Relevant bibliographies by topics / Attachment network

Academic literature on the topic 'Attachment network'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Attachment network"

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Haryono, Haryono, Mukhtar Mukhtar, Titik Sumarti, Didin S. Damanhuri, and Sofyan Sjaf. "Embeddedness of Economic Actions in the Social Network: Study among of Local Genuine Entrepreneurship in Cirebon, West Java." JSW (Jurnal Sosiologi Walisongo) 6, no. 1 (April 30, 2022): 29–42. http://dx.doi.org/10.21580/jsw.2022.6.1.8023.

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The purpose of this study was to analyze the attachment of economic activity in social networks among entrepreneurs in Cirebon, West Java, Indonesia. This research was conducted in Cirebon Regency, for a period of 6 months, from May to October 2019. This research method uses a qualitative approach. The results of the study found that: first, local entrepreneurs (genuine) in the rattan business sector have been running for a very long time. Second, as a result of historical formation, there is a wide network both between entrepreneurs and between entrepreneurs with certain institutions and community structures. Thrid, the map of economic network attachment in social networks shows the diversity of attachments between economic networks and social networks.
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Gillath, Omri, Gery C. Karantzas, and Emre Selcuk. "A Net of Friends: Investigating Friendship by Integrating Attachment Theory and Social Network Analysis." Personality and Social Psychology Bulletin 43, no. 11 (July 24, 2017): 1546–65. http://dx.doi.org/10.1177/0146167217719731.

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The current article focuses on attachment style—an individual difference widely studied in the field of close relationships—and its application to the study of social networks. Specifically, we investigated whether attachment style predicts perception and management of social networks. In Study 1, we examined the associations of attachment style with perceptions of network tie strength and multiplexity. In Studies 2a and 2b, we investigated the association between attachment style and network management skills (initiating, maintaining, and dissolving ties) and whether network management skills mediated the associations of attachment style with network tie strength and multiplexity. In Study 3, experimentally enhancing attachment security made people more likely to initiate and less likely to dissolve social ties (for the latter, especially among those high on avoidance or anxiety). As for maintenance, security priming also increased maintenance; however, mainly among people high on attachment anxiety or low on attachment avoidance.
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Tameirão, Cinthya Rocha, Sérgio Fernando Loureiro Rezende, and Luciana Pereira de Assis. "Ligação Preferencial e Aptidão na Evolução da Rede de Filmes Brasileiros." Organizações & Sociedade 28, no. 99 (December 2021): 888–916. http://dx.doi.org/10.1590/1984-92302021v28n9907pt.

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Abstract This study analyzes the network evolution, specifically that of the Brazilian film network. It examines two generative mechanisms that lie behind the network evolution: preferential attachment and fitness. The starting point is that preferential attachment and fitness may compete to shape the network evolution. We built a novel dataset with 974 Brazilian feature films released between 1995 and 2017 and used PAFit, a brand-new statistical method, to estimate the joint effects of preferential attachment and fitness on the evolution of the Brazilian film network. This study concludes that the network evolution is shaped by both preferential attachment and fitness. However, in the presence of fitness, the effects of preferential attachment on the network evolution become weaker. This means that the node ability to form ties in the Brazilian film network is mainly explained by its fitness. Besides, the preferential attachment assumes a sub-linear form. Costs, communication and managerial capabilities, and node age explain why nodes are unable to accumulate ties at rates proportional to their degree. Finally, preferential attachment and fitness manifest themselves heterogeneously, depending on either the type or the duration of the network. Preferential attachment drives the cast network evolution, whereas fitness is the main generative mechanism of the crew network. Actors and actresses rely on their status, privilege, and power to obtain future contracts (preferential attachment), whereas technical members are selected on the basis of their talent, skills, and knowledge (fitness). Due to node age or exit, preferential attachment becomes stronger in shorter networks.
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Siew, Cynthia S. Q., and Michael S. Vitevitch. "Investigating the Influence of Inverse Preferential Attachment on Network Development." Entropy 22, no. 9 (September 15, 2020): 1029. http://dx.doi.org/10.3390/e22091029.

