A system for collecting and analyzing experience-sampling data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dennis, Simon | - |
dc.contributor.author | Yim, Hyungwook | - |
dc.contributor.author | Garrett, Paul | - |
dc.contributor.author | Sreekumar, Vishnu | - |
dc.contributor.author | Stone, Ben | - |
dc.date.accessioned | 2021-08-03T02:56:13Z | - |
dc.date.available | 2021-08-03T02:56:13Z | - |
dc.date.created | 2021-05-14 | - |
dc.date.issued | 2019-08 | - |
dc.identifier.issn | 1554-351X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/32832 | - |
dc.description.abstract | Online and sensor technologies promise to transform many areas of psychological enquiry. However, collecting and analyzing such data are challenging. In this article, we introduce the unforgettable.me experience-sampling platform. Unforgettable.me includes an app that can collect image, Global Positioning System, accelerometry, and audio data in a continuous fashion and upload the data to a server. The data are then automatically augmented by using online databases to identify the address, type of location, and weather conditions, as well as provide street view imagery. In addition, machine-learning classifiers are run to identify aspects of the audio data such as voice and traffic. The augmented data are available to participants in the form of a keyword search interface, as well as via several visualization mechanisms. In addition, Unforgettable Research Services partners with If This Then That (IFTTT), and so can accumulate data from any of over 600 sources, including social media, wearables, and other devices. Through IFTTT, buttons can be added as icons to smartphones to allow participants to register mood conveniently, as well as behaviors and physiological states such as happiness, microaggressions, or illness. Furthermore, unforgettable.me incorporates a mechanism that allows researchers to run experiments and analyze data within an authenticated environment without viewing users’ private data. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER | - |
dc.title | A system for collecting and analyzing experience-sampling data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Yim, Hyungwook | - |
dc.identifier.doi | 10.3758/s13428-019-01260-y | - |
dc.identifier.scopusid | 2-s2.0-85068215532 | - |
dc.identifier.wosid | 000481874200022 | - |
dc.identifier.bibliographicCitation | BEHAVIOR RESEARCH METHODS, v.51, no.4, pp.1824 - 1838 | - |
dc.relation.isPartOf | BEHAVIOR RESEARCH METHODS | - |
dc.citation.title | BEHAVIOR RESEARCH METHODS | - |
dc.citation.volume | 51 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 1824 | - |
dc.citation.endPage | 1838 | - |
dc.type.rims | ART | - |
dc.type.docType | 정기학술지(Article(Perspective Article포함)) | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Psychology | - |
dc.relation.journalWebOfScienceCategory | Psychology, Mathematical | - |
dc.relation.journalWebOfScienceCategory | Psychology, Experimental | - |
dc.subject.keywordPlus | PRIVACY | - |
dc.subject.keywordAuthor | Experience sampling | - |
dc.subject.keywordAuthor | PrivacyData collection | - |
dc.subject.keywordAuthor | Data analysis | - |
dc.identifier.url | https://link.springer.com/article/10.3758/s13428-019-01260-y | - |
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