dc.contributor.author | Zielinski, Andrea | de |
dc.contributor.author | Mutschke, Peter | de |
dc.date.accessioned | 2018-06-28T08:17:25Z | |
dc.date.available | 2018-06-28T08:17:25Z | |
dc.date.issued | 2017 | de |
dc.identifier.uri | https://www.ssoar.info/ssoar/handle/document/57722 | |
dc.description.abstract | Research in Social Science is usually based on survey data where individual research questions relate to observable concepts (variables). However, due to a lack of standards for data citations a reliable identification of the variables used is often difficult. In this paper, we present a work-in-progress study that seeks to provide a solution to the variable detection task based on supervised machine learning algorithms, using a linguistic analysis pipeline to extract a rich feature set, including terminological concepts and similarity metric scores. Further, we present preliminary results on a small dataset that has been specifically designed for this task, yielding modest improvements over the baseline. | en |
dc.language | en | de |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/654021 | de |
dc.rights | info:eu-repo/semantics/openAccess | de |
dc.subject.ddc | Literatur, Rhetorik, Literaturwissenschaft | de |
dc.subject.ddc | Literature, rhetoric and criticism | en |
dc.subject.ddc | News media, journalism, publishing | en |
dc.subject.ddc | Publizistische Medien, Journalismus,Verlagswesen | de |
dc.subject.other | OpenMinTed | de |
dc.title | Mining Social Science Publications for Survey Variables | de |
dc.type | info:eu-repo/semantics/conferenceObject | de |
dc.description.review | begutachtet (peer reviewed) | de |
dc.description.review | peer reviewed | en |
dc.identifier.url | http://www.aclweb.org/anthology/W17-2907 | de |
dc.source.collection | Proceedings of the Second Workshop on NLP and Computational Social Science | de |
dc.publisher.country | MISC | |
dc.subject.classoz | Information Science | en |
dc.subject.classoz | Literaturwissenschaft, Sprachwissenschaft, Linguistik | de |
dc.subject.classoz | Informationswissenschaft | de |
dc.subject.classoz | Science of Literature, Linguistics | en |
dc.subject.thesoz | publication | en |
dc.subject.thesoz | technical literature | en |
dc.subject.thesoz | Datengewinnung | de |
dc.subject.thesoz | künstliche Intelligenz | de |
dc.subject.thesoz | artificial intelligence | en |
dc.subject.thesoz | computational linguistics | en |
dc.subject.thesoz | survey | en |
dc.subject.thesoz | social science | en |
dc.subject.thesoz | Begriff | de |
dc.subject.thesoz | concept | en |
dc.subject.thesoz | Algorithmus | de |
dc.subject.thesoz | Computerlinguistik | de |
dc.subject.thesoz | Befragung | de |
dc.subject.thesoz | Publikation | de |
dc.subject.thesoz | Sozialwissenschaft | de |
dc.subject.thesoz | Fachliteratur | de |
dc.subject.thesoz | algorithm | en |
dc.subject.thesoz | periodical | en |
dc.subject.thesoz | Indikatorenbildung | de |
dc.subject.thesoz | construction of indicators | en |
dc.subject.thesoz | data capture | en |
dc.subject.thesoz | Zeitschrift | de |
dc.identifier.urn | urn:nbn:de:0168-ssoar-57722-7 | |
dc.rights.licence | Creative Commons - Namensnennung, Nicht-kommerz., Weitergabe unter gleichen Bedingungen 4.0 | de |
dc.rights.licence | Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 | en |
ssoar.contributor.institution | GESIS | de |
internal.status | formal und inhaltlich fertig erschlossen | de |
internal.identifier.thesoz | 10035039 | |
internal.identifier.thesoz | 10040547 | |
internal.identifier.thesoz | 10040387 | |
internal.identifier.thesoz | 10037910 | |
internal.identifier.thesoz | 10047135 | |
internal.identifier.thesoz | 10058540 | |
internal.identifier.thesoz | 10039627 | |
internal.identifier.thesoz | 10037963 | |
internal.identifier.thesoz | 10043145 | |
internal.identifier.thesoz | 10041401 | |
internal.identifier.thesoz | 10043031 | |
dc.type.stock | incollection | de |
dc.type.document | Konferenzbeitrag | de |
dc.type.document | conference paper | en |
dc.source.pageinfo | 47-52 | de |
internal.identifier.classoz | 30200 | |
internal.identifier.classoz | 1080500 | |
internal.identifier.document | 16 | |
dc.contributor.corporateeditor | Association for Computational Linguistics (ACL) | |
dc.event.city | Vancouver | de |
internal.identifier.corporateeditor | 1020 | |
internal.identifier.ddc | 800 | |
internal.identifier.ddc | 070 | |
dc.date.conference | 2017 | de |
dc.description.pubstatus | Postprint | en |
dc.description.pubstatus | Postprint | de |
internal.identifier.licence | 36 | |
internal.identifier.pubstatus | 2 | |
internal.identifier.review | 1 | |
dc.subject.classhort | 30200 | de |
dc.subject.classhort | 50200 | de |
ssoar.wgl.collection | true | de |
internal.pdf.version | 1.5 | |
internal.pdf.valid | true | |
internal.pdf.wellformed | true | |
internal.check.openaire | true | de |
internal.check.abstractlanguageharmonizer | CERTAIN | |
internal.check.languageharmonizer | CERTAIN_RETAINED | |