Browsing by Subject "Social networks"

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Accounting for multiple membership data in adolescent social networks : an analysis of simulated data
(2016-05) Peek, Jaclyn Kara; Beretvas, Susan Natasha; Powers, Daniel A.
Multilevel modeling allows for the modeling of nested structures such as students nested within middle schools and middle schools nested within high schools. These kinds of hierarchies are common in social science research. Pure hierarchies may exist, where one variable is completely nested within another. Multiple membership (MM) structures occur when some lower level units are members of more than one higher level clustering unit (e.g., a student attends more than one high school). An extension to the conventional multilevel model, the multiple membership random effects model (MMREM) can be used to handle MM data. I compare a random effects model with and without multiple membership effects to demonstrate the possible benefit of accounting for the MM structure. We replicate an existing study on student academic outcomes (Tranmer et al., 2013) which assumes a multiple membership data structure, and add a comparison to a non-MM (i.e. single membership) model in order to assess the improvement in model fit. The original study investigated the effect of school, area, and social network membership in friendship dyads and triads on academic achievement in adolescents, with age, gender, and ethnicity as covariates. Our models retain the MM structure found in the original social network data. The original data is confidential and unavailable for use – therefore, a major component of this report is the simulation of this dataset in R. Results indicate that multiple membership does not necessarily lead to better goodness-of-fit as measured by DIC. Accounting for MM data structure initially produced a worse-fitting model. Artificially inflating the fixed and random effects that generated the simulated academic performance outcome led to the opposite effect. We conclude that the scale of random effects is important in determining the DIC measure of fit, and propose a full simulation study to more conclusively test our original hypothesis.
Advertising on social networking website : lessons from Cyworld, a South Korea based online network
(2007-08) Jang, Ji-Woon; Leckenby, John D.
Empowered by technologies, more sophisticated and dynamic consumers has become the major force influencing communications. Accordingly, the Internet has been accepted as an innovative, new - although perhaps alternative -- media for over a decade now. Therefore, this paper focuses on weblog advertising, one of Internet advertising forms, as a marketing and communications tool to leverage the power of social networks to create innovative brand experiences. The case of Brand Minihompy, a new marketing medium on Cyworld, South Koreans' social networking website will be scrutinized to look at how marketers can create these experiences for their customers.
Benefits of Internet use in supporting rural life : managing social networks and exchanging social support in a rural area
(2010-05) Park, Namsu; Strover, Sharon; Straubhaar, Joseph; Stein, Laura; Tyner, Kathleen; Lasorsa, Dominic
The purpose of this study was (1) to examine rural residents’ perceived social support from Internet use for communication and (2) to understand the meanings associated with rural Internet users’ social media use, particularly with respect to mediating diverse social ties and exchanging different types of social support. To assess how Internet use affects rural residents’ sense of social support, this study investigated dynamic relationships between online communication and perceived social support by looking at interaction effects relative to extroversion, size of social networks, broadband use, and length of time using the Internet. To explore how social media are situated in a rural area, the present study investigated how rural residents use social network sites (SNSs) to maintain social contacts and exchange social support with members of their networks.
The brave new world : the social and participatory behaviors of the modern suburban African American
(2011-08) McGowen, Ernest Boyd, III; Philpot, Tasha S.; Shaw, Daron R; Roberts, Brian E; Luskin, Robert C; White, Ismail K
Have steady increases in socioeconomic status (SES) and occupational prestige along with changes in residential context and subsequently social networks necessitated a shift in our understanding of Black political participation and group identity? Specifically, how does the unique political environment facing African-American residents in majority Anglo suburbs attach unique utilities to participation, different from their neighbors or even their own co-ethnics that reside in the central city? I argue that African Americans in majority Anglo areas who expend political resources in the most proximate races will derive a negligible benefit. Further, these citizens’ most proximate residential and social network contexts heighten feelings of minority status. Consequently, I contend this class of Black voters are pushed away from the traditional forms of participation (i.e. voting for the congressman or local school board representative) and towards non-traditional, and more resource costly, forms of group directed participation which also come at much higher utilities.
