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Assessing the stability of egocentric networks over time using the digital participant-aided sociogram tool Network Canvas.

Bernie HoganPatrick JanulisGregory Lee PhillipsJoshua MelvilleBrian MustanskiNoshir ContractorMichelle Birkett
Published in: Network science (Cambridge University Press) (2019)
This paper examines the stability of egocentric networks as reported over time using a novel touchscreen-based participant-aided sociogram. Past work has noted the instability of nominated network alters, with a large proportion leaving and reappearing between interview observations. To explain this instability of networks over time, researchers often look to structural embeddedness, namely the notion that alters are connected to other alters within egocentric networks. Recent research has also asked whether the interview situation itself may play a role in conditioning respondents to what might be the appropriate size and shape of a social network, and thereby which alters ought to be nominated or not. We report on change in these networks across three waves and assess whether this change appears to be the result of natural churn in the network or whether changes might be the result of factors in the interview itself, particularly anchoring and motivated underreporting. Our results indicate little change in average network size across waves, particularly for indirect tie nominations. Slight, significant changes were noted between waves one and two particularly among those with the largest networks. Almost no significant differences were observed between waves two and three, either in terms of network size, composition, or density. Data come from three waves of a Chicago-based panel study of young men who have sex with men.
Keyphrases
  • men who have sex with men
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  • mental health
  • machine learning
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  • south africa
  • hiv infected