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A proposal to deal with sampling bias in social network big data

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A proposal to deal with sampling bias in social network big data

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dc.contributor.author Iacus, Stefano Maria es_ES
dc.contributor.author Porro, Giuseppe es_ES
dc.contributor.author Salini, Silvia es_ES
dc.contributor.author Siletti, Elena es_ES
dc.date.accessioned 2018-11-07T08:02:01Z
dc.date.available 2018-11-07T08:02:01Z
dc.date.issued 2018-09-07
dc.identifier.isbn 9788490486894
dc.identifier.uri http://hdl.handle.net/10251/112038
dc.description.abstract [EN] Selection bias is the bias introduced by the non random selection of data, it leads to question whether the sample obtained is representative of the target population. Generally there are different types of selection bias, but when one manages web-surveys or data from social network as Twitter or Facebook, one mostly need to focus with sampling and self-selection bias. In this work we propose to use offcial statistics to anchor and remove the sampling bias and unreliability of the estimations, due to the use of social network big data, following a weighting method combined with a small area estimations (SAE) approach. es_ES
dc.format.extent 9 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018) es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Web data es_ES
dc.subject Internet data es_ES
dc.subject Big data es_ES
dc.subject QCA es_ES
dc.subject PLS es_ES
dc.subject SEM es_ES
dc.subject Conference es_ES
dc.subject Well-being es_ES
dc.subject Social indicators es_ES
dc.subject Sentiment analysis es_ES
dc.subject Self-selection bias es_ES
dc.subject Small area estimation es_ES
dc.title A proposal to deal with sampling bias in social network big data es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2018.2018.8302
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Iacus, SM.; Porro, G.; Salini, S.; Siletti, E. (2018). A proposal to deal with sampling bias in social network big data. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politècnica de València. 29-37. https://doi.org/10.4995/CARMA2018.2018.8302 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2018 - 2nd International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Julio 12-13,2018 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/view/8302 es_ES
dc.description.upvformatpinicio 29 es_ES
dc.description.upvformatpfin 37 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\8302 es_ES


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