In Symplur, we distinguish “Keywords” from “Topics.”
A Keyword is just that: a word, or a short string of words like "diabetes," or "gestational diabetes."
When you select a keyword as your dataset you will call up the tweets that contain that specific word or string of words in the text of those tweets.
A Topic on the other hand is entirely different: it's a group of hashtags that are related to the name given to that Topic. For example, the Topic of “Diabetes” contains over 450 hashtags that we’re tracking related to the general subject area of Diabetes.
For the Topic of “Type 1 Diabetes,” we're tracking over 130 hashtags that are related to the subject area of Type 1 Diabetes.
And for the Topic of “Gestational Diabetes,” we have 5 hashtags that we’re tracking that are related to the more focused subject of Gestational Diabetes. So when you select a Topic as a dataset, you are actually selecting a whole group of related hashtags all at once, and you will get tweets that contain one or more of those hashtags in them.
Lastly, Topics only include hashtags, nothing else.
If you’re wondering which contains more tweets — a Topic or a Keyword — you won’t get a consistent answer because it really depends on the Topic, how many hashtags it represents, and how popular any of those hashtags are.