Combining qualitative, quantitative and structural dimensions in a longitudinal perspective. The case of network influence

Bidart, Claire; Cacciuttolo, Patrice

doi:10.1007/s11135-012-9667-6

Cited by 14 publications

(7 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Research suggests that between-ego differences are much less significant contributors to patterns of alter loss than are between-tie differences (e.g., van Duijin et al 1999;Marin and Hampton, 2019), but a few attributes do stand out. People undergoing life transitions-marriage, widowhood, graduation, moving, retirement and nearing the end of life-report more drops and more churn generally (e.g., Badawy, et al, 2018;Bidart and Cacciuttolo, 2013;Bidart and Lavenu, 2005;Bidart, et al, 2011;Bloem, et al, 2008;Carstensen, et al, 1999;Cornwell et al, 2014;Lang, 2000;Mollenhorst, 2014;Schafer and Vargas, 2016;Small, et al, 2015;van Dujian, et al, 1999;Wellman et al, 1997). Thus, both young and very elderly adults tend to have high drop rates.…”

Section: Which Egos Are Likeliest To Keep Ties or Drop Ties?mentioning

confidence: 99%

Who is dropped and why? Methodological and substantive accounts for network loss

Fischer

Offer

2020

Social Networks

View full text Add to dashboard Cite

High rates of egocentric network turnover are frequently observed but not well explained. About 1,000 respondents to the UCNets survey named an average of 10 names in each of two waves a year apart. Consistent with prior studies, respondents in wave 2 failed to relist about half of the names they provided in wave 1. Asked why, respondents explained that they had forgotten the alter for about 40 percent of the missing names. Other common answers, such as no "occasion... to be in touch," also suggest that the true rate of alters being dropped is probably under 20 percent. Multilevel logit models identified the predictors of alters being dropped (neither relisted nor forgotten) versus retained. Immediate kin were likeliest to be retained and roommates, coworkers, and acquaintances to be dropped. Alters who provided companionship, confiding, advice, and emergency help were especially likely to be retained, as were those to whom respondents felt close. Little about the respondents themselves affected drop rates: having moved recently, having a close friend die, or having had an important relationship break up. Results are consistent with the argument that a tie's degree of constraint (notably being close family) and its balance of rewards determine the likelihood of it being dropped or demoted. Who is Dropped and Why? Methodological and Substantive Accounts for Network Loss Panel studies of egocentric networks commonly report a paradox: Respondents report much turnover among their alters-typically, about half of those named are not renamed-and yet respondents' repopulated networks display notable constancy in traits such as size, composition, supportiveness, and structure (see review below). Our purpose here is to expand our understanding of this phenomena by focusing on the first part of this process: whom respondents drop. We use two waves of UCNets, a survey that administered many name-eliciting questions to about 1,000 adult respondents. Methodologically, we found that (a) many apparently dropped alters were not really dropped, but were simply forgotten; (b) many alters whom respondents failed to re-list nonetheless remained "dormant" and available to the respondents; and (c) respondents positively dropped or demoted alters for several distinct reasons. Substantively, we found that (a) alters who were really dropped-neither re-listed nor simply forgotten-tended to be: extended kin, coworkers, or acquaintances; alters who had not been named as providing key support; and alters who were considered "difficult" (unless they were immediate kin). (b) Respondents who dropped many of their alters were particularly likely to have moved outside the region between waves. These findings suggest, methodologically, that the "true" rate of dropped alters in an adult population is nearer to 20 percent than the conventional 50 percent (depending on how the analyst classifies dropped alters who seemed to have been moved toward the periphery of ego's network). Theoretically, the findings suggest that the likelihood of being dropped ...

