electability, investigating the determinants of “wish fulfillment” – i.e., the over-estimation of a candidate’s chances of winning; Chapter 5 considers the use and consequences of networks in the wake of a major (motivating) political event, focusing on the case of a divisive primary. Finally, Chapter 6 provides a review of the major findings in the dissertation, particularly its contributions with respect to how networks handle the content of campaigns, vary over time in response to electoral developments, and function in lower-salience contests. The concluding chapter also notes the limitations of the current effort and discusses several avenues of future research.

Committee:

Paul Beck (Committee Chair); Janet Box-Steffensmeier (Committee Member); Herb Weisberg (Committee Member)

Subjects:

Political Science

Keywords:

social networks; voting behavior; primary elections; political participation

Vatev, Kiril MTime to Check the Tweets: Harnessing Twitter as a Location-indexed Source of Big Geodata
Master of Arts, The Ohio State University, 2013, Geography
Twitter, a popular online social network based on the microblogging format, is an important and significant source of both locational and archival data. It lends to a wide range of topics, from predicting the results of political elections, analysis of natural disasters, and tracking of disease epidemics, to studying political movements and protests, notably in cases of protest organization in Moldova and Iran, and recent events in the Arab Spring. However, many obstacles and barriers to entry are posed by Twitter’s system. Twitter has two main ways of obtaining data with different API requirements, and both returning different formats of data. System-wide authentication further complicates the data collection process. This research is based in creating an open-source software package to overcome the difficulties and barriers to obtaining a Twitter dataset, for both programming aficionados and those only interested in the data. The goals of the software are to ease the collection, storage, and future access to those interesting and important datasets. The resulting software package provides ways to drill down into the data through advanced queries not available from Twitter, and retains the data for extended analysis and reference over time. The software provides a friendly user interface, as well as plug-in capabilities for programmers.

Committee:

Karl Ahlqvist (Advisor); Ningchuan Xiao (Committee Member)

Subjects:

Geography

Keywords:

Twitter; social networks; software; PointBank; open source; geodata; geocoding; geography

McCarthy, Brendan JamesGoing Viral in Ancient Rome: Spreading and Controlling Information in the Roman Republic
Doctor of Philosophy, The Ohio State University, 2018, History
In recent years scholars have discussed the role of communication in the Roman political system. These studies have focused mostly on major public events like votes and contiones. This study will add to that discussion by looking at word-of-mouth communication. Rome’s political elite formed information networks to spread news and took great care that their public events like contiones and ludi were well attended and made news. Rome’s non-elite lived in a thriving city that encouraged the movement of people and information. Using theories taken from communications studies, sociology and the spatial turn of archeology, this study will examine the way information was spread after public events. The Roman elite relied on word-of-mouth to ensure that their reputations grew and their agendas received public support. They took great care to ensure that their public events would become news by encouraging favorable audiences to share accounts of the events with their peers. Sharing news, therefore, would have been an integral way from Romans to participate in politics.

Committee:

Nathan Rosenstein (Advisor); Gregory Anderson (Committee Member); Kristina Sessa (Committee Member)

Subjects:

History

Keywords:

Rome; Roman Republic; Cicero; Gossip; Communication; Space; Social Networks; Politics

Duque, Marina GuedesStatus in International Politics
Doctor of Philosophy, The Ohio State University, 2016, Political Science
What is international status, and where does it come from? Whereas previous IR research focuses on the state level by considering status as a motivation, I treat status as relational. Following Weber, I conceptualize status as an effective claim to social esteem. Status is ultimately founded on social recognition: it concerns identity formation processes in which an actor is deemed as belonging in a social group because they adopt the distinctive lifestyle expected from group members. As such, status relations are characterized by the formation of groups bound together by dense relations and a common lifestyle, which involves both material and nonmaterial symbols. Empirically, this approach enables me to move beyond measuring status symbols to examine how status emerges from state relations. Leveraging state-of-the-art network analysis, I examine state practices that express recognition—specifically, the network of diplomatic representations. As expected, I find that status relations are characterized by self-reinforcing dynamics and social closure, neither of which can be explained using traditional approaches. Moreover, the lifestyle of con- temporary high-status states involves not only the ability to fend for oneself under anarchy, but also a standard of civilization based on democracy and economic freedom. In fact, civilizational standards are the main drivers of status recognition. More generally, results indicate that status has a broader role in international politics than previously assumed—one of promoting international order rather than exacerbating conflict.

Committee:

Alexander Wendt (Committee Chair); Randall Schweller (Committee Member); Richard Herrmann (Committee Member)

Subjects:

International Relations; Political Science

Keywords:

Status; prestige; diplomacy; social networks

Wei, RanOn Estimation Problems in Network Sampling
Doctor of Philosophy, The Ohio State University, 2016, Statistics
With the popularity of online social networks such as Facebook, Twitter and LinkedIn, the scale of network data has become enormous. How to take samples that are representative of the full network has been a major research focus. For example, link-tracing sampling methods are effective for obtaining samples from hard-to-reach populations. However link-tracing methods often result in substantially biased samples. In this dissertation we study different link-tracing sampling methods and network models. We compare these methods with simple random sampling in terms of sampling mechanism, estimation bias and variances in estimating parameters and attributes of networks. We explore the root cause for simple average estimators to have large biases and variances. We investigate the interplay among network structure, sampling methods and the variable of interest for both simulated data and real-world social networks data. We propose new estimation methods to correct bias and improve estimation performances. Judgement Post-Stratification (JPS) is a data analysis method based on ideas similar to those in ranked set sampling. Besides serving a variance reduction role, as for traditional sampling schemes, post-stratification also helps reduce bias in a size-biased sampling scheme by down-weighting units that are more likely to be selected and up-weighting units that are less likely to be sampled. In this dissertation, we discuss the applications of JPS in improving estimation performance when using link-tracing sampling methods. We compare the JPS estimator with traditional size-bias compensation methods such as Horvitz-Thompson Estimators (HTE) and Volz-Hackethorn Estimators (VHE). We use machine learning methods to build and improve ranking functions and compare machine learning based JPS with traditional machine learning methods without post-stratification. Extending the ideas of JPS and VHE, we propose a new method, JVE, which is a combination of both. JPS and JVE have been demonstrated to provide a flexible framework that is able to incorporate various information to better rank observed units. We conduct analyses on both simulated data and real world social networks data.

Committee:

David Sivakoff, Dr. (Advisor); Elizabeth Stasny, Dr. (Advisor); Catherine Calder, Dr. (Committee Member)

Subjects:

Statistics

Keywords:

social networks, network sampling, sampling bias, estimation, machine learning, judgement post-stratification, data mining

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