The text in these spam tweets are not easy to recognize.
They do not repeat. They are mixed of different words and they contain a
link.
They seem to be sent via web.

The ranking and discarding some mentions will not completely resolve the
problem.
Because our mention data and trending words data both were affected. We
donot want to eliminate tweets from innocent people who have few followers.

The simplest way seems to be just ignoring the tweets coming from outside of
the community.
But those tweets were helping us to extend our network.



On Fri, Nov 26, 2010 at 6:42 PM, Adam Green <140...@gmail.com> wrote:

> As long as you aren't trying to capture and deliver *all* tweets,
> there are a couple of good ways to cut out spammers. One thing I do is
> save all mentions for all users in a database of tweets. When a tweet
> comes in from the streaming API, I collect @mentions, and store them
> with the screen name of the tweet's author and the screen name
> mentioned. Then I can rank users based on the number of different
> accounts that mention them. If you only use the tweets from the top N%
> of users, the quality improves a lot. I find that the top 80% is
> usually enough of a screen to get good quality.
>
> Another trick is blocking duplicates from each user. The API only
> blocks duplicates that repeat immediately, but if a spammer has a list
> of tweets, and cycles through them, all the tweets get through. I
> compare all new tweets with the other tweets from that user. This is
> very expensive if you have a big database. This can be made less
> intensive by limiting the comparison to just the tweets from that user
> in the last few days. You can also run this with a separate process
> that doesn't slow down you main tweet parsing loop. Most spammers are
> so simplistic that they just repeat the same tweet over and over. In a
> real spammy set of keywords, if I find more than a few duplicates from
> a user, I just stop saving their tweets.
>
>
> On Fri, Nov 26, 2010 at 11:26 AM, Furkan Kuru <furkank...@gmail.com>
> wrote:
> >
> > Word "lol" is the most common in these spam tweets. We receive 400 spam
> > tweets per hour now tracking 100K people.
> >
> > We plan to delete all of the tweets containing "lol" word. It is also
> used
> > by our users (Turkish people) writing in English though.
> >
> > Any better suggestions?
> >
>
> --
> Adam Green
> Twitter API Consultant and Trainer
> http://140dev.com
> @140dev
>
> --
> Twitter developer documentation and resources: http://dev.twitter.com/doc
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> Issues/Enhancements Tracker:
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>



-- 
Furkan Kuru

-- 
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