Consumer-brand relationships and effective management of social media
(2010-05) Henry, Daniel D.; Choi, Sejung Marina; Sung, Yongjun
Relationship marketing is an important part of the development of brands. The following report conceives the role of relationship marketing and how brands can use social networks as a key for unlocking a relationship with their consumer. This report presents the managerial implications on relationship marketing, the importance of dialogue, and social media. This report is for marketers to understand the importance of initiating, developing and maintaining a relationship with consumers and translate the concepts so that brands can successfully apply them into social networks.
The emergence of the south European migration system and the role of social networks of migration as catalysts of change in countries of origin : the cases of Argentina and Peru
(2010-08) Vasquez, Tania R.; Buckley, Cynthia J.; Roberts, Bryan R., 1939-; Raley, Kelly; Sakamoto, Arthur; Hale, Charles R.
With this study I aim to understand the role of social networks of migration as very special catalysts of change in the countries of origin of important labor migration streams, particularly in the case of the emergent and second most important system of migration in which Latin Americans participate, i.e. the South European Migration System. I pursue this aim through the means of examining the characteristics and mechanisms of operation of ego – centered social networks of migration that are active within the migration streams from Argentina and Peru to Italy and Spain, therefore: (1) I examine the two different institutional contexts that contribute to the shape of the mentioned social networks of migration in Argentina and Peru; (2) I study the structure of these networks (which comprises characteristics such as size, density, and degree of heterogeneity); their resources and mechanisms of operation ; and (3) I discuss the main possible causal influences that these social networks of migration exert in the countries of origin of the emigration streams I study, namely Argentina and Peru, considering the very specific characteristics these social networks have in each one of the country cases. In order to discuss these causal influences, I examine their impact on children residing in Argentina and Peru who are members of migrant sending households, and I specifically analyze impacts on their living arrangements. I use quantitative and qualitative data on the emigration streams from Argentina and Peru to Italy and Spain which I collected during 2006, 2007 and 2008 , in Buenos Aires (Argentina) and Lima (Peru). Quantitative data was collected using a small household survey targeting relatives of migrants to Spain and Italy, in both cities (Argentina – Italy: n=75, Argentina – Spain: n= 245, Peru – Italy: n= 206, and Peru – Spain: n=398). Qualitative data included expert interviews (n=5 for Peru and n=7 for Argentina); and different types of semi-structured in- depth interviews targeting relatives of migrants to Spain and Italy in different household positions, including children 12 -18 years old (n=11 for Peru, and n=11 for Argentina).
Enabling information-centric networking : architecture, protocols, and applications
(2010-08) Cho, Tae Won, 1978-; Zhang, Yin, doctor of computer science; Gouda, Mohamed; Mooney, Raymond; Ramakrishnan, K.K.; Qiu, Lili
As the Internet is becoming information-centric, network services increasingly demand scalable and efficient communication of information between a multitude of information producers and large groups of interested information consumers. Such information-centric services are growing rapidly in use and deployment. Examples of deployed services that are information-centric include: IPTV, MMORPG, VoD, video conferencing, file sharing, software updates, RSS dissemination, online markets, and grid computing. To effectively support future information-centric services, the network infrastructure for multi-point communication has to address a number of significant challenges: (i) how to understand massive information-centric groups in a scalable manner, (ii) how to analyze and predict the evolution of those groups in an accurate and efficient way, and (iii) how to disseminate content from information producers to a vast number of groups with potentially long-lived membership and highly diverse, dynamic group activity levels? This dissertation proposes novel architecture and protocols that effectively address the above challenges in supporting multi-point communication for future information-centric network services. In doing so, we make the following three major contributions: (1) We develop a novel technique called Proximity Embedding (PE) that can approximate a family of path-ensembled based proximity measures for information-centric groups. We develop Clustered Spectral Graph Embedding (SCGE) that captures the essential structure of large graphs in a highly efficient and scalable manner. Our techniques help to explain the proximity (closeness) of users in information-centric groups, and can be applied to a variety of analysis tasks of complex network structures. (2) Based on SCGE, we develop new supervision based link prediction techniques called Clustered Spectral Learning and Clustered Polynomial Learning that enable us to predict the evolution of massive and complex network structures in an accurate and efficient way. By exploiting supervised information from past snapshots of network structures, our methods yield up to 20% improvement in link prediction accuracy when compared to existing state-of-the-art methods. (3) Finally, we develop a novel multicast infrastructure called Multicast with Adaptive Dual-state (MAD). MAD supports large number of group and group membership, and efficient content dissemination in a presence of dynamic group activity. We demonstrate the effectiveness of our approach in extensive simulation, analysis, and emulation through the real system implementation.
