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My research question is going to help guide what kind of data I am going to collect. Though I intend to collect a lot of data, I want to make sure that I don't collect data that is irrelevant to answering my research question, so that I don't waste time and make the data analysis more difficult than it needs to be. Since I intend to investigate how content's subject matter affects the amount of engagement it gets, relevant data will help me determine the amount of engagement a video gets, as well as data that relates to the subject of the content.

I am intending on collecting a lot of data for my project. I don't want to overdo it but judging from the last project it seems that the more data you have the easier it is to answer your research question as you have more to work with during the analyzing phase. Meaningful data is data that is going to help me to answer my research question. One mark of meaningful data is whether or not it can help gauge audience engagement. This includes views, likes, and comments. Another mark of meaningful content includes information about the subject matter of the video itself, and what type of content the creator is presenting. I will be recording this data in an excel spreadsheet. Some of the data related to subject matter will be more difficult to quantify, but will be determined by me watching the video and recording statistics and observations that I make in the excel sheet.

My research question is: how does the subject matter of content affect how much engagement the content gets? The data I was planning on collecting includes titles, thumbnails, views, likes, comments, dislikes, the description, the time and date of the post, video length, the amount of comments, and content of subjects and themes in the comments section. These data points are relevant because they can help me gauge how much engagement each piece of content is getting. The difficult part is going to be relating this to the subject matter of the content in a relevant way, and figuring out why certain topics/videos get more engagement from the audience from others.

Are there any data points that you recommend collecting from YouTube accounts that one may not think of right away? I'm trying to collect as much data as possible so that I have a lot to work with during the data analysis. I was planning on titles, thumbnails, views, likes, comments, dislikes, the description, the time and date of the post, the amount of comments, and some of the content in the comments section getting the overall tone and topics discussed in the comments section. Is there anything else you would recommend I look at? I was also wondering about YouTube shorts, I was planning on just not recording data for them and only using actual YouTube videos, but do you think it would be beneficial for me to include anything from the shorts?

During the last project, I learned that writing a research question was more complicated than I originally would have expected. One thing that I did wrong the first time was looking at the content before formulating my research question. In doing so, I began to try to look for trends in the content sort of subconsciously, which affected my research question. This time around I intend to look at as little of the content as possible before coming up with my research question as to not be influenced by trends that I might see before starting the data collection. It is also important to pick a research question that is both fairly broad, so that you have enough to write about with the data that you collect, and also a research question that is interesting to you so that you stay engaged with the project.

First and foremost I learned that the more data you collect during that phase of the process, the more information you will have to work with when analyzing different trends and aspects of the data later on in the process. Therefore it is important to collect as much information about the content as you can in the early stages. I also learned that data can be found in unexpected places. You want to look for statistical data and contextual data in ways that you may not initially expect. An example of this from the last project was analyzing what the content of the comments on the posts I was looking at.

I'm trying to narrow account choices in a number of ways. To begin, I'm trying to analyze accounts within a community that I am familiar with, but not too invested in. At first I was thinking about researching accounts I was really into but after considering the notes about not ruining content that you follow for enjoyment by analyzing them, I decided to go with accounts that I don't know quite as well. I also narrowed down the platforms of the accounts I want to research to Instagram or YouTube. Those are the platforms I'm most familiar with so I think the data collection and analysis will be easier if I use them. I will probably go with YouTube because that is the platform that I use the most and I think it would be most interesting to research.

I'm pretty into comedy and I was thinking about doing my project using Instagram pages within the standup comedy community. My only concern was appropriateness of the content within a classroom setting. I was thinking about blurring out words within content that I deemed relevant to my project if necessary. Would this be a good way of going about it? Would you recommend using another community entirely? I am familiar with other communities within Instagram so this wouldn't be an issue, I just thought it might be interesting to do my project on pages within the comedy community but don't know how sensitive/cumbersome the censorship component of the project is going to be within a classroom setting. I am just brainstorming on communities to do the project on right now so I am not set on this if it might be an issue.

This is a youtube channel that I listen to pretty frequently, they narrate horror stories from authors like H.P Lovecraft. I usually listen to it to help me fall asleep, the narrator's voice is relaxing.

One of the main arguments of my paper is that by looking at the comments of a post, you can tell whether a post is successful or not. Is this sound logic? This is a big point in my paper. My thinking is that even if a post doesn't have that much engagement from likes or that many comments, you can tell from the few comments it has whether the purpose of the post reached the audience or not. An example I used is a post congratulating a student for defending a thesis, and used the comments from her friends supporting her as proof that the intended purpose of the post reached its intended audience, therefore making it successful. Is this a strong enough argument to be a main point in my paper or should I strengthen/ expand on this further?

I'm wondering if the purpose of this graph comes across effectively to the reader of my essay. With this graph, I tried to show how there was no correlation between comments and likes. However, since there is such a low amount of comments compared to the likes on each post, I'm a bit concerned that the point I was trying to make with the graph doesn't really come across that well. Is there enough data for this point to be understood? Is there maybe another way that I could show this in a different form, or perhaps edit the graph in such a way that shows this more effectively. I might be overthinking this, feedback would be much appreciated!

I am wondering whether or not this graph is clear and easy to understand enough. With this graph I show the correlation between hashtags and likes for the ten posts I analyzed. I feel like it is pretty straightforward and easy to understand, but looks a bit empty. Should I maybe add something to this graph? The one thing I was thinking about doing was labeling each post with a description, instead of just post one, post two, etc. Before submitting this in my final draft I also have to figure out how to remove the column 1 from the legend of the chart as it is not needed.