
Manual corpus annotation facilitates exhaustive and detailed corpus-based analyses of evaluation that would not be possible with purely automatic techniques. However, manual annotation is a complex and subjective process. Most studies adopting this approach have paid insufficient attention to the methodological challenges involved in manually annotating evaluation – especially concerning transparency, reliability and replicability. This article illustrates a procedure for annotating evaluative expressions in text that facilitates more transparent, reliable and replicable analyses. The method is demonstrated through a case study analysis of appraisal ( Martin and White, 2005 ) in a small-size specialised corpus of CEO letters published by the British energy company, BP, and four competitors before and after the Deepwater Horizon oil spill of 2010. Drawing on Fuoli and Paradis's (2014) model of trust–repair discourse, we examine how attitude and engagement resources are strategically deployed by BP's CEO in the attempt to repair stakeholders’ trust after the accident.
transparency, evaluation, reliability, Comparative Language Studies and Linguistics, inter-coder agreement, trust-repair, BP Deepwater Horizon oil spill, Languages and Literature, replicability, APPRAISAL theory, manual corpus annotation
transparency, evaluation, reliability, Comparative Language Studies and Linguistics, inter-coder agreement, trust-repair, BP Deepwater Horizon oil spill, Languages and Literature, replicability, APPRAISAL theory, manual corpus annotation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 58 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
