Check the phone book: Testing information and communication technology (ICT) recall aids for personal network surveys

Hsieh, Y. Patrick

doi:10.1016/j.socnet.2014.11.006

Cited by 17 publications

(17 citation statements)

References 73 publications

(87 reference statements)

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“…There are few examples of research that test somewhat competing methods of eliciting interaction-based contacts. The current study nearly replicated Hsieh's [10] study which found that a retrieval cue approach elicits more contacts than a baseline approach (p = 0.13). However, a few caveats much be mentioned before any premature conclusions.…”

Section: Discussionsupporting

confidence: 85%

“…Moreover, prior literature has suggested that successful recall (i.e., remembering all of your contacts) is influenced by a number of factors because contacts tend be cognitively stored in clusters or what Brashears and Quintane [9] call chunked substructures. Likewise, there may be individual differences in recall pertaining to demographic and social identity factors like gender, age, race [10,11] and psychological factors like mood and well-being [12,13].…”

Section: Theory and Hypothesis Developmentmentioning

confidence: 99%

“…For the retrieval cue approach, we followed procedures laid out by Hiesh [10]. Before eliciting contacts, participants were instructed to look at their (1) cellphone calls and texts from the last four days, (2) last 30 emails, and (3) recent posts, tags, and messages they have sent or received on their preferred social media (e.g., Facebook, Twitter, etc.)…”

Section: Measures 251 Contact Elicitationmentioning

confidence: 99%

“…Past research on individual level factors and network alter recall can help give guidance for additional control variables to include. Our review has identified such factors as gender [23], age [10], race [10], mood [24], well-being [13], and physical functioning [25]. Standard items were used to gather information on demographics like gender, age, and race.…”

Section: Control Variablesmentioning

confidence: 99%

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An Egocentric Network Contact Tracing Experiment

Pilny¹,

Huber²

2020

Preprint

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Contact tracing is one of the oldest social network health interventions used to reduce the diffusion of various infectious diseases. However, some infectious diseases like COVID-19 amass at such a great scope that traditional methods of conducting contact tracing (e.g., face-to-face interviews) remain difficult to implement, pointing the need to develop reliable and valid survey approaches. The purpose of this research is to test the effectiveness of three different egocentric survey methods for extracting contact tracing data: (1) a baseline approach, (2) a retrieval cue approach, and (3) a context-based approach. A sample of 397 college students were randomized into one of each condition and were prompted to anonymously provide contacts and populated places visited from the past four days. After controlling for various demographic, social identity, psychological, and physiological variables, participants in the context-based condition were significantly more likely recall more contacts (medium effect size) and places (large effect size) than the other two conditions. Theoretically, the research supports suggestions by field theory that assume network recall can be significantly improved by activating relevant activity foci. Practically, the research contributes to developing innovative social network data collection methods for contract tracing survey instruments.

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Section: Discussionsupporting

confidence: 85%

Section: Theory and Hypothesis Developmentmentioning

confidence: 99%

Section: Measures 251 Contact Elicitationmentioning

confidence: 99%

Section: Control Variablesmentioning

confidence: 99%

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An Egocentric Network Contact Tracing Experiment

Pilny¹,

Huber²

2020

Preprint

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“…Each of these tools has its own pros and cons. In case of name generator, relaying too much on respondents' memory or self-report that has possibility of personal networks being reported with mistakes or simply it is probable that ego doesn't have accurate information of alters as an example about their political views and s/he is reporting her image of alters (Marsden, 1990;Hsieh, 2015; Número 4, septiembre 2015, Nº 04/y1. ISSN: 2014-5993 http://dx.doi.org/10.5565/rev/grafowp.14 Wejnert, 2010) that could be probably different from what is happening in reality.…”

Section: Data Collection Strategymentioning

confidence: 99%

A tool for dynamic measurement of social capital embedded in Online Social Networks.

Hezarjaribi

Jullien

2015

grafowp

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This paper suggests a methodological improvement to study social capital in online social networks. We have designed a measurement tool based on Lin's theory of social resources. It is named Social Village and can be accessed in (http://socialvillage.me). By this tool, we are getting access to profile and friendship data of users of online social networks (Facebook and Google Plus). To access this data, we ask for users' permission by social login and we have designed a gamified and interesting social survey that helps users get an in-depth knowledge of their online life. This tool combines three structural generators for social capital data (name, position and resource generators) and it has been developed in three languages (English, French and Persian) enabling us to conduct comparative studies. Based on our preliminary results presented in this paper, 412 users in sample of our study know who they are connected with in online social networks, they know their friends' socioeconomic positions and they are providing or receiving various resources through their online friendships. Gamified social survey used in this tool helped us gain a four times more response rate than existing online surveys. In this paper, we present, reviewed literature, theoretical framework, methodology of constructing the tool and results obtained.

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Collecting Social Network Data

Stark

2017

The Palgrave Handbook of Survey Research

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Check the phone book: Testing information and communication technology (ICT) recall aids for personal network surveys

Cited by 17 publications

References 73 publications

An Egocentric Network Contact Tracing Experiment

An Egocentric Network Contact Tracing Experiment

A tool for dynamic measurement of social capital embedded in Online Social Networks.

Collecting Social Network Data

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