Iām revising my Data Analysis, and the main issue is that I didnāt include enough discussion around each graph. Could you tell me what parts feel too short or unclear?
Does my explanation help the reader understand what the graph shows?
Should I add example posts here to clarify the trend?
My Data analysis section:
For this project, I collected 30 posts from 3 different stars in season 34Ā of Dancing with the Stars Instagram accounts: Alix Earle, Whitney Leavitt, and Robert Irwin. Every post was coded into content types based on how it related to the show (Performance, Behind the scenes, and Personal). Ā
I recorded the number of likes and comments on each post. I did not include shares in the dataset because Instagram does not clearly show share counts on every post, and I wanted to use numbers that were visible and consistent across all three accounts.Ā
Across all three influencers, the graphs show that content type does affect engagement, but not in a single, simple way. Each creator has a slightly different pattern for which posts get the most likes and comments.Ā
For Robert Irwin, performance posts showed the most engagement. The average likes for his performance post were 569,750 and an average of 5,596 for comments. These numbers are drastically higher than the behind the scenes and personal likes/comments averages. In his graphs, personal posts are slightly higher than behind the scenes posts in both likes and comments (see Figure 1 and Figure 2). This pattern supports the idea that Robertās audience enjoys seeing his hard work throughout the week come to life in his performance, not just the fun and silly side behind the scenes.Ā
For Alix Earle, the pattern is different. HerĀ behind the scenes pull the highest average likes and comments of 446,333 for likes and 927.5 for comments (see Figure 3 and 4). These posts are more authentic and allow the audience to feelĀ closer to the influencer. When watching her videos, behind the scenes footage gives the audience the feeling of friendship as they get an insight into their life rather than just an update from an event or brand deal. This type of content is also more enjoyable as it is typically silly/unprofessional or creative rather than serious and professional. Ā Performance posts also do very well with an average of 393400 average likes and 901 average of comments. This shows that the audience loves the authenticity behind the scenes but also loves to see the hard work pay off in the ballroom. Ā
For Whitney Leavitt, the data shows more of a mixed pattern. Whitney's engagements in likes and comments show the same results, however; the average comments are drastically different compared to likes (see figure 5 and 6). The average of likes is the highest in personal posts with a 170,728 average. While performance is just below with a 169,000 average. These two categories vary only slightly in likes. Meanwhile, in regard to comments, the highest engagement average is still personal posts with an average of 3,742 but the comment average of performance was lower at 2,564. This data shows that Whitneys audience loves to see her personal life while also supporting her in the ballroom. But the audience can relate and engage more to her personal content rather than on DWTS. Ā
When comparing all of the data, there is no single content type that always āwinsā. Each influencer has a different audience and therefore has a different content type that their audience prefers. Overall, comments generally rise and fall in the same pattern as likes, which means audience interaction follows the same trend as basic visibility.Ā
Taken together, these patterns answer the research question: yes, the type of content posted does influence engagement, measured through likes and comments, but it depends on the specific influencer and their relationship with their audience. The hypothesis predicted that behind the scenes content would have the highest engagement overall. The data only partly supports this. For Alix, behind the scenesĀ posts often do have the highest engagement, but forĀ Robert performance had the highest engagement, and Whitney, personalĀ content had the highest engagement. Ā
Overall, the data shows that content type matters, but it interacts with each influencerās brand and audience expectations.Ā Behind the Scenes posts are powerful for some creators because they feel authenticĀ and personal; performance posts are more powerful for others because they feel exciting and event based. While personal posts are more powerful for others because their audience already likes this content since these influences had previously establishedĀ an audience before DWTS and enjoy their typical content outside of DWTS. This mixed result is important because it shows that content strategy cannot rely on one rule like ābehind the scenes always wins.ā Instead, content creators need to look at their own data, their own audience, and how different post types perform over time.Ā
