I have a survey that's fielding with commercial sample, and based on reviewing open end responses, I have 50+ respondents that are fraudulent / not giving good responses, and I want to set a flag to identify them in the data. I have been setting up a big filter: "if any of these are true: userID=..." and then putting all 50+ IDs into the filter, each on a separate line, then editing the filtered cases. Setting up that filter is a pain, is there a way to do it as a batch? I think I could download the dataset, add a variable that identifies bad cases and then re-upload, is that true? Are there any other faster / more efficient ways to approach this?

Create a new field in the data and analysis tab, use the filter function to filter out the relevant ones and then add a value to them.

Most efficient way to remove bad respondents?

Most efficient way to remove bad respondents? | Experience Community