Encouraging expert participation in online communities
(2011-08) DeAngelis, David; Barber, K. Suzanne; Perry, Dewayne E.; Arapostathis, Aristotle; Julien, Christine; Francisco-Revilla, Luis
In concept, online communities allow people to access the wide range of knowledge and abilities of a heterogeneous group of users. In reality, current implementations of various online communities suffer from a lack of participation by the most qualified users. The participation of qualified users, or experts, is crucial to the social welfare and widespread adoption of such systems. This research proposes techniques for identifying the most valuable contributors to several classes of online communities, including question and answer (QA) forums and other content-oriented social networks. Once these target users are identified, content recommendation and novel quantitative incentives can be used to encourage their participation. This research represents an in-depth investigation into QA systems, while the major findings are widely applicable to online communities in general. An algorithm for recommending content in a QA forum is introduced which can route questions to the most appropriate responders. This increases the efficiency of the system and reduces the time investment of an expert responder by eliminating the need to search for potential questions to answer. This recommender is analyzed using real data captured from Yahoo! Answers. Additionally, an incentive mechanism for QA systems based on a novel class of incentives is developed. This mechanism relies on systemic rewards, or rewards that have tangible value within the framework of the online community. This research shows that human users have a strong preference for reciprocal systemic rewards over traditional rewards, and a simulation of a QA system based on an incentive that utilizes these reciprocal rewards outperforms a leading incentive mechanism according to expert participation. An architecture is developed for a QA system built upon content recommendation and this novel incentive mechanism. This research shows that it is possible to identify the most valuable contributors to an online community and motivate their participation through a novel incentive mechanism based on meaningful rewards.
Entrepreneur career paths, location choice, and ecosystems : an empirical analysis
(2018-05-07) Stephens, Bryan Michael; Butler, John S. (John Sibley); Garg, Rajiv; Chen, Wenhong; Paxton, Pamela
This dissertation consists of three research articles investigating three related research questions about entrepreneurial ecosystems and the career and location transitions of technology entrepreneurs. Altogether, the analyses improve our understanding of how particular work experiences and skills can shape the career paths of entrepreneurs and executives and how certain locations are consistently better at retaining/attracting entrepreneurial talent. The first article explores the common career paths of entrepreneurs, executives, and senior managers in the high-tech industry. I build career trajectories (as network graphs) that provide insights on career paths of entrepreneurs, executives, and senior managers based on a large dataset of work histories. Focusing on the high-tech industry, I find that individuals with certain transferable skills—notably technical, management, mixed, and boundary-spanning experience—are more likely to be in position to capitalize on job opportunities across industries. Furthermore, I test these insights by developing and refining a supervised learning model for predicting individual career transitions. In the second article, I investigate why certain U.S. metropolitan areas are better able to retain and attract technology entrepreneurs. Placing the entrepreneur at the center of the analysis, I examine the role of regional economic factors, regional funding opportunities, and personal social networks on entrepreneur decisions to start a high-tech firm in a specific location. The third article investigates the entrepreneurial ecosystems of Silicon Valley, Austin, Boston, and New York, which are well-established innovation-centered business clusters and entrepreneurial “talent magnets”. Following a brief overview and history of the entrepreneurial ecosystems of each region, I specify models (for each region) testing the importance of social network ties, funding, education, and cumulative work experience in driving the entrepreneurs’ location choice decisions. I supplement the empirical findings by analyzing interview data collected from technology entrepreneurs to explain how particular structures within entrepreneurial ecosystems facilitate interaction and networking among entrepreneurs—offering potential explanations for some of the observed variation between regions.
