I am a social media manager, and I am hoping AI will be helpful in doing analysis of social media metrics to help improve engagement on the accounts I run. I am not a data scientist or statistician, so I am not familiar enough with the vocabulary to know how to explicitly ask Julius for a type of model that would be helpful. But what I am looking for is insight or trends that I would otherwise not be able to tell on my own, or with simple analysis. Something deeper than pulling out commonly used key words in comments, or basic themes from our content. And more than just telling me which times of the day are the best to post.
What are some realistic use cases for Julius to give meaningful analysis of our social media content? Do you see it improving greatly in the near future?
Hey deelaina! It’s tough to give specific examples of how to use Julius to analyze social media data without knowing the exact data you have on hand. That being said, here are some ideas:
Adding labels to specify content format (eg. product announcement vs. interview vs. guide) or type (eg. humorous/informative/educational) or topic, then using Julius to compare engagement based on these labels. You may even be able to use Julius to perform the labeling as well.
Performing clustering analysis
Running different forms of sentiment analysis over the text content, then analyzing to see if there is a correlation between sentiment and engagement.