Adding words to improve classification
I am familiar with basic classification (given a span of text, what label should it get) but I am wondering about scenarios where there is more than just a span of text to use.  Let’s imagine a scenario where in addition to the text, there is also a date, location, and time. If one (or all) of them were appended on to the text, would this hurt or help the classification?  I can see it going both ways. Has anyone tried doing something like this?Another similar scenario would be for tweet classification. The tweet contains emojis/emoticons and urls, so every time there is an emoji/emoticon, a description of the face or emotion replaces the emoji/emoticon (becomes “happy”,becomes “sad”) and then the url (https://www…) gets turned into the word “url” or “link.” Does this information hurt or help the classifier?I will probably try it out myself, but I’d like to hear from others for their perspective or experience.