Essays in economic theory
(2011-05) Tang, Qianfeng; Pȩski, Marcin; Stinchcombe, Maxwell; Norman, Alfred; Wiseman, Thomas; Whinston, Andrew
This dissertation consists of three essays in Economic Theory. The rst essay proposes and studies a new solution concept for games with incomplete information. In game theory, there is a basic methodological dichotomy between Harsanyi's \game-theoretic" view and Aumann's \Bayesian decision-theoretic" view of the world. We follow the game theoretic view, propose and study interim partially correlated rationalizability for games with incomplete information. We argue that the distinction between this solution concept and the interim correlated rationalizability studied by Dekel, Fudenberg and Morris (2007) is fundamental, in that the latter implicitly follows Aumann's Bayesian view. Our main result shows that two types provide the same prediction in interim partially correlated rationalizability if and only if they have the same in nite hierarchy of beliefs over conditional beliefs. We also establish an equivalence result between this solution concept and the Bayesian solution{a notion of correlated equilibrium proposed by Forges (1993). The second essay studies the relationship between correlated equilibrium the redundancy embedded in type spaces. The Bayesian solution is a notion of correlated equilibrium proposed by Forges (1993), and hierarchies of beliefs over conditional beliefs are introduced by Ely and Peski (2006) in their study of interim rationalizability. We study the connection between the two concepts. We say that two type spaces are equivalent if they represent the same set of hierarchies of beliefs over conditional beliefs. We show that the correlation embedded in equivalent type spaces can be characterized by partially correlating devices, which send correlated signals to players in a belief invariant way. Since such correlating devices also implement the Bayesian solution, we establish that the Bayesian solution is invariant across equivalent type spaces. The third essay studies the existence of equilibria for rst-price sealed bid auctions when bidders form a network and each bidder observes perfectly their neighbors' private valuations. Asymmetry in bidders' positions in the network creates asymmetry in bidders' knowledge. We show the existence of pure-strategy equilibrium.
Essays on firm strategies and consumer dynamics in socially embedded technology networks
(2013-05) Mukherjee, Rajiv, active 2013; Barua, Anitesh
It is of deep interest to researchers and practitioners in Information System (IS) to understand the efficacy of the traditional IS and economics theory in modern business environments such as online social networks. In the pursuit to understand such new IS phenomenon and address the gap in extant literature, my dissertation, identifies the strategies that the firms should incorporate in the presence of network effects; i.e., the increases in benefits accrued by a network user with an increase in the number of users, and its impact on consumer behavior. My first essay, challenges the traditional notion that network effects create a strong protective moat for the incumbent in network competition. I show that network effects are over rated in multi-homing setting, where users can co-exist across multiple networks under resource constraints. Over reliance on the strength of network effects by the incumbent firm in multi-homing setting, stems from extant economic theory that is applicable to single homing networks, where users has to choose one of the available networks. The first essay recommends strategies for the level of innovation and its time of delivery that firms should incorporate in order to survive and succeed in multi-homing environment. While the first essay focuses on multi-homing and the strength of network effects, the second essay revisits firm's preemption strategy in single homing setting with network effects, in order to prevent its users from migrating to a new entrant with better technology. I find that, for moderate levels of price and innovation competition, an incumbent with high reputation is better off being non-committal in its preemption. In contrast, committal preemption is apt for other combinations of reputation, innovation and price. While the first two essays focus on the impact of consumer behavior on firm strategies, the third essay delves into the impact of firm strategies on consumer behavior. In particular, I identify identity revelation policies that increase the number of successful transactions and collaborations in a socially embedded marketplace. The results imply that revealing social identities may be detrimental to negotiation and collaboration in a socially embedded marketplace -- a notion that is counter intuitive to networks that are inherently social.
Essays on the economics of information systems
(2014-08) Qiu, Liangfei; Whinston, Andrew B.
Information technology and social media have been a driving force in the economy and have transformed all aspects of business in recent decades. Understanding social networks is necessary to evaluate their impacts and examine key business issues involving information and technological innovations. The dissertation contains three chapters exploring those issues. In the first chapter, I propose an optimal procurement mechanism for mobile data offloading, covering both technological and business aspects. The unprecedented growth of cellular traffic driven by web surfing, video streaming, and cloud-based services is creating challenges for cellular service providers to fulfill the unmet demand. My present work contributes to the existing literature by developing an analytical model, which considers the unique challenge of integrating the longer range cellular resource and shorter range WiFi hotspots. In the second chapter, I examine the effect of a social network on prediction markets using a controlled laboratory experiment. In prediction markets, people place bets on events that they think are most likely to happen, thus revealing in a sense the nature of their private information. Through a randomized experiment, I show that when the cost of information acquisition is low, a social-network-embedded prediction market outperforms a non-networked prediction market. The third chapter studies different forms of social learning in the context of location-based networks: observational learning and the saliency effect. In recent years, the location-sensing mobile devices offer geographic location capabilities to share users' information about their locations with their friends. In our context, observational learning corresponds to the fact that "check-ins" made by friends help users learn the quality information of a venue; the saliency effect refers to that check-ins lead some of the uninformed consumers to discover a new venue.
