The basic content analysis I conducted was counting the number of positive and negative comments seen on all 25 of the YouTube videos. I selected the comments but using the 25 top comments under the comment section, that had either the most likes, dislikes, or interaction on them making them a top comment. I also kept track of the number of likes, dislikes, and subscribers that were seen throughout all of the 25 videos. While examining those numbers, I looked to see if there were any themes shown for each of the influencers five videos in the activity or content that they created for their channels.
The interpretive content analysis I conducted was looking at the types of comments that were posted within the videos, searching for recurring themes, and new themes that arose after the scandal. I specifically analyzed for comments of negativity, hate, rejection, positivity, and forgiveness. When coding these comments, I coded for specific words and phrases such as “love”, “support”, “disappointed”, and dismissive comments, that did not necessarily have to do with the perception of the video. For example, on an apology video, someone commented on the color of the walls. That is something that is not important to the public perception nor the influencer. The public’s perception of these influencers was assessed based on the most common activity and recurring themes that was seen within all 25 videos in relation to the public eye. Along with these comments, for interpretive content analysis, I also looked at the influencers nonverbal behaviors such as facial expressions, hand gestures, and eye contact.