Paige

Data within YouTube is the number of views, likes, and comments that individual people use to interact with videos that they either like/dislike. The option to dislike a video is also a feature that viewers can use but these days it’s unlikely you’ll see a dislike count. This is important for my analysis because paying attention to what types of videos are pulling higher views, can tell me what type of content specific audiences are looking to interact with the most. This allows me to understand which videos are more likely to perform well from a creator within the genre of content I’m analyzing in my project.

Since I’m working with YouTube channels the main elements of data that matter would mainly be views, likes, and comments. In my project, I’m focusing on views counts because I feel like it’s the best way to see how the majority of people are interacting with posts. When it comes to YouTube, people engage through likes and comments but I think it’s a lot less common than a platform like instagram. I think this is clear in the ratio between views and likes on a single video, many people will watch a video but a fraction of them will leave a like and even less will leave comments.

Right now, I have each YouTube channel I’m working with graphed individually rather than all together in one graph so that it’s easier to see trends across all three channels since they all have different sized audiences. This has made it easier to see if there’s an overall trend when it comes to specific topics. Keeping the channels graphed individually has helped keep me more organized and has lowered my chances of getting myself confused. If I were to make a graph that included all three channels for one specific topic, such as views, the graph would end up being unhelpful since one channel I’m working with has a significantly higher viewership than the other two.

My approach when answering my research question is to come at the data from an angle of if more people will view a paranormal themed video that is covering real listener stories, will they be more likely to watch the video because will this be more likely to gain the viewer’s trust? Or will the viewers be more open minded to the video? I think this perspective makes the number of views more meaningful as it shows more of a human connection rather than just a view count.

@npfannen

So I had to pivot with my research and I ended up changing the accounts I’m working with, but I ended up picking three different paranormal themed podcasts on YouTube. My research question is: If a video title mentions there will be stories from real people, will it garner more views? I think this adds to the conversation about content strategy because it will show whether viewers are more likely to click on a video about a paranormal topic if it’s coming from other alleged real everyday people. This could show if this brings the viewer a sense of trust by sharing stories from other people that could be similar to them.

When choosing the accounts I will be working with in this new project, I wanted to stick to one singular platform instead of crossing because I honestly just wanted to keep the data straightforward. I chose to do three YouTube channels, I’m looking forward to working with a different platform since the data collection process might look a little different this time. I also chose some relevant channels to me that I’ve been watching lately and that all have somewhat of a similar theme between them. Each of them consist of current events in one way or another and I wanted to explore how people are interacting with different types of videos relating that theme.

I thought it was interesting taking notice to the fact that some social media posts can be discerned easily between each other by looking at the number of likes they have but the numbers of shares can be similar. For example, in my data set I have a post that has about 400 likes and compared to a post with 200 likes, the number of shares are pretty much the exact same. It seems that it could be the same people continuously interacting with these posts each time. The number of likes will set posts apart but shares seem to stay at seemingly average rate.

I’m analyzing @millersvilleu on instagram and I’ve noticed that the highest performing posts within my set of data, are either related to offering resources to students, or helping students get involved and connect on campus. The lower performing posts are some of the relatable TikTok/Reels adjacent posts that seem to sometimes target specific types of students, filtering out other viewers/followers.

@npfannen

As of right now, I don’t think my hypothesis is entirely correct based on all the data I collected, it’s more of an in between. For context, I’m using the @millersvilleu instagram page and my hypothesis is relating on-campus events and the amount of shares related to those types of posts. The data I collected has situated my hypothesis sort of in the middle, not completely untrue but not entirely true based on all of my data. How I’ve been going about writing my essay is that I’ve just been going through the highest performing posts with shares to the lowest and comparing this information with the different engagement indicators in Capriotti’s article. I think the writing portion has been a little confusing because my hypothesis isn’t entirely correct, so working around it and explaining my data regardless has been a challenge.

I think it’ll allow me to think more critically about different types of information and recognize patterns within information and data. I think for me personally, if I decide I want to make a dedicated social media page and I wanted to try to build a following through it, I think I could definitely think back to working through this process and notice how it would help me become more aware of how to reach an audience. More generally, I do this assignment so far is helping me understand the overall reasoning for why data collection is important outside of just working through the practice project.