Evaluation of Consent to Link Twitter Data to Survey Data

Author:

Mneimneh Zeina1

Affiliation:

1. Survey Research Center, Institute for Social Research University of Michigan (previously) , Ann Arbor, Michigan , USA

Abstract

Abstract This study presents an initial framework describing factors that could affect respondents’ decisions to link their survey data with their public Twitter data. It also investigates two types of factors, those related to the individual and to the design of the consent request. Individual-level factors include respondents’ attitudes towards helpful behaviours, privacy concerns and social media engagement patterns. The design factor focuses on the position of the consent request within the interview. These investigations were conducted using data that was collected from a web survey on a sample of Twitter users selected from an adult online probability panel in the United States. The sample was randomly divided into two groups, those who received the consent to link request at the beginning of the survey, and others who received the request towards the end of the survey. Privacy concerns, measures of social media engagement and consent request placement were all found to be related to consent to link. The findings have important implications for designing future studies that aim at linking social media data with survey data.

Funder

Michigan Institute for Data Science and Data Acquisition for Data Science, University of Michigan

National Science Foundation

Division of Social and Economic Sciences

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Social Sciences (miscellaneous),Statistics and Probability

Reference27 articles.

1. Linking Twitter and survey data: the impact of survey mode and demographics on consent rates across three UK studies;Al Baghal;Social Science Computer Review,2019

2. Informed consent for linking survey and social media data: differences between platforms and data types;Bruer;IASSIST Quarterly,2021

3. Participant” perceptions of Twitter research ethics;Fiesler;Social Media + Society,2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3