C. Yuan, Gerald C. Kane, Jason M. Fletcher, Ingrid M. Nembhard
Abstract The successful implementation of technology often hinges on individual beliefs about the innovation being introduced. Little is known about how social networks shape these beliefs. In this study, we examine: (1) whether individual beliefs about technology are influenced by the beliefs of their peers within their social networks (network content); and (2) whether changes in the composition of the social network over time (network churn) moderates the effect of peer beliefs on individual beliefs. We offer and test hypotheses about these relationships using longitudinal social network survey data from hospital staff collected 2 – 4 months before (N = 256) and 3 – 5 months after (N = 284) the implementation of a new electronic medical record (EMR) system at a large, academic hospital. Our findings suggest that peer beliefs about new technology significantly and negatively affect individual beliefs about technology in the early stages of EMR implementation. We also find that the effect of peer beliefs on individual beliefs is stronger in more stable social networks (i.e., social networks that experience few tie deletions over time) and weaker in less stable social networks (i.e., social networks that experience many tie deletions over time). Our study examines social influence in a novel context – the implementation of EMR systems in the hospital setting – and extends network theory by conceptualizing network churn as a moderating variable that may amplify or dampen the effect of networks.
{"title":"The Role of Social Influence and Network Churn in Beliefs about Electronic Medical Record Technology","authors":"C. Yuan, Gerald C. Kane, Jason M. Fletcher, Ingrid M. Nembhard","doi":"10.21307/joss-2019-005","DOIUrl":"https://doi.org/10.21307/joss-2019-005","url":null,"abstract":"Abstract The successful implementation of technology often hinges on individual beliefs about the innovation being introduced. Little is known about how social networks shape these beliefs. In this study, we examine: (1) whether individual beliefs about technology are influenced by the beliefs of their peers within their social networks (network content); and (2) whether changes in the composition of the social network over time (network churn) moderates the effect of peer beliefs on individual beliefs. We offer and test hypotheses about these relationships using longitudinal social network survey data from hospital staff collected 2 – 4 months before (N = 256) and 3 – 5 months after (N = 284) the implementation of a new electronic medical record (EMR) system at a large, academic hospital. Our findings suggest that peer beliefs about new technology significantly and negatively affect individual beliefs about technology in the early stages of EMR implementation. We also find that the effect of peer beliefs on individual beliefs is stronger in more stable social networks (i.e., social networks that experience few tie deletions over time) and weaker in less stable social networks (i.e., social networks that experience many tie deletions over time). Our study examines social influence in a novel context – the implementation of EMR systems in the hospital setting – and extends network theory by conceptualizing network churn as a moderating variable that may amplify or dampen the effect of networks.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"29 - 49"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47097594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01DOI: 10.1007/978-1-4939-7131-2_394
M. Huisman, Robert W. Krause
{"title":"Imputation of Missing Network Data","authors":"M. Huisman, Robert W. Krause","doi":"10.1007/978-1-4939-7131-2_394","DOIUrl":"https://doi.org/10.1007/978-1-4939-7131-2_394","url":null,"abstract":"","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"2 1","pages":"707-715"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-1-4939-7131-2_394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"51056689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Brusco, Hannah J. Stolze, Michaela Hoffman, D. Steinley, P. Doreian
Abstract Deterministic blockmodeling of a two-mode binary network matrix based on structural equivalence is a well-known problem in the social network literature. Whether implemented in a standalone fashion, or embedded within a metaheuristic framework, a popular relocation heuristic (RH) has served as the principal solution tool for this problem. In this paper, we establish that a two-mode KL-median heuristic (TMKLMedH) seeks to optimize the same criterion as the RH for deterministic blockmodeling. The TMKLMedH runs much faster than the RH, so many more restarts of the TMKLMedH can be accomplished when the two methods are constrained to the same time limit. Three computational comparisons of RH and TMKLMedH were conducted using both synthetic and real-world networks. In all three comparisons, the superiority of TMKLMedH was unequivocal.