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Recent work investigating the development of the phonological lexicon, where edges between words represent phonological similarity, have suggested that phonological network growth may be partly driven by a process that favors the acquisition of new words that are phonologically similar to several existing words in the lexicon. To explore this growth mechanism, we conducted a simulation study to examine the properties of networks grown by inverse preferential attachment, where new nodes added to the network tend to connect to existing nodes with fewer edges. Specifically, we analyzed the network structure and degree distributions of artificial networks generated via either preferential attachment, an inverse variant of preferential attachment, or combinations of both network growth mechanisms. The simulations showed that network growth initially driven by preferential attachment followed by inverse preferential attachment led to densely-connected network structures (i.e., smaller diameters and average shortest path lengths), as well as degree distributions that could be characterized by non-power law distributions, analogous to the features of real-world phonological networks. These results provide converging evidence that inverse preferential attachment may play a role in the development of the phonological lexicon and reflect processing costs associated with a mature lexicon structure.
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Adam, Diyawu Rahman, Kwame Simpe Ofori, Abednego Feehi Okoe, and Henry Boateng. "Effects of structural and bonding-based attachment on brand loyalty." African Journal of Economic and Management Studies 9, no. 3 (September 3, 2018): 305–18. http://dx.doi.org/10.1108/ajems-10-2017-0252.

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PurposeThe purpose of this paper is to ascertain the effects of structural and bonding attachment on brand loyalty. The authors identified network quality, network coverage and mobile number portability (MNP) as structural elements of attachment that affect brand loyalty. Similarly, the authors identify brand trust and social interaction ties as elements of bonding-based attachment that affects brand loyalty.Design/methodology/approachThe authors employed a survey as the research design. There were 500 respondents who were customers of telecommunication network brands in Ghana. Data collected were analyzed using the partial least square approach to structural equation modeling (PLS-SEM) on SmartPLS 3.FindingsThe findings indicate that structural and bonding-based attachments affect the brand loyalty. Specifically, the authors found that network coverage, network quality, brand trust and social interaction ties have positive effects on brand loyalty while MNP has a negative effect on brand loyalty.Originality/valueThis study conceptualizes attachment from both structural and bonding perspectives, which are rare in the marketing literature. Thus, this study advances the conceptualization of attachment in the marketing literature.
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Scharfe, Elaine. "Hitting the bull’s eye: Attachment representations and the organization of social networks." Interpersona: An International Journal on Personal Relationships 14, no. 1 (July 2, 2020): 15–27. http://dx.doi.org/10.5964/ijpr.v14i1.3919.

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Hazan and Zeifman were the first to explore Bowlby’s proposition that adults would organize their attachment relationships into a hierarchy and since then considerable research has explored both the structure and function of attachment hierarchies using different methodologies. In this study, previous findings establishing an association between attachment and networks were replicated and the associations between network members were explored. First, consistent with expectations, the findings provided additional evidence that romantic partners do not necessarily jump to the top of the hierarchy and young adults continue to place parents, in particular mothers, at the top of their hierarchy. Consistent with previous work, security was associated with placing others closer to the self and attachment avoidance was associated with placing others farther from the self on an electronic bull’s eye. Furthermore, to date, this is the first study to examine the association between attachment representations and the organization of network members. Interestingly, security was associated with placing network members closer to each other and attachment avoidance was associated with placing network members farther from each other. This finding suggests that individuals with high attachment security may be more motivated to allow members of their social networks to mingle whereas individuals with high attachment avoidance scores seemed to be motivated to keep their network members at a distance. The results of this study extend our understanding how attachment representations may influence the organization of our social networks.
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Rak, Rafał, and Ewa Rak. "The Fractional Preferential Attachment Scale-Free Network Model." Entropy 22, no. 5 (April 29, 2020): 509. http://dx.doi.org/10.3390/e22050509.

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Many networks generated by nature have two generic properties: they are formed in the process of preferential attachment and they are scale-free. Considering these features, by interfering with mechanism of the preferential attachment, we propose a generalisation of the Barabási–Albert model—the ’Fractional Preferential Attachment’ (FPA) scale-free network model—that generates networks with time-independent degree distributions p ( k ) ∼ k − γ with degree exponent 2 < γ ≤ 3 (where γ = 3 corresponds to the typical value of the BA model). In the FPA model, the element controlling the network properties is the f parameter, where f ∈ ( 0 , 1 ⟩ . Depending on the different values of f parameter, we study the statistical properties of the numerically generated networks. We investigate the topological properties of FPA networks such as degree distribution, degree correlation (network assortativity), clustering coefficient, average node degree, network diameter, average shortest path length and features of fractality. We compare the obtained values with the results for various synthetic and real-world networks. It is found that, depending on f, the FPA model generates networks with parameters similar to the real-world networks. Furthermore, it is shown that f parameter has a significant impact on, among others, degree distribution and degree correlation of generated networks. Therefore, the FPA scale-free network model can be an interesting alternative to existing network models. In addition, it turns out that, regardless of the value of f, FPA networks are not fractal.
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ANTUNOVIĆ, TONĆI, ELCHANAN MOSSEL, and MIKLÓS Z. RÁCZ. "Coexistence in Preferential Attachment Networks." Combinatorics, Probability and Computing 25, no. 6 (February 9, 2016): 797–822. http://dx.doi.org/10.1017/s0963548315000383.