The family and the making of women's rights activism in Lebanon
(2009-05) Stephan, Rita Toufic; Charrad, M. (Mounira)
This research explores how Lebanese women's rights activists use their kinship system to pursue citizenship rights and political recognition. Building on social movements, social capital, and feminist theories, I argue that Lebanese women's rights activists leverage support from their kin groups and adhere to the behavioral norms set by the kinship system in order to gain access, build capacity and advance their movement's goals and strategies. In investigating the impact of being embedded in--or autonomous from--kinship structure on activism, my research suggests that Lebanese women's rights activists interact with their kin groups at three levels. Firstly, at the level of becoming an activist, some women obtain direct support and encouragement from their nuclear and extended family, while others rise through alternative networks such as membership in a political party or a professional union. At the personal strategies level, some activists utilize their family support and kinship networks to establish their activist identities and facilitate their civic engagement, while others use collegial and professional networks. Finally, on the organizational level, women's rights organizations pursue women's empowerment in the context of their role in the family, dissolving the divide between women's rights in the sphere of legal equality and women's rights within the family. Women's relation to kinship is significant in explaining how they form their activist identity and construct their activism, regardless whether they use embedded or autonomous strategies. Activists receive empowerment and support from the family in advancing their goals and consider family members as important forces in shaping their journeys to activism. In the same vein, the kinship system contributes to determining actors' social status at the outset; its networks potentially grant activists access to the public sphere; and its name and ties endows activists with public trust and respect. Lebanese activists expand on the capabilities provided for them by their kin groups to enhance women’s status in their public as well as private roles.
Feeding the technopolis : an overview of the potential emergence of homemade food markets in neighborhoods and its energy savings : a trans-disciplinary approach
(2018-12) Azagra, Marcelo; King, Carey Wayne, 1974-
Individual decision making (e.g. deciding which type of food to eat) has recently significantly benefited from the widespread use of machine learning in artificial intelligence (AI) applications (e.g. search-friendly metadata) used by companies like Yelp, Google, Amazon, and Facebook. Nevertheless, certain goals are difficult to achieve via the collective use of AI. As a result, the centralized authority framework of control prevails, governing the factors of collective intelligence (e.g. countries, cities, neighborhoods, groups). AI gets its value from large data sets obtained from exploiting collective human interactions, mathematical models, and computing power. So, while AI is usually compared with human intelligence (e.g. Deep Blue beat chess' master in 1997 and AlphaGo beat Go's master in 2017), both complement each other more than is usually admitted. The emergence of new ideas often mimics the way natural systems survive and evolve. Some living organisms such a slime mold, ant colonies, and beehives work collectively especially when food is scarce. For instance, ant colonies follow rules written in the form of pheromones with different intensities, a “chemical alphabet” to signal specific requests and warnings, ultimately creating an autocatalytic processes that functions as a collective brain to find food and survive. By extension, the social and economic value of technological innovations for humans is comparable. Linking previously disconnected agents through electronic platforms increases the number of interactions and the number of choices available, minimizing their transaction cost. Moreover, the blurring roles of actors interacting in the cyberspace and physical space are a distinctive characteristic of the new economy (e.g. Amazon’s acquisition of Whole Foods). People work collectively producing, consuming, and improving solutions aided by Peer-to-Peer (P2P) networks, enabling the rise of self-management systems without central planning (e.g. Wikipedia, DIY bio). Democracy and human rights are notable examples of social innovations that historically challenged the status-quo. The rise of self-organizing political and economic structures without a central authority could be the next one. Moreover, if technologies are configured to enable regular, honest, and cooperative behavior through social norms and programmable trust, it can be a powerful tool for the emergence of new collective actions without central planning in neighborhoods, cities, and countries. One of the affordances of AI applications is to solve problems that scale globally such as energy and food security. AI applications are helpful, for example, by providing more efficient grid operation or an optimal inventory and delivery management system. They also reduce waste and energy consumption by supporting the operation of networked collaborative systems capable of changing the very nature of food consumption habits and improving the overall efficiency in the use of natural resources. As a result of this study, I have found that the potential development of a self-organizing homemade food market in neighborhoods could improve the energy efficiency of the food system, allowing energy savings equal to 1.2 percent of the total energy used by a city’s food system. To support the development of such a market, tools used in AI applications such as sentiment analysis and the Blockchain, can play a significant role in their ability to anticipate market needs, and provide a secure, transparent, and efficient transaction platforms. Therefore, these AI tools can have a significant impact in reducing the need of trustees such as banks and companies that provide access to peer-to-peer service platforms like Uber and Airbnb.