{"title":"Deterministic Blockmodeling of Two-Mode Binary Networks Using a Two-Mode KL-Median Heuristic","authors":"M. Brusco, Hannah J. Stolze, Michaela Hoffman, D. Steinley, P. Doreian","doi":"10.21307/JOSS-2018-007","DOIUrl":"https://doi.org/10.21307/JOSS-2018-007","url":null,"abstract":"Abstract Deterministic blockmodeling of a two-mode binary network matrix based on structural equivalence is a well-known problem in the social network literature. Whether implemented in a standalone fashion, or embedded within a metaheuristic framework, a popular relocation heuristic (RH) has served as the principal solution tool for this problem. In this paper, we establish that a two-mode KL-median heuristic (TMKLMedH) seeks to optimize the same criterion as the RH for deterministic blockmodeling. The TMKLMedH runs much faster than the RH, so many more restarts of the TMKLMedH can be accomplished when the two methods are constrained to the same time limit. Three computational comparisons of RH and TMKLMedH were conducted using both synthetic and real-world networks. In all three comparisons, the superiority of TMKLMedH was unequivocal.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"19 1","pages":"1 - 22"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49598664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract How do sex risk and protection change over the course of a relationship? It is often claimed that protection generally declines over the course of relationships. This 3-year longitudinal study examines 412 new sexual relationships described by 126 adult participants and tests this claim. Analyses identify four relationship trajectories: only 15% of new sex relationships show a declining trajectory of protection; another 12% show only a temporary decline. Population average analyses previously interpreted to show a decline in protection are shown here to be is largely explained by the attrition of the low trust, high protection relationships that creates the association between higher trust and lower protection. The long-term relationships turn out mostly not to have been low trust, high protection relationships at the start. Instead they have mostly always been high trust, low protection relationships. Other proposed theories, notably self-protection and power theories are not supported, while drug use is supported for 15% of the sample. Only trust and secondary partners successfully account for the observed patterns of protection and attrition. Actors seem to be concerned to protect their partners, using more protection with a secondary partner who might provide a risk to the primary partner.
{"title":"Risk in New Sexual Relationships: Trajectories of Protection*","authors":"D. Bell","doi":"10.21307/joss-2018-008","DOIUrl":"https://doi.org/10.21307/joss-2018-008","url":null,"abstract":"Abstract How do sex risk and protection change over the course of a relationship? It is often claimed that protection generally declines over the course of relationships. This 3-year longitudinal study examines 412 new sexual relationships described by 126 adult participants and tests this claim. Analyses identify four relationship trajectories: only 15% of new sex relationships show a declining trajectory of protection; another 12% show only a temporary decline. Population average analyses previously interpreted to show a decline in protection are shown here to be is largely explained by the attrition of the low trust, high protection relationships that creates the association between higher trust and lower protection. The long-term relationships turn out mostly not to have been low trust, high protection relationships at the start. Instead they have mostly always been high trust, low protection relationships. Other proposed theories, notably self-protection and power theories are not supported, while drug use is supported for 15% of the sample. Only trust and secondary partners successfully account for the observed patterns of protection and attrition. Actors seem to be concerned to protect their partners, using more protection with a secondary partner who might provide a risk to the primary partner.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"19 1","pages":"1 - 26"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67666448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Adolescents who experience a pregnancy often face educational and economical difficulties later in life. One factor that has been found to improve outcomes for pregnant teens is access to social supports. Inopportunely, teen pregnancy presents social obstacles, and cross-sectional analysis has found pregnant teens have fewer friendships than their non-pregnant counterparts. However, longitudinal work has yet to explore network change after a pregnancy. This study uses multiple network modeling techniques to follow the social networks of a group of girls who become pregnant between waves of the Add Health survey. Pregnant teens were found to maintain fewer friendships between time points than peers. Whole school network maps suggest that in some schools teens move to more peripheral network positions following pregnancy. These preliminary findings suggest that the relationship between social network change and pregnancy may vary depending on school environment; future work is needed to better understand how school contexts may change the social outcomes of pregnant girls.