show abstract

Section: Which Egos Are Likeliest To Keep Ties or Drop Ties?mentioning

confidence: 99%

Who is dropped and why? Methodological and substantive accounts for network loss

Fischer

Offer

2020

Social Networks

View full text Add to dashboard Cite

show abstract

“…There is thus a long tradition of researchers adapting or adjusting name generators to address these difficulties. Changes have included reducing respondent burden by limiting the number of alters elicited, the number of name interpreters administered, or making interviews more enjoyable (Burt, 1984;Campbell & Lee, 1991;Hogan et al, 2007;Marin & Hampton, 2007;Van der Poel, 1993); adding qualitative components (Bidart & Cacciuttolo, 2013;Small, 2017); using context-focused name generators to ensure broad network coverage (Bidart & Charbonneau, 2011), and fixing the number of alters to be listed (McCarty, 2002).…”

Section: Collecting Data To Study Change In Ego Networkmentioning

confidence: 99%

Noting the ties after tying the knot: Photo-based elicitation of retrospective personal network data

Marin¹,

Lin²

2019

Net Sci

View full text Add to dashboard Cite

We report on an interview method using photo-based network elicitation and a landmark anchoring event to collect data on relationship change in ego networks retrospectively. Using the wedding albums of married or formerly married respondents, we populate a network from many years ago with persons pictured in the album and then collect data about each respondent’s relationship with each person at the time of the wedding and at the time of the interview. This data collection method mitigates many of the problems associated with retrospective data collection and does not have the logistical difficulties associated with panel studies. Our findings show that this method is successful in collecting significant numbers of connections that have undergone change, and especially reductions in activity along various dimensions.

show abstract

“…As for personal networks, a detailed interview-based investigation of change in those of French young people in their twenties used a typology of egonetwork shapes in order to discuss which life events (e.g. moving to a new place, leaving a partner) could lead to a specific change in shape (Bidart/Cacciuttolo 2013). As for organizations, a study of the transition to capitalism in Hungary based on written documents used the same typological approach to discuss the changing "local network topographies" of individual firms in the context of a national network of ownership ties (Stark/Vedres 2006).…”

Section: Change In Panel Data: Comparing Snapshotsmentioning

confidence: 99%

Taking time seriously

Lemercier¹

2015

Sozialtheorie

View full text Add to dashboard Cite

Sociologists are arguably the first, among humanists and social scientists, who have built a consistent canon of social network analysis. This includes often cited pioneering papers, the concepts and indicators that these had introduced, software allowing to calculate such indicators and to produce more and more standardized visualizations, and textbooks summing up and coagulating these elements (e.g. Scott/Carrington 2011). 2 In this canon, standard network data typically include a dozen to a few hundreds individuals or organizations, whose ties are described thanks to sociometric surveys, i.e. by asking individuals about one or a few specific types of relationships at a given moment. Non-standard data of course have always exi-1 Previous versions of this text have been presented in various conferences and seminars and have very much benefited from collective discussions. I am especially grateful to Fabien Accominotti, Claire Bidart, Ainhoa de Federico, Michel Grossetti, Karim Hammou, Linda Reschke, Isabelle Rosé and Tom Snijders, who in various ways made me take time more seriously, and even more to Marten Düring, who made invaluable comments on a first draft. Figures are reproduced with permissions from the authors and the journal. 2 In fact, the sociologists who built this specific canon of quantitative and structural network analysis had borrowed their main ideas to a previous generation of anthropologists and social psychologists: see Freeman (2004).

show abstract

Combining qualitative, quantitative and structural dimensions in a longitudinal perspective. The case of network influence

Abstract: To cite this version:Claire Bidart, Patrice Cacciuttolo. Combining qualitative, quantitative and structural dimensions in a longitudinal perspective. The case of network influence.. Quality and Quantity, Springer Verlag, 2013, 47 (5)

Cited by 14 publications

References 23 publications

Who is dropped and why? Methodological and substantive accounts for network loss

Who is dropped and why? Methodological and substantive accounts for network loss

Noting the ties after tying the knot: Photo-based elicitation of retrospective personal network data

Taking time seriously

Contact Info

Product

Resources

About