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We introduce a new model of competition on growing networks. This extends the preferential attachment model, with the key property that node choices evolve simultaneously with the network. When a new node joins the network, it chooses neighbours by preferential attachment, and selects its type based on the number of initial neighbours of each type. The model is analysed in detail, and in particular, we determine the possible proportions of the various types in the limit of large networks. An important qualitative feature we find is that, in contrast to many current theoretical models, often several competitors will coexist. This matches empirical observations in many real-world networks.
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Tameirão, Cinthya Rocha, Sérgio Fernando Loureiro Rezende, and Luciana Pereira de Assis. "Preferential Attachment and Fitness in the Evolution of the Brazilian Film Network." Organizações & Sociedade 28, no. 99 (December 2021): 888–916. http://dx.doi.org/10.1590/1984-92302021v28n9907en.

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Abstract This study analyzes the network evolution, specifically that of the Brazilian film network. It examines two generative mechanisms that lie behind the network evolution: preferential attachment and fitness. The starting point is that preferential attachment and fitness may compete to shape the network evolution. We built a novel dataset with 974 Brazilian feature films released between 1995 and 2017 and used PAFit, a brand-new statistical method, to estimate the joint effects of preferential attachment and fitness on the evolution of the Brazilian film network. This study concludes that the network evolution is shaped by both preferential attachment and fitness. However, in the presence of fitness, the effects of preferential attachment on the network evolution become weaker. This means that the node ability to form ties in the Brazilian film network is mainly explained by its fitness. Besides, the preferential attachment assumes a sub-linear form. Costs, communication and managerial capabilities, and node age explain why nodes are unable to accumulate ties at rates proportional to their degree. Finally, preferential attachment and fitness manifest themselves heterogeneously, depending on either the type or the duration of the network. Preferential attachment drives the cast network evolution, whereas fitness is the main generative mechanism of the crew network. Actors and actresses rely on their status, privilege, and power to obtain future contracts (preferential attachment), whereas technical members are selected on the basis of their talent, skills, and knowledge (fitness). Due to node age or exit, preferential attachment becomes stronger in shorter networks.
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Shang, Yilun. "Limit of a nonpreferential attachment multitype network model." International Journal of Modern Physics B 31, no. 05 (February 9, 2017): 1750026. http://dx.doi.org/10.1142/s0217979217500266.

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Here, we deal with a model of multitype network with nonpreferential attachment growth. The connection between two nodes depends asymmetrically on their types, reflecting the implication of time order in temporal networks. Based upon graph limit theory, we analytically determined the limit of the network model characterized by a kernel, in the sense that the number of copies of any fixed subgraph converges when network size tends to infinity. The results are confirmed by extensive simulations. Our work thus provides a theoretical framework for quantitatively understanding grown temporal complex networks as a whole.
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Dissertations / Theses on the topic "Attachment network"

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Belinkov, Yonatan. "Neural network architectures for Prepositional Phrase attachment disambiguation." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91147.

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Thesis: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
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Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 41-44).
This thesis addresses the problem of Prepositional Phrase (PP) attachment disambiguation, a key challenge in syntactic parsing. In natural language sentences, a PP may often be attached to several possible candidates. While humans can usually identify the correct candidate successfully, syntactic parsers are known to have high error rated on this kind of construction. This work explores the use of compositional models of meaning in choosing the correct attachment location. The compositional model is defined using a recursive neural network. Word vector representations are obtained from large amounts of raw text and fed into the neural network. The vectors are first forward propagated up the network in order to create a composite representation, which is used to score all possible candidates. In training, errors are back-propagated down the network such that the composition matrix is updated from the supervised data. Several possible neural architectures are designed and experimentally tested in both English and Arabic data sets. As a comparative system, we offer a learning-to-rank algorithm based on an SVM classifier which has access to a wide range of features. The performance of this system is compared to the compositional models.
by Yonatan Belinkov.
S.M. in Computer Science and Engineering
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Ouellette, David M. "The Social Network and Attachment Bases of Loneliness." VCU Scholars Compass, 2004. http://scholarscompass.vcu.edu/etd/949.

