User Comments from a SNL 'Fast Fashion Ad' Sketch Combined with RoBERTa and BERTopic Outputs

Context This dataset was created for a Master's thesis in Digital Humanities by Ka Yee Suvini Lai (see Related Works for the thesis paper titled: Emotion Classification, Topic Modelling, and Discourse Evaluation of Audience Responses to SNL's Fast Fashion Sketch on Social Media: Leveraging RoBERTa, BERTopic and Discourse Analysis ). The dataset consists of user comments from a SNL sketch titled 'Fast Fashion Ad', extracted across YouTube, Instagram and TikTok (n=4028).

The dataset also contains emotion classification and topic modelling outputs from RoBERTa and BERTopic. Data Structure The dataset consists of the following columns (with explanations in brackets): comment_text (this column contains the user comments of the SNL sketch from Youtube, Instagram and Tiktok) top_emotion (RoBERTa's output of the highest emotion score from the comment) emotion_scores (RoBERTa's output of all the emotions and their scores from the comment) topic (BERTopic's output for the topic number for the comment) topic_label (BERTopic's output for the topic number and topic label for the comment) probability (BERTopic's output for the probability of the topic from the comment) This dataset is a .csv file and is interoperable across many digital tools.