Loading…

Reprint of: Using Trellis software to enhance high-quality large-scale network data collection in the field

•Trellis network data collection platform enables name disambiguation.•Trellis network data collection platform enables multiple language interviews.•Trellis report allows for real-time monitoring of data collection.•Trellis network data collection platform can be used offline in remote areas. Trell...

Full description

Saved in:
Bibliographic Details
Published in:Social networks 2022-05, Vol.69, p.293-306
Main Authors: Lungeanu, Alina, McKnight, Mark, Negron, Rennie, Munar, Wolfgang, Christakis, Nicholas A., Contractor, Noshir S.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c198t-776a594f1fa1ad5168f7aae758f2d1c4f383d6a1cb1d42a9f259fefdebd312543
container_end_page 306
container_issue
container_start_page 293
container_title Social networks
container_volume 69
creator Lungeanu, Alina
McKnight, Mark
Negron, Rennie
Munar, Wolfgang
Christakis, Nicholas A.
Contractor, Noshir S.
description •Trellis network data collection platform enables name disambiguation.•Trellis network data collection platform enables multiple language interviews.•Trellis report allows for real-time monitoring of data collection.•Trellis network data collection platform can be used offline in remote areas. Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis’ ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.
doi_str_mv 10.1016/j.socnet.2022.01.004
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2689717721</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0378873322000041</els_id><sourcerecordid>2689717721</sourcerecordid><originalsourceid>FETCH-LOGICAL-c198t-776a594f1fa1ad5168f7aae758f2d1c4f383d6a1cb1d42a9f259fefdebd312543</originalsourceid><addsrcrecordid>eNp9kEtrGzEUhUVoIa7bf9CFoOuZ6moe0nRRKCFpA4ZCiddCka5sOcrIluSY_PvIuOuszuY8OB8hX4G1wGD8vmtzNDOWljPOWwYtY_0VWYAUU8MB4ANZsE7IRoquuyafct4xxkYBckGe_uE--bnQ6H7Qdfbzhj4kDMFnmqMrJ52Qlkhx3urZIN36zbY5HHXw5ZUGnTbYZKMD0rp-iumJWl00NTEENMXHmfqZli1S5zHYz-Sj0yHjl_-6JOu724ebP83q7-_7m1-rxsAkSyPEqIepd-A0aDvAKJ3QGsUgHbdgetfJzo4azCPYnuvJ8WFy6Cw-2g740HdL8u3Su0_xcMRc1C4e01wnFR_lJEAIDtXVX1wmxZwTOlVBPOv0qoCpM1a1Uxes6oxVMVAVa439vMSwPnjxmFQ2Hisb61P9rGz07xe8AfsOhGc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2689717721</pqid></control><display><type>article</type><title>Reprint of: Using Trellis software to enhance high-quality large-scale network data collection in the field</title><source>International Bibliography of the Social Sciences (IBSS)</source><source>ScienceDirect Freedom Collection</source><source>Sociological Abstracts</source><creator>Lungeanu, Alina ; McKnight, Mark ; Negron, Rennie ; Munar, Wolfgang ; Christakis, Nicholas A. ; Contractor, Noshir S.</creator><creatorcontrib>Lungeanu, Alina ; McKnight, Mark ; Negron, Rennie ; Munar, Wolfgang ; Christakis, Nicholas A. ; Contractor, Noshir S.</creatorcontrib><description>•Trellis network data collection platform enables name disambiguation.•Trellis network data collection platform enables multiple language interviews.•Trellis report allows for real-time monitoring of data collection.•Trellis network data collection platform can be used offline in remote areas. Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis’ ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.</description><identifier>ISSN: 0378-8733</identifier><identifier>EISSN: 1879-2111</identifier><identifier>DOI: 10.1016/j.socnet.2022.01.004</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Data collection ; Graphical interface ; Human nature ; Mobile social network survey technologies ; Online surveys ; Rural network data collection ; Social networks ; Software ; Software data collection ; Time of day ; Villages</subject><ispartof>Social networks, 2022-05, Vol.69, p.293-306</ispartof><rights>2022 The Authors</rights><rights>Copyright Elsevier Science Ltd. May 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c198t-776a594f1fa1ad5168f7aae758f2d1c4f383d6a1cb1d42a9f259fefdebd312543</cites><orcidid>0000-0002-9234-987X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925,33223,33774</link.rule.ids></links><search><creatorcontrib>Lungeanu, Alina</creatorcontrib><creatorcontrib>McKnight, Mark</creatorcontrib><creatorcontrib>Negron, Rennie</creatorcontrib><creatorcontrib>Munar, Wolfgang</creatorcontrib><creatorcontrib>Christakis, Nicholas A.</creatorcontrib><creatorcontrib>Contractor, Noshir S.</creatorcontrib><title>Reprint of: Using Trellis software to enhance high-quality large-scale network data collection in the field</title><title>Social networks</title><description>•Trellis network data collection platform enables name disambiguation.•Trellis network data collection platform enables multiple language interviews.•Trellis report allows for real-time monitoring of data collection.•Trellis network data collection platform can be used offline in remote areas. Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis’ ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.