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This thesis tests Robert S. Weiss's 1973 theory of loneliness, which claims two types of loneliness: emotional and social. Emotional loneliness is the affective reaction to the absence of a close attachment bond. Social loneliness stems from inadequate integration into a social network. Undergraduate residents of a university dormitory completed questionnaires on loneliness, attachment, personality, and relationships with other dorm residents. Patterns of relational ties among participants were evaluated using social network analysis, specifically density, tie strength, and four forms of centrality. Results reveal that, while controlling for neuroticism, the network measure of outdegree and the two attachment dimensions accounted for more than half the variance in loneliness, R = .73. None of the three predictors intercorrelated significantly. A portion of loneliness is derived from one's internal attachment security and a separate portion is derived from the external features of one's social network integration.
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Abdelzaher, Ahmed F. "Identifying Parameters for Robust Network Growth using Attachment Kernels: A case study on directed and undirected networks." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4481.

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Network growing mechanisms are used to construct random networks that have structural behaviors similar to existing networks such as genetic networks, in efforts of understanding the evolution of complex topologies. Popular mechanisms, such as preferential attachment, are capable of preserving network features such as the degree distribution. However, little is known about such randomly grown structures regarding robustness to disturbances (e.g., edge deletions). Moreover, preferential attachment does not target optimizing the network's functionality, such as information flow. Here, we consider a network to be optimal if it's natural functionality is relatively high in addition to possessing some degree of robustness to disturbances. Specifically, a robust network would continue to (1) transmit information, (2) preserve it's connectivity and (3) preserve internal clusters post failures. In efforts to pinpoint features that would possibly replace or collaborate with the degree of a node as criteria for preferential attachment, we present a case study on both; undirected and directed networks. For undirected networks, we make a case study on wireless sensor networks in which we outline a strategy using Support Vector Regression. For Directed networks, we formulate an Integer Linear Program to gauge the exact transcriptional regulatory network optimal structures, from there on we can identify variations in structural features post optimization.
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Tsipenyuk, Gregory. "Evaluation of decentralized email architecture and social network analysis based on email attachment sharing." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/273963.

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Present day email is provided by centralized services running in the cloud. The services transparently connect users behind middleboxes and provide backup, redundancy, and high availability at the expense of user privacy. In present day mobile environments, users can access and modify email from multiple devices with updates reconciled on the central server. Prioritizing updates is difficult and may be undesirable. Moreover, legacy email protocols do not provide optimal email synchronization and access. Recent phenomena of the Internet of Things (IoT) will see the number of interconnected devices grow to 27 billion by 2021. In the first part of my dissertation I am proposing a decentralized email architecture which takes advantage of user's a IoT devices to maintain a complete email history. This addresses the email reconciliation issue and places data under user control. I replace legacy email protocols with a synchronization protocol to achieve eventual consistency of email and optimize bandwidth and energy usage. The architecture is evaluated on a Raspberry Pi computer. There is an extensive body of research on Social Network Analysis (SNA) based on email archives. Typically, the analyzed network reflects either communication between users or a relationship between the email and the information found in the email's header and the body. This approach discards either all or some email attachments that cannot be converted to text; for instance, images. Yet attachments may use up to 90% of an email archive size. In the second part of my dissertation I suggest extracting the network from email attachments shared between users. I hypothesize that the network extracted from shared email attachments might provide more insight into the social structure of the email archive. I evaluate communication and shared email attachments networks by analyzing common centrality measures and classication and clustering algorithms. I further demonstrate how the analysis of the shared attachments network can be used to optimize the proposed decentralized email architecture.
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Zheng, Huanyang. "SOCIAL NETWORK ARCHITECTURES AND APPLICATIONS." Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/470889.

