I have a dataset with two columns of interest, one a "Response" column (where participants in a task could respond through typing what they believed a presented image was - so the class being a "character" for their responses). The second column is an "Image" column (containing the name of the actual image presented).
What I would like to do is see how many of the Responses do not match what the image actually was. As there are multiple words participants can characterise and name an object, I would also like to have several options for what is acceptable for the response to be. What I have done so far is to try and use the filter function for each of the 300 images that have been presented, including all responses to the presentation of one individual image and all responses to that image that contain the word that is correct. See below:
Image1CorrectAnswers <- data %>% filter(data$Image == "Image1.jpg", data$Response == "bike")
What I was wondering however, is 1) whether it is possible to use the filter function for responses that do not contain the correct word for that specific image? 2) As well as whether I can have multiple different "acceptable" words to "filter" out correct responses from the incorrect ones (as different participants can answer differently to the same image, and yet both be correct). The goal is to have a final variable for each of the 300 images containing only the incorrect responses.
Thank you in advance.