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I've looked into this a bit, albeit more in a spam-filtering context; tweets have very little text for naive Bayes to latch onto. 140 characters would be 20-30
by kmavm 16y ago
I've looked into this a bit, albeit more in a spam-filtering context; tweets have very little text for naive Bayes to latch onto. 140 characters would be 20-30 words, tops. That is so few words that it is hard to move the prior very much, unless there are blockbuster words that almost always indicate a bad tweet; as the article suggested, "breakfast", "beer", etc.
- jshen 16y agoDont many classifiers pick the most interesting n words and only use those to decide? Where n is something like 15.
- JCThoughtscream 16y agoFilter by account, then, instead of by post? With a sample body of, say, the ten or twenty of an account's most recent posts.
- kmavm 16y agoThe article's whole premise was that tweet quality does not correlate well within an account; e.g., some marvelous twitter streams include breakfast tweets.
- sketerpot 16y agoAs I said, I'm fine with a filter that has poor accuracy, as long as it makes twitter marginally better.
- fizx 16y agoHere's a start. It's a simple ruby app that runs on heroku and proxies your twitter account, dropping uninteresting things. Extremely raw code. http://github.com/fizx/sometweets http://github.com/fizx/sometweets http://sometweets.heroku.com/ http://sometweets.heroku.com/