{"title":"Dynamics of Social Networks Following Adolescent Pregnancy","authors":"E. Humberstone","doi":"10.21307/joss-2018-009","DOIUrl":"https://doi.org/10.21307/joss-2018-009","url":null,"abstract":"Abstract Adolescents who experience a pregnancy often face educational and economical difficulties later in life. One factor that has been found to improve outcomes for pregnant teens is access to social supports. Inopportunely, teen pregnancy presents social obstacles, and cross-sectional analysis has found pregnant teens have fewer friendships than their non-pregnant counterparts. However, longitudinal work has yet to explore network change after a pregnancy. This study uses multiple network modeling techniques to follow the social networks of a group of girls who become pregnant between waves of the Add Health survey. Pregnant teens were found to maintain fewer friendships between time points than peers. Whole school network maps suggest that in some schools teens move to more peripheral network positions following pregnancy. These preliminary findings suggest that the relationship between social network change and pregnancy may vary depending on school environment; future work is needed to better understand how school contexts may change the social outcomes of pregnant girls.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"19 1","pages":"1 - 34"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49507830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract How do civilians select internal displacement destinations during conflict? Existing research emphasizes the value of cascades as a guide to making these difficult decisions. Cascades may involve civilians following people in their social networks (community cascades), people with similar characteristics (co-ethnic cascades), or the crowd in general (herd cascades). Analyses relying upon interview or regression-based methodological approaches face substantial challenges in identifying the prevalence of, and relationship between, each type of cascade. While interview-based approaches can incorporate location characteristics and movement patterns, they struggle with assessing aggregate trends. Meanwhile, regression-based approaches can assess aggregate trends, but they struggle with incorporating location characteristics and movement patterns. Exponential Random Graph Models (ERGMs) that conceive of locations as nodes in a network and movements between those locations as ties can overcome these challenges and assess aggregate trends while incorporating location characteristics and movement patterns. This paper demonstrates the utility of this approach using data from UNHCR on internal displacement in Somalia from 2007-2013. Results reveal that herd cascades only form at high displacement levels, co-ethnic cascades form at medium and high displacement levels, and community cascades form at all displacement levels. Therefore, cascades provide stronger guides for displacement-related decisions as civilians switch from following the crowd in general to following those with similar characteristics to following social ties.
{"title":"Using ERGMs to Disaggregate Displacement Cascades*","authors":"J. Schon","doi":"10.21307/JOSS-2018-006","DOIUrl":"https://doi.org/10.21307/JOSS-2018-006","url":null,"abstract":"Abstract How do civilians select internal displacement destinations during conflict? Existing research emphasizes the value of cascades as a guide to making these difficult decisions. Cascades may involve civilians following people in their social networks (community cascades), people with similar characteristics (co-ethnic cascades), or the crowd in general (herd cascades). Analyses relying upon interview or regression-based methodological approaches face substantial challenges in identifying the prevalence of, and relationship between, each type of cascade. While interview-based approaches can incorporate location characteristics and movement patterns, they struggle with assessing aggregate trends. Meanwhile, regression-based approaches can assess aggregate trends, but they struggle with incorporating location characteristics and movement patterns. Exponential Random Graph Models (ERGMs) that conceive of locations as nodes in a network and movements between those locations as ties can overcome these challenges and assess aggregate trends while incorporating location characteristics and movement patterns. This paper demonstrates the utility of this approach using data from UNHCR on internal displacement in Somalia from 2007-2013. Results reveal that herd cascades only form at high displacement levels, co-ethnic cascades form at medium and high displacement levels, and community cascades form at all displacement levels. Therefore, cascades provide stronger guides for displacement-related decisions as civilians switch from following the crowd in general to following those with similar characteristics to following social ties.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"19 1","pages":"1 - 40"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48344592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The main aim of this study is twofold: first, to examine the underlying structure of coauthorship in Indian economics; and second, to explore the link between the participation in scientific collaborations and academic visibility. We decipher the structure of co-authorship by presenting collaboration networks of scholars who published articles in six Indian economics journals during 1966-2005, which is split into four windows: 1966-75, 1976-85, 1986-95, and 1996-2005. In this study, the following social network measures are applied: the size of the network, the size of the main component, average degree, path length, and clustering coefficient. The study presents the following three features of Indian economics: first, a substantial proportion of Indian authors are isolated, albeit declining very slowly over a period of time; second, it appears that the structure of scholarly collaboration in Indian economics is highly fragmented, and the observed size of main components accounts for a small proportion of the total authors; third, and more importantly, the size and composition of co-authorship networks presented in the paper seldom impact the scientific visibility of authors.
{"title":"The Structure of Collaboration Networks: An Illustration of Indian Economics","authors":"M. Krishna, G. Paul","doi":"10.21307/JOSS-2018-001","DOIUrl":"https://doi.org/10.21307/JOSS-2018-001","url":null,"abstract":"Abstract The main aim of this study is twofold: first, to examine the underlying structure of coauthorship in Indian economics; and second, to explore the link between the participation in scientific collaborations and academic visibility. We decipher the structure of co-authorship by presenting collaboration networks of scholars who published articles in six Indian economics journals during 1966-2005, which is split into four windows: 1966-75, 1976-85, 1986-95, and 1996-2005. In this study, the following social network measures are applied: the size of the network, the size of the main component, average degree, path length, and clustering coefficient. The study presents the following three features of Indian economics: first, a substantial proportion of Indian authors are isolated, albeit declining very slowly over a period of time; second, it appears that the structure of scholarly collaboration in Indian economics is highly fragmented, and the observed size of main components accounts for a small proportion of the total authors; third, and more importantly, the size and composition of co-authorship networks presented in the paper seldom impact the scientific visibility of authors.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"18 1","pages":"1 - 19"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46162508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Among the many centrality indices used to detect structures of actors’ positions in networks is the use of the first eigenvector of an adjacency matrix that captures the connections among the actors. This research considers the seeming pervasive current practice of using only the first eigenvector. It is shows that, as in other statistical applications of eigenvectors, subsequent vectors can also contain illuminating information. Several small examples, and Freeman’s EIES network, are used to illustrate that while the first eigenvector is certainly informative, the second (and subsequent) eigenvector(s) can also be equally tractable and informative.