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Computer and Information Science
Ph.D.
Rather than being randomly wired together, the components of complex network systems are recently reported to represent a scale-free architecture, in which the node degree distribution follows power-law. While social networks are scale-free, it is natural to utilize their structural properties in some social network applications. As a result, this dissertation explores social network architectures, and in turn, leverages these architectures to facilitate some influence and information propagation applications. Social network architectures are analyzed in two different aspects. The first aspect focuses on the node degree snowballing effects (i.e., degree growth effects) in social networks, which is based on an age-sensitive preferential attachment model. The impact of the initial links is explored, in terms of accelerating the node degree snowballing effects. The second aspect focuses on Nested Scale-Free Architectures (NSFAs) for social networks. The scale-free architecture is a classic concept, which means that the node degree distribution follows the power-law distribution. `Nested' indicates that the scale-free architecture is preserved when low-degree nodes and their associated connections are iteratively removed. NSFA has a bounded hierarchy. Based on the social network structure, this dissertation explores two influence propagation applications for the Social Influence Maximization Problem (SIMP). The first application is a friend recommendation strategy with the perspective of social influence maximization. For the system provider, the objective is to recommend a fixed number of new friends to a given user, such that the given user can maximize his/her social influence through making new friends. This problem is proved to be NP-hard by reduction from the SIMP. A greedy friend recommendation algorithm with an approximation ratio of $1-e^{-1}$ is proposed. The second application studies the SIMP with the crowd influence, which is NP-hard, monotone, non-submodular, and inapproximable in general graphs. However, since user connections in Online Social Networks (OSNs) are not random, approximations can be obtained by leveraging the structural properties of OSNs. The modularity, denoted by $\Delta$, is proposed to measure to what degree this problem violates the submodularity. Two approximation algorithms are proposed with ratios of $\frac{1}{\Delta+2}$ and $1-e^{-1/(\Delta+1)}$, respectively. Beside the influence propagation applications, this dissertation further explores three different information propagation applications. The first application is a social network quarantine strategy, which can eliminate epidemic outbreaks with minimal isolation costs. This problem is NP-hard. An approximation algorithm with a ratio of 2 is proposed through utilizing the problem properties of feasibility and minimality. The second application is a rating prediction scheme, called DynFluid, based on the fluid dynamics. DynFluid analogizes the rating reference among the users in OSNs to the fluid flow among containers. The third application is an information cascade prediction framework: given the social current cascade and social topology, the number of propagated users at a future time slot is predicted. To reduce prediction time complexities, the spatiotemporal cascade information (a larger size of data) is decomposed to user characteristics (a smaller size of data) for subsequent predictions. All these three applications are based on the social network structure.
Temple University--Theses
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Ouellette, David M. "Shadows on the Cave Wall: The Cognitive Accuracy of Social Network Perception." VCU Scholars Compass, 2008. http://hdl.handle.net/10156/2249.

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Berg, Junker Maria Constance. "Neural correlates of romantic love and romantic attachment." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16055.

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In the field of neuroscience, being in love and feeling romantically attached to a partner is described as a dynamic process. Romantic love may be viewed as a motivational system, changing throughout time and place, fluctuating on the interest and motivation of the individual. Early memories and attachment towards a caregiver, lay the foundation for later attachment behavior, also known as attachment styles. In this thesis, an exploratory approach is present. The thesis aims to introduce and describe the neural correlates of romantic love and romantic attachment. Brain regions concerned with reward, emotion and thought processing, such as the reward circuitry network of the brain and the limbic system, are being investigated. So are other brain areas involved in romantic love and romantic attachment. Research findings suggest that brain areas responsible for affection, emotional control, learning, memory and social judgment are all involved in the complex processes of being in love and feeling romantically attached. These findings are represented by the involvement of the frontal lobe, cerebral cortex, limbic system, orbitofrontal cortex, and hippocampus, anterior cingulate cortex (ACC), ventral tegmental area (VTA), caudate tail, including the reward pathways of the brain. Distribution and regulation of neurotransmitters such as; vasopressin, oxytocin, dopamine, corticosterone and serotonin are all present in the state of romantic  attachment and romantic love. Overlapping evidence confirms the involvement of the reward circuitry network, together with the limbic system as crucial in the formation and maintenance of a romantic relationship.
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Woolford, Brittany. "Adolescent's Social Networking Use and Its Relationship to Attachment and Mental Health." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc955025/.

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Adolescents spend much of their time using the internet and electronic media. Since its inception, the use of online social networking (OSN) sites by adolescents continues to grow. With the proliferation of OSN, it is critical to examine how this activity affects psychological development, but better measurement tools are needed. As researchers struggle to keep up with this rapidly growing field, many gaps remain in the literature investigating the interrelations between adolescent's OSN use and mental health outcomes. Research examining the relationship between OSN and mental health outcomes, specifically depression and anxiety, has produced mixed results suggesting that other factors influence this association. A large research literature documents associations between attachment and mental health. Given that attachment also affects interpersonal communication, several studies have investigated links between attachment and OSN use in adult and college populations. Results indicated that even though attachment to father was independently related to anxiety and depression symptoms, it was not a significant moderator for mental health and OSN. Attachment to mother was a significant moderator for anxiety and depression and several OSN subscales. Based on this information, a greater focus on youth's interpersonal connection and social skills both online and offline may be beneficial when treating adolescents experiencing anxiety or depression.
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Dabkowski, Matthew Francis. "Using Network Science to Estimate the Cost of Architectural Growth." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/612431.