Getting connected : minority group membership and implicit theories of portfolios of social capital
(2021-08-12) Jo, Jae Kwon; Harrison, David A. (Professor in management); Burris, Ethan; Gray, Steven; Rosette, Ashleigh
Social network theory posits that informal ties provide access to critical resources such as task knowledge, social support, or unique information that are essential for job performance and career success. Central positions in the social network or positions that bridge disconnected circles of individuals have been linked to important individual-level outcomes. Despite the benefits that advantageous positions in social networks have to offer, some individuals experience systematically greater difficulty in obtaining them. Prior investigations have found that individuals in minority groups are often pushed to the periphery of their social networks. Minority group members face unique constraints at the workplace due to the lack of similar others in the social environment. Thus, individuals in minority groups might have different ideas about how to develop and manage their social networks than their majority group counterparts. Overall, this dissertation attempts to understand the implicit theories behind how individuals form their informal ties at the workplace. I identify several parameters of individuals’ implicit theories of social networks, and then compare how these parameters differ across individuals from different identity groups. This dissertation provides an initial psychological account for how these implicit theories lead to an increased or decreased likelihood of tie formation. Overall, I find that minority group members are more likely to hold implicit theory sub-dimensions that center around trust and acceptance. These sub-dimensions act as selectivity filters that lead minority group members to reach out to fewer individuals because such individuals will only look to reach out to those who they believe will be accepting of them. Following a sample of MBA students (N = 195), I find initial support that minority group members have a different mental approach in constructing their overall portfolios of social capital.
Grouping and comparing Texas high schools through machine learning and visualization techniques
(2018-04-27) Guthrie, Matthew Warren; Marder, Michael P., 1960-; Berk, Herbert; Gordon, Vernita; Marshall, Jill; Riley, Peter
The Texas Assessment of Knowledge and Skills (TAKS) was administered from Spring 2003 to Spring 2012 to every public school student in the state of Texas. Student test scores from the mathematics portion of the test were analyzed in this study. These standardized test scores form a large and complex data set which cannot be easily understood. Simplification of the educational system and analysis of the data in aggregate are necessary for nuanced features of the data set to be studied. The Texas Education Agency utilizes a k-nearest neighbor algorithm with a small number of factors (e.g., the number of students relative to the largest school, the percentage of English language learners, and the percentage of students who qualify for free/reduced price lunch) to calculate a campus comparison group for every school in the state. However, there are a few challenges associated with this approach - the comparison groups are highly interconnected and asymmetric (vary from school to school). The asymmetry of the grouping does not simplify the system under study, and the asymmetry does not allow for the classification of the types of groups that are created. In order to address these limitations, a method for forming disjoint groups of schools in Texas was developed using modern machine learning techniques (dimensionality reduction and clustering). Test scores for students from each high school in the state were visualized, which showed that test scores were stratified by student poverty concentration. Inter-cluster comparisons allowed for the identification of a group of schools which significantly outperform other groups with similar poverty levels. Intra-cluster comparisons were conducted which identified exemplary schools based on their outstanding performance compared to that of the average performance of their cluster. Overall, grouping schools through clustering algorithms was shown to be superior to the current method for the purposes of this study, and allowed for the identification of different types of exemplary schools in the state of Texas.