{"title":"Eigenvector Centrality: Illustrations Supporting the Utility of Extracting More Than One Eigenvector to Obtain Additional Insights into Networks and Interdependent Structures","authors":"D. Iacobucci, Rebecca McBride, Deidre Popovich","doi":"10.21307/JOSS-2018-003","DOIUrl":"https://doi.org/10.21307/JOSS-2018-003","url":null,"abstract":"Abstract Among the many centrality indices used to detect structures of actors’ positions in networks is the use of the first eigenvector of an adjacency matrix that captures the connections among the actors. This research considers the seeming pervasive current practice of using only the first eigenvector. It is shows that, as in other statistical applications of eigenvectors, subsequent vectors can also contain illuminating information. Several small examples, and Freeman’s EIES network, are used to illustrate that while the first eigenvector is certainly informative, the second (and subsequent) eigenvector(s) can also be equally tractable and informative.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"75 9","pages":"1 - 23"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41264955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract As human beings, we understand and make sense of the social world using social cognition. Social cognitions are cognitive processes through which we understand, process, and recall our interactions with others. Most agent-based models do not account for social cognition; rather, they either provide detailed models of task-related cognition or model many actors and focus on social processes. In general, the more cognitively realistic the models, the less they explain human social behavior and the more computationally expensive it is to model a single agent. In contrast, in this research an agent-based model containing an explicit model of social cognition is developed. Results from this model demonstrate that adding social cognition both improves the model veridicality and decreases computation costs.
{"title":"The Power of Social Cognition","authors":"G. Morgan, K. Joseph, Kathleen M. Carley","doi":"10.21307/JOSS-2018-002","DOIUrl":"https://doi.org/10.21307/JOSS-2018-002","url":null,"abstract":"Abstract As human beings, we understand and make sense of the social world using social cognition. Social cognitions are cognitive processes through which we understand, process, and recall our interactions with others. Most agent-based models do not account for social cognition; rather, they either provide detailed models of task-related cognition or model many actors and focus on social processes. In general, the more cognitively realistic the models, the less they explain human social behavior and the more computationally expensive it is to model a single agent. In contrast, in this research an agent-based model containing an explicit model of social cognition is developed. Results from this model demonstrate that adding social cognition both improves the model veridicality and decreases computation costs.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":" ","pages":"1 - 23"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42414457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This study analyzed the e-mail exchange network of participants of a national dating website. The investigation examined whether aggregated partner preferences give rise to distinct, “invisible,” clusters in online dating networks that structure dating opportunities and result in homophilous subgroups. The findings identified and visualized the ten largest network clusters of participants who interacted with each other and examined the dater characteristics most responsible for cluster membership. Rated attractiveness and age were the strongest cluster correlates, whereas education and race were relatively uncommon determinants. In sum, daters’ interdependent actions created aggregate communities unseen by the users themselves, but no less influential for dating opportunities, that were based more on attractiveness and age than on race and education.
{"title":"The Invisible Contours of Online Dating Communities: A Social Network Perspective","authors":"Diane H Felmlee, D. Kreager","doi":"10.21307/JOSS-2018-004","DOIUrl":"https://doi.org/10.21307/JOSS-2018-004","url":null,"abstract":"Abstract This study analyzed the e-mail exchange network of participants of a national dating website. The investigation examined whether aggregated partner preferences give rise to distinct, “invisible,” clusters in online dating networks that structure dating opportunities and result in homophilous subgroups. The findings identified and visualized the ten largest network clusters of participants who interacted with each other and examined the dater characteristics most responsible for cluster membership. Rated attractiveness and age were the strongest cluster correlates, whereas education and race were relatively uncommon determinants. In sum, daters’ interdependent actions created aggregate communities unseen by the users themselves, but no less influential for dating opportunities, that were based more on attractiveness and age than on race and education.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"18 1","pages":"1 - 28"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49494270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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