I would like to have your suggestions regarding the kind of statistical analysis that would fit the nature of my data.


Participants have seen 12 videos, in each of which an emotion was conveyed and they had to guess which emotion was conveyed in each video (I plan to do a separate analysis for each video, so 12 similar analyses in total). Participants were presented with 36 words and had to choose the word that correspond to the emotion conveyed. The independent variables will be categorical (such as native speakers vs. learners vs. non-speakers of Chinese; advanced vs. intermediate vs. beginner proficiency level; etc).


I would like to not focus on whether they chose the ”right” emotion which was intended to be conveyed in the video (so it’s not a dichotomous dependent variable), but I would like to see the different patterns between my groups: e.g. what is the FIRST most chosen word among among the native speakers vs. among the learners vs. among the non speakers, what is the SECOND (THIRD, FOURTH, ...) most chosen word among among the native speakers vs. among the learners vs. among the non speakers, ... and are these between-group differences significant?

Basically, I would like to see where the differences in this bar chart are significant (this corresponds to the data for the video in which the emotion "afraid" was conveyed, broken down by Status of Chinese).

I have thought about Chi-square, but that will not allow me to look at interactions. I have also thought about multinomial logistic regression, but the problem is that you have to specify one of the categories of your DV as baseline against which all other categories will be compared, whereas I would like to compare all the categories with each other.
Inferential test for differences in frequencies between groups?-output2__document2__-_ibm_spss_statistics_viewer.jpg