Identifying infection processes with incomplete information
(2014-12) Milling, Philip Christopher; Shakkottai, Sanjay
Infections frequently occur on both networks of devices and networks of people, and can model not only viruses, but also information, rumors, and product use. However, in many circumstances, the infection process itself is hidden, and only the effects, e.g. sickness or knowledge, can be observed. In addition, this information is likely incomplete, missing many sick nodes, as well as inaccurate, with false positives. To use this data effectively, it is often essential to identify the infection process causing the sickness, or even whether the cause is an infection. For our purposes, we consider the susceptible-infected (SI) infection model. We seek to distinguish between infections and random sickness, as well as between different infection (or infection-like) processes in a limited information setting. We formulate this as a hypothesis testing problem, where (typically) in the null, the sickness affects nodes at random, and in the alternative, the infection is spread through the network. Similarly, we consider the case where the sickness may be caused by one of two infection (or infection-like) processes, and we wish to find which is the causative process. We do this is a setting with very limited information, given only a single snapshot of the infection. Only a small portion of the infected population reports the sickness. In addition, there are several other limitations we consider. There may be false positives, obfuscating the infection. Similarly, there may be a random sickness and epidemic process occurring simultaneously. Knowledge of the graph topology may be incomplete, with unknown edges over which the infection may spread. The graph may also be weighted, affecting the way the infection spreads over the graph. In all these cases, we develop algorithms to identify the causative process of the infection utilizing the fact that infected nodes will be clustered. We demonstrate that under reasonable conditions, these algorithms detect an infection with asymptotically zero error probability as the graph size increases.
The Impact of Imitation on Vaccination Behavior in Social Contact Networks
(Public Library of Science, 2012-04-12) Ndeffo Mbah, Martial L.; Liu, Jingzhou; Bauch, Chris T.; Tekel, Yonas I.; Medlock, Jan; Meyers, Lauren Ancel; Galvani, Alison P.
Previous game-theoretic studies of vaccination behavior typically have often assumed that populations are homogeneously mixed and that individuals are fully rational. In reality, there is heterogeneity in the number of contacts per individual, and individuals tend to imitate others who appear to have adopted successful strategies. Here, we use network-based mathematical models to study the effects of both imitation behavior and contact heterogeneity on vaccination coverage and disease dynamics. We integrate contact network epidemiological models with a framework for decision-making, within which individuals make their decisions either based purely on payoff maximization or by imitating the vaccination behavior of a social contact. Simulations suggest that when the cost of vaccination is high imitation behavior may decrease vaccination coverage. However, when the cost of vaccination is small relative to that of infection, imitation behavior increases vaccination coverage, but, surprisingly, also increases the magnitude of epidemics through the clustering of non-vaccinators within the network. Thus, imitation behavior may impede the eradication of infectious diseases. Calculations that ignore behavioral clustering caused by imitation may significantly underestimate the levels of vaccination coverage required to attain herd immunity.
Meet the parents (and friends) : examining the association between social network introductions and romantic relationship state and fate
(2014-12) Wright, Brittany Lauren, 1985-; Loving, Timothy J.
Part of the natural progression of any romantic relationship is that, over time, individuals will meet and form connections with each other’s friends and family (Milardo, 1982). Interestingly, the examination of social network introductions has largely been neglected by researchers. We do not know when couple members introduce each other to their friends and parents. We also do not know what effect, if any, these network introductions have on future relationship outcomes. The present study addressed these gaps. Specifically, I examined when couple members typically met each other’s friends and parents for the first time, whether relationship quality influenced the likelihood of making these introductions, and whether these introductions predicted later relationship outcomes (i.e., relationship quality, likelihood of breakup, and post-breakup adjustment). In the present study, participants in new romantic relationships (less than 6 months duration) completed a survey every two weeks for nine months. In each survey, participants indicated whether friend and family introductions had occurred, their current relationship quality, and whether they had broken up with their partners since the previous survey. If individuals reported having broken up, they were asked about their reactions to the breakup. Results revealed that friends were typically introduced before parents, and that relationship quality predicted the likelihood of newly dating individuals introducing their parents (but not friends) to their romantic partners. Largely, network introductions failed to predict later perceptions of relationship quality but did influence the likelihood of relationship dissolution over the course of the study. Furthermore, introductions to participants’ mothers predicted worse emotional reactions to a breakup, and introductions to participants’ fathers and best friends were associated with greater relationship longing. The results of this study represent an important first step in understanding when individuals introduce their romantic partners to their friends and family and how these introductions influence relationship development.
More than One, Less than Many: A Review of Three “Post-ANT” Books
(Currents in Electronic Literacy, 2003) Spinuzzi, Clay