Web Survey Methodology

Callegaro, Mario; Manfreda, Katja Lozar; Vehovar, Vasja

doi:10.4135/9781529799651

Cited by 252 publications

(104 citation statements)

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“…According to Callegaro, Manfreda and Vehovar (2015) web surveys include those based on a "computerized self-administered questionnaires, stored on a specific computer connected to the internet" (p. …..). In this regard, "targeted chain referral sampling" draws on informants recruiting participants in their social network (Salagnick and Heckathorn, 2004).…”

Section: Sample and Participantsmentioning

confidence: 99%

“…For research purposes, web surveys have become more common over the past 15 years (Callegaro et al 2015), and present major advantages that makes them adequate regarding the goals of the present study. However, they also present major challenges, as a key issue concerns the sampling method, because while web surveys give access to widespread populations, they can provide non-probability samples too (Duffy, Smith, Terhanian and Bremer 2005).…”

Section: Sample and Participantsmentioning

confidence: 99%

“…However, they also present major challenges, as a key issue concerns the sampling method, because while web surveys give access to widespread populations, they can provide non-probability samples too (Duffy, Smith, Terhanian and Bremer 2005). According to Callegaro et al (2015), while this sampling method may be problematic for descriptive statistics aiming to account for the general characteristics of the parent population, it is adequate for causal research designs. In our case, the targeted population and sample was defined on two criteria: occupations including nurses and auxiliary nurses, and type of work placethat are public and private hospitals.…”

Section: Sample and Participantsmentioning

confidence: 99%

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“…Reips (2010) lists several typical errors that frequently happen when constructing online questionnaires:preselected answer options in drop-down menus, resulting either in submission of the default answer option as a chosen answer when the item is really skipped or provoking an anchoring effect,overlapping answer categories,no limitations set or announced to size of text to be entered in text fields,lack of options that indicate reluctance to answer (e.g., “don’t want to answer” or “no answer”), especially for sensitive items,all items on one run-on web page (see OIOS Technique section below),incorrect writing (e.g., errors in instructions or questions). An excellent resource for many topics around web survey methodology is Callegaro and colleagues (2015). It summarizes many important learnings from the scientific literature on moving surveying to the web and supersedes many earlier attempts in scientific depth and applicability.…”

Section: Types Of Web-based Researchmentioning

confidence: 99%

Web-Based Research in Psychology

Reips

2021

Zeitschrift für Psychologie

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Abstract. The present article reviews web-based research in psychology. It captures principles, learnings, and trends in several types of web-based research that show similar developments related to web technology and its major shifts (e.g., appearance of search engines, browser wars, deep web, commercialization, web services, HTML5…) as well as distinct challenges. The types of web-based research discussed are web surveys and questionnaire research, web-based tests, web experiments, Mobile Experience Sampling, and non-reactive web research, including big data. A number of web-based methods are presented and discussed that turned out to become important in research methodology. These are one-item-one-screen design, seriousness check, instruction manipulation and other attention checks, multiple site entry technique, subsampling technique, warm-up technique, and web-based measurement. Pitfalls and best practices are described then, especially regarding dropout and other non-response, recruitment of participants, and interaction between technology and psychological factors. The review concludes with a discussion of important concepts that have developed over 25 years and an outlook on future developments in web-based research.

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“…Survey Techniques: There is extensive work on traditional statistical survey techniques [25,27], as well on newer areas such as web survey methodology [15]. See [3] for a survey of non-response bias challenges, and [14] for an overview of selection bias.…”

Section: Related Workmentioning

confidence: 99%

LinkedIn Salary: A System for Secure Collection and Presentation of Structured Compensation Insights to Job Seekers

Kenthapadi¹,

Chudhary²,

Ambler³

2017

2017 IEEE Symposium on Privacy-Aware Computing (PAC)

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Online professional social networks such as LinkedIn have enhanced the ability of job seekers to discover and assess career opportunities, and the ability of job providers to discover and assess potential candidates. For most job seekers, salary (or broadly compensation) is a crucial consideration in choosing a new job. At the same time, job seekers face challenges in learning the compensation associated with different jobs, given the sensitive nature of compensation data and the dearth of reliable sources containing compensation data. Towards the goal of helping the world's professionals optimize their earning potential through salary transparency, we present LinkedIn Salary, a system for collecting compensation information from LinkedIn members and providing compensation insights to job seekers. We present the overall design and architecture, and describe the key components needed for the secure collection, de-identification, and processing of compensation data, focusing on the unique challenges associated with privacy and security. We perform an experimental study with more than one year of compensation submission history data collected from over 1.5 million LinkedIn members, thereby demonstrating the tradeoffs between privacy and modeling needs. We also highlight the lessons learned from the production deployment of this system at LinkedIn. 2 https://www.linkedin.com/salary

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Web Survey Methodology

Cited by 252 publications

References 0 publications

Leveraging green human resource practices to achieve environmental sustainability

Leveraging green human resource practices to achieve environmental sustainability

Web-Based Research in Psychology

LinkedIn Salary: A System for Secure Collection and Presentation of Structured Compensation Insights to Job Seekers

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