@@ -36,12 +36,14 @@ After the human needs have been successfully assigned for all essays, we evaluat
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> The system scored an accuracy of roughly 28% for Maslow categories, while scoring merely 7.7% for Reiss motives. Just as we had conjectured at the beginning of our project (and also experienced ourselves during the Inter-Annotor-Agreement phase), the assigment of Maslow categories is significantly easier for both the system and us human. This is due to the more coarse-grained nature of the Maslow categories, which only consist of 5 categories and thus leavey the system and us human less options to choose from. With a broad spectrum of possibile categories to choose from, the system struggles more and has significant difficulties to assign the correct Reiss motive (though it did assign the correct Maslow category for many examples). <br> The more fine-grained nature of the Reiss motives provide much more options, some of which correspond heavily to one another, which makes the assigment of a correct Reiss motive even more difficult. This confirms our study conjectures at the beginning: <br> **The classification of more coarse-grained categories works signiifcantly better than that of fine-grained categories.**
>>Though the results may seem disappointing at first sight, we're still somewhat satisfied with them as we had to use a different, more naive approach, which was still effective in assigning human needs. For the accurate consideration of our results, we also need to take the nature of our texts into account. Entire paragraphs provide much more tokens and thus also much more information, which also makes them more difficult to process. Another factor that contributes to the difficulty of these texts is that they are all of varying lengths. Still, at least for Maslow, the system was able to score satisfying results.
