Social Networks最新文献

{"title":"Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure","authors":"Axel Browne ,&nbsp;David Butts ,&nbsp;Edgar Jaramillo-Rodriguez ,&nbsp;Nidhi Parikh ,&nbsp;Geoffrey Fairchild ,&nbsp;Zach Needell ,&nbsp;Cristian Poliziani ,&nbsp;Tom Wenzel ,&nbsp;Timothy C. Germann ,&nbsp;Sara Del Valle","doi":"10.1016/j.socnet.2024.06.003","DOIUrl":"https://doi.org/10.1016/j.socnet.2024.06.003","url":null,"abstract":"<div><p>Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as <em>sensor selection</em>. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 122-132"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378873324000364/pdfft?md5=fac337893b941443ddb1a4018c7151cf&pid=1-s2.0-S0378873324000364-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141596440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Symbolic association networks: A case study of orchestral programming’s effect on the reputation of composers","authors":"L.E.A. Braden ,&nbsp;Ju Hyun Park ,&nbsp;Jay Lee","doi":"10.1016/j.socnet.2024.08.001","DOIUrl":"10.1016/j.socnet.2024.08.001","url":null,"abstract":"<div><p>A type of symbolic association network for the development of reputation is described and tested. Associations between people in these networks are not based on individual interaction, but rather are created by “reputational entrepreneurs” based on perceived symbolic association between people. We argue the intent of this type of connection is to add to the reputational information about those connected and we test whether a network of such associations influence cultural recognition. To do this, we use dyadic connections between classical music composers created by conductors for orchestra performance and determine whether a composer’s symbolic association network (SAN) aids recognition in publications. We find SANs to have a significant impact on the extent of reputational recognition, even when holding a composer’s individual status achievements constant. Composers with a large symbolic association network and those who bridge unconnected composers tend to receive more recognition. We discuss the influence of symbolic association networks on perception of reputational significance. We suggest SANs may advance research in reputation and culture particularly when considering actors whose reputation is active beyond their work or lifetime, such as artists, writers, musicians, and historical figures.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 198-208"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378873324000431/pdfft?md5=272aa0fc9439eae463d339ace55e0d19&pid=1-s2.0-S0378873324000431-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141962908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “How adolescents’ popularity perceptions change: Measuring interactions between popularity and friendship networks” [Soc. Netw. 78 (2024) 1462]","authors":"Ana Bravo ,&nbsp;Robert W. Krause ,&nbsp;Rosario Ortega-Ruiz ,&nbsp;Eva M. Romera","doi":"10.1016/j.socnet.2024.07.004","DOIUrl":"10.1016/j.socnet.2024.07.004","url":null,"abstract":"","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Page 153"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S037887332400042X/pdfft?md5=bb0bceb57cd4d24d2974e35feee641ad&pid=1-s2.0-S037887332400042X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141952304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Categorical closure: Transitivity and identities in longitudinal networks","authors":"Chen-Shuo Hong ,&nbsp;Anthony Paik ,&nbsp;Swethaa Ballakrishnen ,&nbsp;Carole Silver ,&nbsp;Steven Boutcher","doi":"10.1016/j.socnet.2024.06.004","DOIUrl":"https://doi.org/10.1016/j.socnet.2024.06.004","url":null,"abstract":"<div><p>This research examines whether categorical closure – an increased tendency for closure in homogeneous triads – matters for tie formation and tie persistence. We utilized 2019–2020 panel data on students’ networks at three law schools and employed separable temporal exponential random graph models to examine whether closed triads with shared identities were more likely to form and to persist over time. We also investigated whether closed triads based on shared organizational assignments were associated with lower likelihoods of tie formation and tie persistence over time. Results supported the notion that law students were more likely to form homogeneous closed triads based on shared categories, particularly family background, gender, and race, while closed triads based on organizational assignments were less likely. Closed triads tended to persist over time, but there was some support for the notion that homogeneous closed triads based on family background, college rank, and sexuality were more durable. This study highlights categorical closure as an additional network mechanism giving rise to homogenous groups.