</description><subject>Data collection</subject><subject>Graphical interface</subject><subject>Human nature</subject><subject>Mobile social network survey technologies</subject><subject>Online surveys</subject><subject>Rural network data collection</subject><subject>Social networks</subject><subject>Software</subject><subject>Software data collection</subject><subject>Time of day</subject><subject>Villages</subject><issn>0378-8733</issn><issn>1879-2111</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><sourceid>BHHNA</sourceid><recordid>eNp9kEtrGzEUhUVoIa7bf9CFoOuZ6moe0nRRKCFpA4ZCiddCka5sOcrIluSY_PvIuOuszuY8OB8hX4G1wGD8vmtzNDOWljPOWwYtY_0VWYAUU8MB4ANZsE7IRoquuyafct4xxkYBckGe_uE--bnQ6H7Qdfbzhj4kDMFnmqMrJ52Qlkhx3urZIN36zbY5HHXw5ZUGnTbYZKMD0rp-iumJWl00NTEENMXHmfqZli1S5zHYz-Sj0yHjl_-6JOu724ebP83q7-_7m1-rxsAkSyPEqIepd-A0aDvAKJ3QGsUgHbdgetfJzo4azCPYnuvJ8WFy6Cw-2g740HdL8u3Su0_xcMRc1C4e01wnFR_lJEAIDtXVX1wmxZwTOlVBPOv0qoCpM1a1Uxes6oxVMVAVa439vMSwPnjxmFQ2Hisb61P9rGz07xe8AfsOhGc</recordid><startdate>202205</startdate><enddate>202205</enddate><creator>Lungeanu, Alina</creator><creator>McKnight, Mark</creator><creator>Negron, Rennie</creator><creator>Munar, Wolfgang</creator><creator>Christakis, Nicholas A.</creator><creator>Contractor, Noshir S.</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U4</scope><scope>8BJ</scope><scope>BHHNA</scope><scope>DWI</scope><scope>FQK</scope><scope>JBE</scope><scope>WZK</scope><orcidid>https://orcid.org/0000-0002-9234-987X</orcidid></search><sort><creationdate>202205</creationdate><title>Reprint of: Using Trellis software to enhance high-quality large-scale network data collection in the field</title><author>Lungeanu, Alina ; McKnight, Mark ; Negron, Rennie ; Munar, Wolfgang ; Christakis, Nicholas A. ; Contractor, Noshir S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c198t-776a594f1fa1ad5168f7aae758f2d1c4f383d6a1cb1d42a9f259fefdebd312543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Data collection</topic><topic>Graphical interface</topic><topic>Human nature</topic><topic>Mobile social network survey technologies</topic><topic>Online surveys</topic><topic>Rural network data collection</topic><topic>Social networks</topic><topic>Software</topic><topic>Software data collection</topic><topic>Time of day</topic><topic>Villages</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lungeanu, Alina</creatorcontrib><creatorcontrib>McKnight, Mark</creatorcontrib><creatorcontrib>Negron, Rennie</creatorcontrib><creatorcontrib>Munar, Wolfgang</creatorcontrib><creatorcontrib>Christakis, Nicholas A.</creatorcontrib><creatorcontrib>Contractor, Noshir S.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Sociological Abstracts</collection><collection>Sociological Abstracts</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>Social networks</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lungeanu, Alina</au><au>McKnight, Mark</au><au>Negron, Rennie</au><au>Munar, Wolfgang</au><au>Christakis, Nicholas A.</au><au>Contractor, Noshir S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Reprint of: Using Trellis software to enhance high-quality large-scale network data collection in the field</atitle><jtitle>Social networks</jtitle><date>2022-05</date><risdate>2022</risdate><volume>69</volume><spage>293</spage><epage>306</epage><pages>293-306</pages><issn>0378-8733</issn><eissn>1879-2111</eissn><abstract>•Trellis network data collection platform enables name disambiguation.•Trellis network data collection platform enables multiple language interviews.•Trellis report allows for real-time monitoring of data collection.•Trellis network data collection platform can be used offline in remote areas. Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis’ ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.socnet.2022.01.004</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-9234-987X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0378-8733
ispartof Social networks, 2022-05, Vol.69, p.293-306
issn 0378-8733
1879-2111
language eng
recordid cdi_proquest_journals_2689717721
source International Bibliography of the Social Sciences (IBSS); ScienceDirect Freedom Collection; Sociological Abstracts
subjects Data collection
Graphical interface
Human nature
Mobile social network survey technologies
Online surveys
Rural network data collection
Social networks
Software
Software data collection
Time of day
Villages
title Reprint of: Using Trellis software to enhance high-quality large-scale network data collection in the field
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T13%3A47%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Reprint%20of:%20Using%20Trellis%20software%20to%20enhance%20high-quality%20large-scale%20network%20data%20collection%20in%20the%20field&rft.jtitle=Social%20networks&rft.au=Lungeanu,%20Alina&rft.date=2022-05&rft.volume=69&rft.spage=293&rft.epage=306&rft.pages=293-306&rft.issn=0378-8733&rft.eissn=1879-2111&rft_id=info:doi/10.1016/j.socnet.2022.01.004&rft_dat=%3Cproquest_cross%3E2689717721%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c198t-776a594f1fa1ad5168f7aae758f2d1c4f383d6a1cb1d42a9f259fefdebd312543%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2689717721&rft_id=info:pmid/&rfr_iscdi=true