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Article: Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science

TitleTesting Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science
Authors
Issue Date2015
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
PLoS One, 2015, v. 10 n. 8, p. e0134270 How to Cite?
AbstractReplication is an essential requirement for scientific discovery. The current study aims to generalize and replicate 10 propositions made in previous Twitter studies using a representative dataset. Our findings suggest 6 out of 10 propositions could not be replicated due to the variations of data collection, analytic strategies employed, and inconsistent measurements. The study’s contributions are twofold: First, it systematically summarized and assessed some important claims in the field, which can inform future studies. Second, it proposed a feasible approach to generating a random sample of Twitter users and its associated ego networks, which might serve as a solution for answering social-scientific questions at the individual level without accessing the complete data archive.
Persistent Identifierhttp://hdl.handle.net/10722/217973
ISSN
2015 Impact Factor: 3.057
2015 SCImago Journal Rankings: 1.395
ISI Accession Number ID
Dataset
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DC FieldValueLanguage
dc.contributor.authorLiang, H-
dc.contributor.authorFu, KW-
dc.date.accessioned2015-09-18T06:20:01Z-
dc.date.available2015-09-18T06:20:01Z-
dc.date.issued2015-
dc.identifier.citationPLoS One, 2015, v. 10 n. 8, p. e0134270-
dc.identifier.issn1932-6203-
dc.identifier.urihttp://hdl.handle.net/10722/217973-
dc.description.abstractReplication is an essential requirement for scientific discovery. The current study aims to generalize and replicate 10 propositions made in previous Twitter studies using a representative dataset. Our findings suggest 6 out of 10 propositions could not be replicated due to the variations of data collection, analytic strategies employed, and inconsistent measurements. The study’s contributions are twofold: First, it systematically summarized and assessed some important claims in the field, which can inform future studies. Second, it proposed a feasible approach to generating a random sample of Twitter users and its associated ego networks, which might serve as a solution for answering social-scientific questions at the individual level without accessing the complete data archive.-
dc.languageeng-
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action-
dc.relation.ispartofPLoS One-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleTesting Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science-
dc.typeArticle-
dc.identifier.emailLiang, H: hailiang@hku.hk-
dc.identifier.emailFu, KW: kwfu@hkucc.hku.hk-
dc.identifier.authorityFu, KW=rp00552-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0134270-
dc.identifier.hkuros250426-
dc.identifier.volume10-
dc.identifier.issue8-
dc.identifier.spagee0134270-
dc.identifier.epagee0134270-
dc.identifier.isiWOS:000360018600017-
dc.publisher.placeUnited States-
dc.relation.projectCan online opinion reflect public opinion? An investigation into the interplays between online opinion, public opinion, and mass media-
dc.relation.dataTesting Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science-

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