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Between 1997 and 2009, 47 major defense acquisition programs experienced cost overruns of at least 15% or 30% over their current or original baseline estimates, respectively (GAO, 2011, p. 1). Known formally as a Nunn-McCurdy breach (GAO, 2011, p. 1), the reasons for this excessive growth are myriad, although nearly 70% of the cases identified engineering and design issues as a contributing factor (GAO, 2011, p. 5). Accordingly, Congress legislatively acknowledged the need for change in 2009 with the passage of the Weapon Systems Acquisition Reform Act (WSARA, 2009), which mandated additional rigor and accountability in early life cycle (or Pre-Milestone A) cost estimation. Consistent with this effort, the Department of Defense has recently required more system specification earlier in the life cycle, notably the submission of detailed architectural models, and this has created opportunities for new approaches. In this dissertation, I describe my effort to transform one such model (or view), namely the SV-3, into computational knowledge that can be leveraged in Pre-Milestone A cost estimation and risk analysis. The principal contribution of my work is Algorithm 3-a novel, network science-based method for estimating the cost of unforeseen architectural growth in defense programs. Specifically, using number theory, network science, simulation, and statistical analysis, I simultaneously find the best fitting probability mass functions and strengths of preferential attachment for an incoming subsystem's interfaces, and I apply blockmodeling to find the SV-3's globally optimal macrostructure. Leveraging these inputs, I use Monte Carlo simulation and the Constructive Systems Engineering Cost Model to estimate the systems engineering effort required to connect a new subsystem to the existing architecture. This effort is chronicled by the five articles given in Appendices A through C, and it is summarized in Chapter 2.In addition to Algorithm 3, there are several important, tangential outcomes of this work, including: an explicit connection between Model Based System Engineering and parametric cost modeling, a general procedure for organizations to improve the measurement reliability of their early life cycle cost estimates, and several exact and heuristic methods for the blockmodeling of one-, two-, and mixed-mode networks. More generally, this research highlights the benefits of applying network science to systems engineering, and it reinforces the value of viewing architectural models as computational objects.
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Underwood, Heather, and hjocat@bigpond com. "Who goes there? : demographics, personality and attachment style of those involved in internet affairs." Swinburne University of Technology, 2005. http://adt.lib.swin.edu.au./public/adt-VSWT20051124.091812.

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The overall aim of this thesis was to explore the impact of Internet relationships on regular ongoing relationships from the point of view of those engaged in such relationships. Two studies were conducted. A sample of 75 participants, including 22 females and 53 males who were married or living in defacto relationships and ranging in age from 18 to 75 years completed an anonymous online survey for Study One. Demographic characteristics, frequency and method of communication and relationship satisfaction were investigated. Questions were asked about Internet relationship formation. Respondents were asked to gauge levels of self-disclosure within their regular ongoing relationship and their online relationship. They were also asked about the proximity and physical attractiveness of their online partner. It was found that most respondents communicated daily, were more satisfied with their Internet partner than their regular ongoing partner, considered their Internet partner physically attractive and communicated in a highly intimate manner. The purpose of the second study was to investigate the similarities and differences between the personality characteristics and attachment styles of respondents. Participants in the second study were 133 respondents who were married or living in defacto relationships, including 47 females and 86 males ranging in age from 18 years to 66 years. Respondents completed an anonymous online survey, which included measures of personality (e.g. the International Personality Item Pool, Goldberg, 1999), the Relationship Satisfaction questionnaire (Hendrick, 1988), and the Experiences in Close Relationships Scale (Brennan, Clark, & Shaver, 1998). Respondents were found to be somewhat more agreeable and conscientious, and less narcissistic than previous research had found to be the case for those individuals who engaged in face-to-face infidelity. The preoccupied attachment group was well represented, but was less differentiated from the other attachment groups than was the fearful group, who were mainly female. The personality profile and attachment style of respondents in Study Two was, therefore, found to be different in important ways from that which has been associated with face-to-face infidelity. Findings were discussed in terms of methodological implications, suggestions for future research and also implications for Counselling Psychologists.
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Books on the topic "Attachment network"

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Sinclair, Elizabeth Afua. Attachment and separation within the extended family network. Uxbridge: Brunel University, 1993.

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Wang, Lu, Kaishun Wu, and Mounir Hamdi. Attachment Transmission in Wireless Networks. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04909-0.

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International Business Machines Corporation. International Technical Support Organization, ed. IBM TS3500 tape library with System Z attachment: A practical guide to Enterprise tape drives and TS3500 tape automation. 4th ed. [Poughkeepsie, NY]: IBM, International Technical Support Organization, 2008.

