Not only does this chart only document a time when SHINee was inactive, but SHINee are also not active in the US promotional circuit, media play, and aren’t participating the current sensationalized news of companies like UMG buying their way into kpop btw https://twitter.com/kthcertified/status/1383078609271721987
Let’s talk about analyzing data! So if we know anything abt internet data, we know that these numbers only represent the amount of people.

In related topics, we can see why these numbers are so high. For example we know that MTV exposure has helped w/ these numbers
It’s related bc these topics are commonly discussed together essentially— or by the same people. this is not the same as clickthrough which be more direct data.
For SHINee we actually see rising topics related to them rn are other kpop idols and groups— meaning that the people talking about SHINee are kpop fans, not really media. (Notice how older groups are here too, so long-time kpop fans)
In the top related topics for both groups you actually have the members of respected groups. This is most likely fan searches which would be consistent over time. If you see non-member searches SHINee’s is Kpop and B*S’ is “album” so again we can see consumer habits are different
I have a more specific and accurate tool I use for work so lemme brb with that
Let’s start with these twitter analytics:
Most results in general on twitter come from retweets, not unique posts, as we see here. Obviously the numbers for B*S are super big compared to SHINee, but lets take a look at why that is
If you look at the keywords over the past year, you can see that conversation around shinee occurs in different languages, meanwhile keywords associated with b*s are promotional (as in likely spam to inflate voting numbers)
Another really interesting thing I found was that a VERY LARGE portion of SHINee’s audience is actually in Japan
I should close my thread w this lol https://twitter.com/aquariancity/status/1383111147923066886
Also as a disclaimer: this is my analysis of the data! My analysis isn’t necessarily objective, but the results I’m posting are.
You can follow @aquariancity.
Tip: mention @twtextapp on a Twitter thread with the keyword “unroll” to get a link to it.

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