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Im doing a Java application where I'll have to determine what are the Trending Topics from a specific collection of tweets, obtained trough the Twitter Search. While searching in the web, I found out that the algorithm defines that a topic is trending, when it has a big number of mentions in a specific time, that is, in the exact moment. So there must be a decay calculation so that the topics change often. However, I have another doubt:

How does twitter determines what specific terms in a tweet should be the TT? For example, I've observed that most TT's are hashtag or proper nouns. Does this make any sense? Or do they analyse all words and determine the frequency?

I hope someone can help me! Thanks!

erisco
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Lais Varejão
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2 Answers2

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I don't think anyone knows except Twitter, however it seems hashtags do play a big part, but there are other factors in play. I think mining the whole text would take more time than needed, and would result in too many false positives.

Here is an interested article from Mashable:

http://www.sparkmediasolutions.com/pdfs/SMS_Twitter_Trending.pdf

-Ralph Winters

Ralph Winters
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  • Thank you so much for your help! But I'm really interesed in the proper nouns parts. Do you have any information on this? Perhaps they do some kind of term boosting! – Lais Varejão Apr 08 '11 at 19:04
  • Another thing to consider is string similarity comparision. If the trending topic is "Harry Potter", you can see "HarryPotter", "harry is potter", and lots of similar search results in the trending topic. I've found a [trending topic research by HP](http://www.scribd.com/doc/48665388/Trends-in-Social-Media-Persistence-and-Decay) while searching. It is a little mathematical, but you might want to give it a shot – emrahgunduz Apr 09 '11 at 10:37
  • @Lais - No information on this. However, as the article suggests, recent names in the news are considered very topical, so I would not be surprised to some term boosting going on for these types of nouns. – Ralph Winters Apr 15 '11 at 19:46
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You may be interested in meme tracking, which as I recall, does interesting things with proper nouns, but basically identifies topics in a stream as they become more and less popular:

And in Eddi, interactive topic-based browsing of social status streams

silverasm
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