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IEEE Computer Society. Technical Committee on Computer Communications. and American National Standards Institute, eds. Supplements to Carrier sense multiple access with collision detection (CSMA/CD) access method and physical layer specifications: ANSI/IEEE 802.3a-1988, medium attachment unit and baseband medium specifications, type 10BASE2 (section 10) ... : IEEE standards for local area networks. New York, NY, USA: Institute of Electrical and Electronics Engineers, 1987.

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Institute, American National Standards. Supplements to Carrier sense multiple access with collision detection (CSMA/CD) access method and physical layer specifications: ANSI/IEEE 802.3a-1988, medium attachment unit and baseband medium specifications, type 10BASE2 (section 10) ... : IEEEstandards for local area networks. New York, NY, USA: Institute of Electrical and Electronics Engineers, 1987.

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Newman, Mark. Models of network formation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805090.003.0013.

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This chapter describes models of the growth or formation of networks, with a particular focus on preferential attachment models. It starts with a discussion of the classic preferential attachment model for citation networks introduced by Price, including a complete derivation of the degree distribution in the limit of large network size. Subsequent sections introduce the Barabasi-Albert model and various generalized preferential attachment models, including models with addition or removal of extra nodes or edges and models with nonlinear preferential attachment. Also discussed are node copying models and models in which networks are formed by optimization processes, such as delivery networks or airline networks.
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Coolen, A. C. C., A. Annibale, and E. S. Roberts. Network growth algorithms. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0008.

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Growth processes are a fundamentally different approach compared to probability-driven exponential models covered in earlier chapters. This chapter studies how growth rules can be designed to mimic processes observed in the real world, and how the process can be mathematically analyzed in order to obtain information about the likely topological properties of the resulting networks. The configuration (stub joining) model is described, including a careful discussion of how bias can be introduced if backtracking is used instead of restarting if stubs join to form a self or double link. The second class of models looked at is preferential attachment. The simplest variants of this are analyzed with a master equation approach, in order to introduce this technique as a way of obtaining analytical information about the expected properties of the generated graphs. Extensive references are provided to the numerous variants and extensions of both of these models.
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Attachment Transmission in Wireless Networks. Springer International Publishing AG, 2014.

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Wu, Kaishun, Lu Wang, and Mounir Hamdi. Attachment Transmission in Wireless Networks. Springer London, Limited, 2014.

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Tavecchio, L. W. C., and M. H. van IJzendoorn. Attachment in Social Networks: Contributions to the Bowlby-Ainsworth Attachment Theory. Elsevier Science & Technology Books, 1987.

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Book chapters on the topic "Attachment network"

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Dereich, Steffen. "The Rank-One and the Preferential Attachment Paradigm." In Network Science, 43–58. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26814-5_4.

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Gillath, Omri, and Gery Karantzas. "Insights into the Formation of Attachment Bonds from a Social Network Perspective." In Bases of Adult Attachment, 131–56. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-9622-9_7.

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Hermans, Audrey, Selma Muhammad, and Jan Treur. "An Adaptive Network Model of Attachment Theory." In Computational Science – ICCS 2021, 462–75. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77967-2_39.

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Ardickas, Daumilas, and Mindaugas Bloznelis. "Clustering Coefficient of a Preferred Attachment Affiliation Network." In Lecture Notes in Computer Science, 82–95. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48478-1_6.

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Yang, Yang, Shuyuan Jin, Yang Zuo, and Jin Xu. "Online Social Network Model Based on Local Preferential Attachment." In Web Technologies and Applications, 35–46. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11119-3_4.

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Azadbakht, Keyvan, Nikolaos Bezirgiannis, and Frank S. de Boer. "Distributed Network Generation Based on Preferential Attachment in ABS." In SOFSEM 2017: Theory and Practice of Computer Science, 103–15. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51963-0_9.

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Shang, Rang-An, Yu-Chen Chen, and Je-Wei Chang. "Individual Attachment Style, Self-disclosure, and How People use Social Network." In Communications in Computer and Information Science, 45–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48319-0_4.

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Abbasi, Alireza, and Liaquat Hossain. "Investigating Attachment Behavior of Nodes during Evolution of a Complex Social Network:." In Knowlege-Based and Intelligent Information and Engineering Systems, 256–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23863-5_26.

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Shera, Shailendra Singh, Shraddha Sahu, and Rathindra Mohan Banik. "Artificial Neural Network Modeling to Predict Bacterial Attachment on Composite Biopolymeric Scaffold." In Advances in Polymer Sciences and Technology, 65–74. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2568-7_7.

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Markovich, Natalia M., and Udo R. Krieger. "The PageRank Vector of a Scale-Free Web Network Growing by Preferential Attachment." In Lecture Notes in Computer Science, 24–31. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92507-9_3.

