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Implementing sentiment analysis to an open-ended questionnaire: Case study of digitalization in elderly care during COVID-19

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Implementing sentiment analysis to an open-ended questionnaire: Case study of digitalization in elderly care during COVID-19

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dc.contributor.author Toivanen, Ida es_ES
dc.contributor.author Räsänen, Venla es_ES
dc.contributor.author Lindroos, Jari es_ES
dc.contributor.author Oinas, Tomi es_ES
dc.contributor.author Taipale, Sakari es_ES
dc.date.accessioned 2022-11-10T13:14:36Z
dc.date.available 2022-11-10T13:14:36Z
dc.date.issued 2022-09-20
dc.identifier.isbn 9788413960180
dc.identifier.uri http://hdl.handle.net/10251/189575
dc.description.abstract [EN] The rise of digital technology has enabled us to utilize even more integrated systems for social and health care, but these systems are often complex and time-consuming to learn for the end users without relevant training or experience. We aim to perform Named Entity Recognition based sentiment analysis using the answers of eldercare workers that have taken a survey about the effects of digitalization on their work. The collection of the panel survey data was carried out in two waves: in 2019 and 2021. For the sentiment analysis we compare these two waves to determine the effects of COVID-19 on the work of eldercare workers. The research questions we ask are the following: “Has technology affected eldercare workers’ emotions in their work and how?" and “Has COVID-19 affected eldercare workers’ views on digitalization in their work?”. The main results suggest that criticism of modern technology persists through time – that is, before and after the pandemic the same type of negative and positive sentiments are manifested in the results. However, the familiarization with technology during COVID-19 seems to have been decreasing negative sentiments and increasing positive sentiments regarding digitalization. Due to the smallness of our data, more research should be conducted to make firmer conclusions on the matter. es_ES
dc.format.extent 8 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022)
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Eldercare work es_ES
dc.subject Digitalization es_ES
dc.subject Sentiment analysis es_ES
dc.subject Named entity recognition es_ES
dc.subject BERT es_ES
dc.title Implementing sentiment analysis to an open-ended questionnaire: Case study of digitalization in elderly care during COVID-19 es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2022.2022.15089
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Toivanen, I.; Räsänen, V.; Lindroos, J.; Oinas, T.; Taipale, S. (2022). Implementing sentiment analysis to an open-ended questionnaire: Case study of digitalization in elderly care during COVID-19. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 205-212. https://doi.org/10.4995/CARMA2022.2022.15089 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2022 - 4th International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Junio 29-Julio 01, 2022 es_ES
dc.relation.conferenceplace Valencia, España
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2022/paper/view/15089 es_ES
dc.description.upvformatpinicio 205 es_ES
dc.description.upvformatpfin 212 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\15089 es_ES


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