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 76-92"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141540254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exponential random graph models and pendant-triangle statistics","authors":"Philippa E. Pattison ,&nbsp;Garry L. Robins ,&nbsp;Tom A.B. Snijders ,&nbsp;Peng Wang","doi":"10.1016/j.socnet.2024.07.002","DOIUrl":"10.1016/j.socnet.2024.07.002","url":null,"abstract":"<div><p>The paper builds on the framework proposed by Pattison and Snijders (2012) for specifying exponential random graph models (ERGMs) for social networks. We briefly review the two-dimensional hierarchy of potential dependence structures for network tie variables that they outlined and provide proofs of the relationships among the model forms and of the nature of their sufficient statistics, noting that models in the hierarchy have the potential to reflect the outcome of processes of cohesion, closure, boundary and bridge formation and path creation over short or longer network distances. We then focus on the so-called <em>partial inclusion</em> dependence assumptions among network tie variables and the <em>pendant-triangle</em>, or <em>paw</em>, statistics to which they give rise, and illustrate their application in an empirical setting. We argue that the partial inclusion assumption leads to models that can reflect processes of boundary and bridge formation and that the model hierarchy provides a broad and useful framework for the statistical analysis of network data. We demonstrate in the chosen setting that pendant-triangle (or paw) effects, in particular, lead to a marked improvement in goodness-of-fit and hence add a potentially valuable capacity for modelling social networks.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 187-197"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378873324000406/pdfft?md5=4736b23e85701c944f6c79997f624b51&pid=1-s2.0-S0378873324000406-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141962568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coming into relations: How communication reveals and persuades relational decisions","authors":"Daniel A. McFarland ,&nbsp;David Broska ,&nbsp;Vinodkumar Prabhakaran ,&nbsp;Dan Jurafsky","doi":"10.1016/j.socnet.2024.05.003","DOIUrl":"https://doi.org/10.1016/j.socnet.2024.05.003","url":null,"abstract":"<div><p>Coming into relations involves exiting a state of indecision and deciding whether to relate or not. Little research has focused on these initial moments, the communications involved, and the making of a relational decision. We study this process using 947 speed dating encounters, their minute-by-minute communications, and the reported timing of relational decisions. We show that certain forms of communication reveal an actor’s relational state of being undecided, desiring a relation, or not desiring a relation (<em>revealing signals</em>). For example, indecision corresponds with indirect and ambiguous communication (negative facework); desiring a relation entails positive, excited, and entraining communication (positive facework); and not desiring a relation involves routine talk. We also show that certain forms of communication persuade persons to transition relational states, moving beyond their indecision and coming to a relational decision (<em>persuasive signals</em>). Interestingly, only some revealing signals are persuasive and bring about corresponding relational decisions in others. These tend to be <em>clear signals</em> that cannot be attributed to the situation or politeness. Last, some signals persuade relational decisions without corresponding to a relational state. These <em>performative signals</em> are select forms of ambiguous communication that place the speaker in an advantaged position within social exchange.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 57-75"},"PeriodicalIF":3.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141423370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A clan detector algorithm to identify independent clans in the kinship networks of elite family dynasties","authors":"Niccolò Giorgio Armandola","doi":"10.1016/j.socnet.2024.07.003","DOIUrl":"10.1016/j.socnet.2024.07.003","url":null,"abstract":"<div><p>The sociology of elites has long considered families as the unit of analysis in studies of power dynamics between elite dynasties and their transmission of wealth and prestige over generations. However, the assumption that families are cohesive units with common goals and agendas does not hold, especially for large and powerful family dynasties. Internal conflicts and clan rivalries throughout history suggest that independent clans, rather than families, are the more appropriate level for aggregation. The increasing availability of large-scale genealogical datasets and advances in social network analysis allow this more fine-grained perspective to be implemented even without historical documentation on observed clan structures. This paper builds on socio-anthropological conceptualizations of kinship and on hierarchical clustering techniques to present a new method for identifying independent clans within families that relies only on network-dependent terms. I use simulated data and an empirical kinship network of families of early modern Basel, Switzerland to compare a clan detector algorithm’s performance with common community detection techniques. The historical accuracy of the clan structures detected is further assessed with various status indicators. The analyses show that the proposed clan detector algorithm is more suitable for identifying historically accurate clans than the traditional approaches. The application of the new method to the kinship network of Basel families sheds light on the city’s stratification into high- and low-status societies in which elite families were also divided into privileged and less privileged clans.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 168-186"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378873324000418/pdfft?md5=4c9af084a15189ae5f11fbbb3988ff56&pid=1-s2.0-S0378873324000418-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Occupational selection and the reliability of position generator measures of social capital","authors":"Peter V. Marsden,&nbsp;Derick S. Baum","doi":"10.1016/j.socnet.2024.05.001","DOIUrl":"https://doi.org/10.1016/j.socnet.2024.05.001","url":null,"abstract":"<div><p>This article investigates how variation in the social positions (occupations) presented by a position generator (PG) instrument affects the reliability of egocentric network measures based on PG data. We modify the split-half design employed in Verhaeghe et al.’s (2013) study of university students for use with already-existing PG data on a national adult population. After replicating that study, we examine how reliability varies with the relational criterion (<em>e.g.