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Conference papers on the topic "Attachment network"

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Rinta-aho, Teemu, Rui Campos, Andras Mehes, Ulrike Meyer, Joachim Sachs, and Goran Selander. "Ambient Network Attachment." In 2007 16th IST Mobile and Wireless Communications Summit. IEEE, 2007. http://dx.doi.org/10.1109/istmwc.2007.4299184.

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Sosnowska, Jadwiga, and Oskar Skibski. "Attachment Centrality for Weighted Graphs." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/59.

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Measuring how central nodes are in terms of connecting a network has recently received increasing attention in the literature. While a few dedicated centrality measures have been proposed, Skibski et al. [2016] showed that the Attachment Centrality is the only one that satisfies certain natural axioms desirable for connectivity. Unfortunately, the Attachment Centrality is defined only for unweighted graphs which makes this measure ill-fitted for various applications. For instance, covert networks are typically weighted, where the weights carry additional intelligence available about criminals or terrorists and the links between them. To analyse such settings, in this paper we extend the Attachment Centrality to node-weighted and edge-weighted graphs. By an axiomatic analysis, we show that the Attachment Centrality is closely related to the Degree Centrality in weighted graphs.
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Atwood, James, Bruno Ribeiro, and Don Towsley. "Efficient network generation under general preferential attachment." In the 23rd International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2567948.2579357.

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Kjallman, J. "Attachment to a Native Publish/Subscribe Network." In 2009 IEEE International Conference on Communications Workshops. IEEE, 2009. http://dx.doi.org/10.1109/iccw.2009.5207971.

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Miao Li, Hui Wang, and Jiahai Yang. "Flattening and preferential attachment in the internet evolution." In 2012 14th Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2012. http://dx.doi.org/10.1109/apnoms.2012.6356080.

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Cloteaux, Brian, and Vladimir Marbukh. "SIS Contagion Avoidance on a Network Growing by Preferential Attachment." In the 2nd Joint International Workshop. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3327964.3328502.

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Choi, Jin Seek. "Signaling and Control Requirements of Network Attachment Control Function for NGN." In COIN-NGNCON 2006 - The Joint International Conference on Optical Internet and Next Generation Network. IEEE, 2006. http://dx.doi.org/10.1109/coinngncon.2006.4454499.

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Bhattacharya, Arpita, Sourav Das, Avijit Gayen, and Nilotpal Chakraborty. "HAP: Hierarchical attachment process for mobile nodes in nested network mobility." In 2017 IEEE Region 10 Symposium (TENSYMP). IEEE, 2017. http://dx.doi.org/10.1109/tenconspring.2017.8070047.

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Liu, Chang, Junhong Guo, Peiqiang Liu, and Wangmin Cai. "Identifying protein complexes based on core-attachment from weighted dynamic network." In International Conference on Cloud Computing, Internet of Things, and Computer Applications, edited by Warwick Powell and Amr Tolba. SPIE, 2022. http://dx.doi.org/10.1117/12.2642635.

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Chen, Yaoran, Yuanyuan Zhu, Ming Zhong, and Juan Liu. "COMNA: Core-attachment based protein complex detection via multiple network alignment." In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021. http://dx.doi.org/10.1109/bibm52615.2021.9669342.

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Reports on the topic "Attachment network"

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Aboba, B., J. Carlson, and S. Cheshire. Detecting Network Attachment in IPv4 (DNAv4). RFC Editor, March 2006. http://dx.doi.org/10.17487/rfc4436.

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Daley, G. Goals of Detecting Network Attachment in IPv6. RFC Editor, August 2005. http://dx.doi.org/10.17487/rfc4135.

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Krishnan, S., and G. Daley. Simple Procedures for Detecting Network Attachment in IPv6. RFC Editor, November 2010. http://dx.doi.org/10.17487/rfc6059.

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Montavont, N., E. Njedjou, and S. Veerepalli. Link-Layer Event Notifications for Detecting Network Attachments. Edited by S. Krishnan and A. Yegin. RFC Editor, August 2007. http://dx.doi.org/10.17487/rfc4957.

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Chen-Zion, Ayal, and James Rauch. History Dependence, Cohort Attachment, and Job Referrals in Networks of Close Relationships. Cambridge, MA: National Bureau of Economic Research, October 2019. http://dx.doi.org/10.3386/w26358.

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Perumalla, Kalyan S., and Maksudul Alam. Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model. Office of Scientific and Technical Information (OSTI), October 2017. http://dx.doi.org/10.2172/1399438.

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