Applying one simple regex to the text body of the previous one million tweets creates the most amazing result.
re.findall(r'((?:[A-Z][a-z]+\s?)+)(?<!\s)', full_text) turns into a list of what is currently trending on Twitter. Simple, powerful and elegant.
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Sometimes just ranking hashtags doesn't tell the entire story, but I'm amazed that a small little regex can cut through the noise so nicely.
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I don't understand how a pattern matcher can be linked to finding "Trending", which is purely regression analysis (?). Unless of-course all the valid strings in your data are just already ranked trending topics.
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You are correct. I should have clarified a bit. Basically it is extracting proper nouns that are capitalized so it is really picking up people and places that are currently ranked high in activity.