</em>, friendship) that links an individual to an occupation and with the number of occupations in a PG. We find that most PG measures are only modestly reliable (<em>i.e.</em>, are relatively sensitive to occupational selection), but our absolute assessment of their reliability (given instrument length) is somewhat more optimistic than that of the prior study. Extensity (the number of positions with which a subject has contact) is the most reliable measure, composition measures based on social class groupings are next, and those that involve socioeconomic standing or prestige scores are least reliable. Deeming someone to be connected to an occupation using an acquaintance criterion yields more reliable measures than requiring a stronger level of connectivity. PG measures based on longer (<em>i.e.</em>, more occupations) instruments have higher reliability, and projections for longer PGs suggest that including 20 occupations could measure extensity and counts of contacts in some class groupings with adequate reliability; but other class composition measures and all measures involving socioeconomic standing or prestige scores would require 30 or more.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 34-47"},"PeriodicalIF":3.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141323322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interaction dynamics in classroom group work","authors":"Tomáš Lintner ,&nbsp;Tomáš Diviák ,&nbsp;Barbora Nekardová","doi":"10.1016/j.socnet.2024.05.002","DOIUrl":"https://doi.org/10.1016/j.socnet.2024.05.002","url":null,"abstract":"<div><p>Group work in classrooms is employed by teachers across all levels of education. For group work to be effective, all students should participate equally. Why some students engage in interaction and how group size and composition influence interaction dynamics is a research gap. We employed dynamic actor-oriented models on a sample of 145 Czech lower-secondary students in 62 small groups and pooled the results from the groups with a meta-analytical procedure. We found bursty behavior resulting from endogenous structural mechanisms of reciprocity, transitivity, cyclicity, and preferential attachment. Students gave preference to initiating interactions with those they initiated interactions with before and off-task interaction contributed to the development of on-task interaction. Students strongly preferred interactions with friends. Those students who talked a lot during regular whole-classroom lessons and students with high levels of literacy tended to both initiate and receive more interactions in group work, and students similar in these attributes preferred to interact with each other. Group size did not affect preferential attachment tendencies in interaction, but smaller groups made the effect of friendship ties on interactions stronger, and communication group norms shifted with changing group composition. Our study shows the suitability of dynamic actor-oriented models for studying interaction in education and small groups.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 14-24"},"PeriodicalIF":3.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378873324000303/pdfft?md5=98134ddd6ccd6bc98f8b45dfc4929df8&pid=1-s2.0-S0378873324000303-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141250963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling non-linear effects with neural networks in Relational Event Models","authors":"Edoardo Filippi-Mazzola,&nbsp;Ernst C. Wit","doi":"10.1016/j.socnet.2024.05.004","DOIUrl":"https://doi.org/10.1016/j.socnet.2024.05.004","url":null,"abstract":"<div><p>Dynamic networks offer an insight of how relational systems evolve. However, modeling these networks efficiently remains a challenge, primarily due to computational constraints, especially as the number of observed events grows. This paper addresses this issue by introducing the Deep Relational Event Additive Model (DREAM) as a solution to the computational challenges presented by modeling non-linear effects in Relational Event Models (REMs). DREAM relies on Neural Additive Models to model non-linear effects, allowing each effect to be captured by an independent neural network. By strategically trading computational complexity for improved memory management and leveraging the computational capabilities of graphic processor units (GPUs), DREAM efficiently captures complex non-linear relationships within data. This approach demonstrates the capability of DREAM in modeling dynamic networks and scaling to larger networks. Comparisons with traditional REM approaches showcase DREAM superior computational efficiency. The model potential is further demonstrated by an examination of the patent citation network, which contains nearly 8 million nodes and 100 million events.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"79 ","pages":"Pages 25-33"},"PeriodicalIF":3.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378873324000327/pdfft?md5=1df5a4529750bdad68d7db5d742c29eb&pid=1-s2.0-S0378873324000327-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141292115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}