Table 4. RAT use cases.
| Study type | Field | Search engine and source scrapers | Number of search results | Evaluation view | Classifier or extension | Reference | |
|---|---|---|---|---|---|---|---|
| Conducted with current RAT version | Classification study (automatic) | Political science | Organic results from Google | 1,372 | None | SEO classifier | Hinz, Sünkler & Lewandowski (2023) |
| Content analysis | Library and information science | Results from SUB University Hamburg library system | 5,948 | Biases in library catalogues | None | unpublished student work* | |
| Media and communication science | Organic results from Google | 5,710 | None | Query sampler extension | Ekström & Tattersall Wallin (2023), Haider et al. (2023) | ||
| Source distribution analysis | Information science | Organic results from Google, Bing, DuckDuckGo, and MetaGer | 141,480 | None | None | Yagci et al. (2022) | |
| Organic results from Google | 378,581 | None | None | Norocel & Lewandowski (2023) | |||
| Conducted with previous RAT version | Interactive Information retrieval study | Information retrieval | Organic results from Google and Bing | 2,288 | Relevance assessments | Search logger extension | Sünkler & Lewandowski (2017) |
| Retrieval effectiveness study | Information retrieval | Organic results from Google and Bing | 22,000 | Relevance assessments | None | Lewandowski (2015) | |
| Organic results form Million Short | 750 | Relevance assessments | None | Schaer et al. (2016) | |||
| Organic results from Google and Bing | 20,000 | Relevance assessments | None | Lewandowski (2013) | |||
| Results from EconBiz library system | 35,158 | Relevance assessments | None | Behnert (2015), Behnert & Plassmeier (2016) | |||
| Not conducted with RAT, but could have been supported by RAT | Information quality study | Health | Organic results from Google, Yahoo, and Bing | 49 | Quality assessments | None | Janssen et al. (2019) |
| Information science | Organic results from Google | 60 | Quality assessments | SEO classifier | Schultheiß (2023) | ||
| Classification study (manually) | Health | Organic results from Google | 540 | Classification of source types | None | Döring (2017) | |
| Media and communication science | Organic results from several search engines | 3,350 | Classification of fake news | None | Mazzeo, Rapisarda & Giuffrida (2021) | ||
| Content analysis | Health | Organic results from Google | 227 | E.g., portrayal of immune boosting | None | Rachul et al. (2020) |
Notes.
*
This study serves as a representative of the large number of student work supported by RAT. For more student work, see https://searchstudies.org/research/rat/.