The Impact of Party Cues on Manual Coding of Political Texts
Bibliographic Data
| ID | 6342011 |
|---|---|
| Authors | Laurenz Ennser-Jedenastik (0000-0002-0107-5093), Thomas M Meyer (0000-0002-0389-9918) |
| Year | 2018 |
| Volume | 6 |
| Issue | 3 |
| Pages | 625-633 |
| Publication date | 2018-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Science Research and Methods (JOURNAL) |
| Journal identifiers | ISSN: 2049-8470 • E-ISSN: 2049-8489 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/psrm.2017.29 |
| OpenAlex | W2759290493 |
| Language | EN |
| Citations received | 6 |
| References cited | 30 |
Do coders of political texts incorporate prior beliefs about parties’ issue stances into their coding decisions? We report results from a coding experiment in which ten coders were each given 200 statements on immigration that were extracted from election manifestos. Party labels in these statements were randomly assigned (including a control category without party cues). Coders were more likely to code a statement as pro-immigration if it was attributed to the Greens and less likely choose the anti-immigration category if it was attributed to the populist radical right. No effect was found for mainstream parties of the center-left and center-right. The results also suggest that coders resort to party cues as heuristics when faced with ambiguous policy statements
Coding (social sciences · Heuristics · Immigration · Mainstream · Political science · Politics · Social science · Sociology · Computational and Text Analysis Methods · Computer Science · Electoral Systems and Political Participation · Law · Media Influence and Politics · Psychology · Social Psychology
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| Unique citing works | 6 |
|---|---|
| Citations per year | 1 |
| Citation span | 2020 - 2025 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 5 |