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This codebook is a resource for those interested in analyzing any form of content (interview transcripts, news articles, social media posts, etc.) for the presence of trust and/or trustworthiness. This specific codebook has been tailored to analyzing interviews with National Weather Service (NWS) Forecasters about artificial intelligence (AI). As a result, the examples and rules are designed to capture this context. However, this codebook could be modified to address other contexts as needed. Please cite this codebook if you use this codebook directly or use it to build a related codebook.
This material is based upon work supported by the National Science Foundation under Grant No. ICER-2019758.
risk communication, social science, forecasters, artificial intelligence
risk communication, social science, forecasters, artificial intelligence
| 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). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 60 | |
| downloads | 41 |

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