Show summary data about the current file such as number of factors
Sometimes you might want to work with a pre-determined list of possible factors. This is sometimes called “deductive coding” or “(partially) deductive coding”.
Or you might be working on a larger project with colleagues and you want to periodically share your codebook.
Simply type or paste a list of pre-determined factor labels in the box. They are saved with the file.
These factor labels will then be presented as options when you code.
When you upload data, you can optionally provide a table of sources. The source IDs in this table will usually correspond to the source IDs in the statements table. The other columns in the sources table such as gender provide additional information about the source which provided each statement - for example if statement 123 has source ID s89, and there is a row in the sources table with source ID s89, and this row says that source s89 is female, then the app knows that statement 123 was provided by a female.
When you look at the main sources table in the Tables section of the app, you will see only sources whose ID corresponds to statements in your file. The sources table in this sub-page shows what you uploaded, which might be different - for example, you might have already uploaded information about sources which do not yet have any statements. Or there might be a discrepancy in the way the IDs have been provided, for example A1 is not the same as a1.
Manage all your files and show summary data about the current file such as number of links. As usual you can sort this table by clicking on the headers, search all the text, or filter individual columns.
These three buttons are useful:
There are quite a few metrics, some are more self-explanatory than others. The table below expands on the brief description given in the metrics table.
🎓Metrics with this “mortar-board symbol” are well-known network metrics.
| Metric | Explanation |
|---|---|
| size | The total number of links in the map. |
| order | 🎓The total number of factors in the map. |
| links_per_factor | The average number of links per factor. Usually, you want to have plenty of links per factor. |
| n_statements | The number of statements in the map. |
| n_words | The total number of words in all the statements. |
| n_coded_words | The number of words in coded phrases. |
| n_characters | The number of characters in all statements. |
| links_per_statement | The number of links per statement. |
| percent_coded | The percentage of statements which have been coded. |
| component_count | 🎓The number of unconnected components in the map. Do you have islands in your map? The app first identifies the components – sets of factors which are all (“weakly”, i.e. ignoring the direction of the links) connected to each other by some path; then counts how many separate components there are, i.e. none of the factors in one component are connected to any of the factors in the other component(s). |
| diameter | 🎓The length of the longest geodesic or path between two factors. For example, the count for the very simple map consisting only of A->B->C->D would be three, as it’s three links from A to D. This takes into account the direction of the arrows. |
| reciprocity | 🎓The proportion of mutual connections in the map. This calculates the proportion of factors in which both factors influence one another. The connection must be between two factors, feedback loops are not counted. |
| min_cut | 🎓The minimum number of links that you would have to remove to split the map into two clusters. |
| mean_dist | 🎓The mean number of links between all factors in the map. |