Displayr

Bring back the large text box at the top of the coding tool to see the full text. This was very useful for the customer to copy and paste the text to do further analysis. The main reason for bringing this back is because it is very difficult to see the text when expanded and the text is white with a blue background.

Be able to click on text in the coding tool (right hand side of tool where all the open ends are) and copy the text and paste it into another app or web browser. Reason for this is that with some responses in the medical field, they have technical names for drugs. They would look up further information on the drugs to make better categories and know who is the maker of drugs.

Currently, when a user selects a text variable in the data set panel , they get a list of suggested TEXT ANALYSIS options in the object inspector : * Categorize list of items * Categorize unstructured text * Extract entities * Sentiment I submit that this list is seldom what the user wants to do. And the primary suggested TEXT ANALYSIS tool(s) should be either (or both) of: Semi-automatic or Manual categorization . Of course, the interface would need to allow for the user to select if they want Mutually exclusive or overlapping categories and if they want to re-use an existing codeframe. But I believe nudging users to Semi-Automatic or Manual Categorization would be useful (and avoid support tickets where users have inappropriately applied one of the other tools).

With larger data files, when wanting to code a list of items/brands doing Semi Automatic categorization using Displayr AI, Displayr takes a significant amount of time to process the data and sometimes does not complete the categorization. Can we allow users to specify that they are trying to code a list of items i.e. I am trying to code a list of cola brands, each response only has one brand.

The user would like to be able to filter Text Responses on another question when coding. If not Filter, an option would be to show responses to another question alongside the text response. The idea is that a user knows if (for example) if a text response is for Satisfied or Dissatisfied users. The current workaround is to create new filtered text variables.

When working using text analysis with brand lists, there are usually a number of variations in spelling, which leads to an extensive list of categories that should be bucketed into one group. For example, Coca-Cola, Cok, Coca Cola, Coka, Coke are all part of the same brand. I must Delete and Reclassify or Delete each category one by one to remove the unwanted codes. It would be great if I could Delete/Delete and Reclassify them all at once. I thought I could update the list to Import/Export Category Names, but it would not allow me to make this change. I got this warning "There is already a node with that name!" See details: https://www.loom.com/share/fb254d92d0264047b27b5066433719b5?sid=467a6f25-2a36-41c9-9626-703a68c4e4fe

Right now, the text categorization tool automatically categorizes any blank text responses as "Missing data." However, sometimes users want to be able to still categorize those blanks into their categories. This feature would add the option for users to control if/when that automatic coding happens. This can be used in conjunction with https://displayr.canny.io/admin/feedback/displayr/p/ability-to-filter-text-responses-when-coding?boards=displayr to further extend the capabilities of the coding tool.

Displayr AI-assisted text categorization is a leap forward, but I think the user experience can be improved significantly to avoid situations like the following: A user uses Displayr AI to code a large number of open ends (e.g., > 1,000), which Displayr says "may take a few minutes." The user's held captive for a while thinking it'll be done in a few minutes like Displayr says, but it ends up taking more than an hour. A user uses Displayr AI to code a small number of open ends (e.g., < 100), which Displayr says "may take a few minutes." The user steps away for 15 minutes thinking it won't be done for a few minutes like Displayr says, but it's done in 30 seconds. It's all about setting realistic expectations, so users can act and plan accordingly. Telling all users that Displayr AI-assisted text categorization "may take a few minutes" isn't acceptable. I know it's difficult and involves a lot of factors outside of our (Displayr's) control, but we need to give users a better time estimate based on the volume of text data they’re trying to code w/ Displayr AI. Displayr's all about saving time, and Displayr AI-assisted text categorization, although very powerful, currently puts users in bind and can cause them to waste a lot of time. In short, saying it "may take a few minutes" is way too vague.

When a text variable is categorized using DisplayrAI, some response values may not get categorized into one of the categories. Presumably, this is because the algorithm was not confident enough to assign it into one of the existing categories. This feature request suggests that users be able to adjust the confidence parameter such that a value is categorized into a code.

When using the function Anything > Advanced Analysis > Text Analysis > Advanced > Setup Text Analysis, a single text variable is required. This user would like the ability to be able to use Text Multi Variables as well