dc.contributor.author | Cioroianu, I | |
dc.contributor.author | Banducci, S | |
dc.contributor.author | Szlavik, Z | |
dc.coverage.spatial | United Kingdom | en_GB |
dc.date.accessioned | 2019-12-19T11:12:18Z | |
dc.date.issued | 2018-08-28 | |
dc.description.abstract | In this paper, we test three methods of estimating ideological bias in news media stories. This forms the basis for the development of a news reading app. We find that WordScores offers the most reliable estimate and reliability is improved when applied after identifying topic. | en_GB |
dc.description.sponsorship | Economic and Social Research Council (ESRC) | en_GB |
dc.identifier.grantnumber | 677278 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/40142 | |
dc.language.iso | en | en_GB |
dc.rights | © The Author(s). All rights reserved | en_GB |
dc.subject | text as data | en_GB |
dc.subject | app | en_GB |
dc.subject | ideology | en_GB |
dc.title | Extracting Topic-Specific Ideological Positions from News Articles | en_GB |
dc.type | Working Paper | en_GB |
dc.date.available | 2019-12-19 | en_GB |
dc.date.available | 2019-12-19T11:12:18Z | |
dc.language | English | en_GB |
pubs.notes | Not known | en_GB |
dc.description | This is the final version. | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
exeter.funder | ::Economic and Social Research Council (ESRC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2018-08-28 | |
rioxxterms.type | Working paper | en_GB |
refterms.dateFCD | 2019-12-19T11:10:49Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2019-12-19T11:12:21Z | |