Re: [twitter-dev] Call for action #StopBritneyBots
On Mon, Nov 30, 2009 at 04:23:40PM -0500, TJ Luoma wrote: On Mon, Nov 30, 2009 at 4:19 PM, M. Edward (Ed) Borasky zzn...@gmail.com wrote: Twitter, what say you? Developer community, what say you? Twitter, Inc. can't even keep up with porn spammers reported manually using the Report As Spam links, what makes you think they would be able to keep up with an automated version? As Ed demonstrated in his original message, this particular class of spambots can be detected and auto-blocked quite easily. With the information he provided, I (and I expect many others on this list) could create an anti-BritneyBot-bot to do so in very short order, if not for the potential legal/TOS issues which could arise from doing so without Twitter's official sanction. It's not a question of keeping up with them; Twitter could use Ed's suggested technique to shut them all down en masse at the cost of less than one day of a single employee's time (and they may have other techniques they could use which would be more effective and/or even quicker to implement). It's a question of will and of policy. -- Dave Sherohman
Re: [twitter-dev] Call for action #StopBritneyBots
Hopefully as time goes on twitter will start pushing out more sophisticated anti-spam measures. On twitter.com/jobs does have an open position for anti-spam engineer so they are actively seeking to form a bigger team for this cause. So if you are looking for work and are a spam killing ninja might be worth applying :). Josh
[twitter-dev] Call for action #StopBritneyBots
I'm hearing from many Twitter users that the frustration level caused by the Britney Bots is rising. I'm going to use some euphemisms to make this message safe for work, but the particular bots in question are certainly not work-safe. The _modus operandi_ of these bots is as follows: 1. Get a Twitter account. These are usually of the form small English word5 digit number. The profile picture is typically not safe for work. 2. Collect screen names somehow. They must at least be polling the public timeline. Frequent tweeters seem to get more of them. Perhaps they are doing searches as well, or mining the profiles of the screen names they've collected for more screen names. 3. Send an @ reply to each name collected. These come in bursts - I haven't done any research into the frequency at which they are sent but a number of tweets go out in a burst. The tweets themselves are not safe for work. The bots do *not* appear to be following anybody - they only show up if you do a mentions search. What's worse, though, is that people are retweeting these things! There is a movement on Twitter, using the hashtag #StopBritneyBots, to attempt to get Twitter to put some kind of filtering in place. I'm not sure what the status of that is in Twitter - perhaps some of the Twitter people on this list can chime in. Meanwhile, this particular bot has an easily-detected signature - you can collect the bot names via Twitter search! 1. Do a Twitter search for the following string (the double quotes are part of the string!): '(Click the link at top right of my profile)' Note that the returned tweets from this search will mostly be not safe for work! 2. Break each resulting tweet into space-separated tokens. 3. Scan the tokens from right to left. The first @name you encounter will be the destination victim. The second one you encounter will be the bot that sent it. At this point, you could build a bot to report the bots as spammers. Personally, I think anyone who retweets one of these ought to be considered a spammer as well. ;-) In any event, I've got some code using the Net::Twitter Perl library that collects the tweets, and I can supply a list of names to Twitter if they'd like. I'd prefer, of course, that Twitter deal with this at the inlets to the tweet stream. But I think there's a significant enough groundswell in the community that we will see bots arise using the algorithm I've described above. I've been asked to create one, but I'm holding off - there are some murky legalities involved and I have more interesting research in Twitter text mining I want to do. ;-) Twitter, what say you? Developer community, what say you? -- M. Edward (Ed) Borasky http://borasky-research.net/smart-at-znmeb I've always regarded nature as the clothing of God. ~Alan Hovhaness
Re: [twitter-dev] Call for action #StopBritneyBots
On Mon, Nov 30, 2009 at 4:19 PM, M. Edward (Ed) Borasky zzn...@gmail.com wrote: Twitter, what say you? Developer community, what say you? Twitter, Inc. can't even keep up with porn spammers reported manually using the Report As Spam links, what makes you think they would be able to keep up with an automated version? TjL
Re: [twitter-dev] Call for action #StopBritneyBots
On 11/30/09 4:23 PM, TJ Luoma wrote: On Mon, Nov 30, 2009 at 4:19 PM, M. Edward (Ed) Borasky zzn...@gmail.com wrote: Twitter, what say you? Developer community, what say you? Twitter, Inc. can't even keep up with porn spammers reported manually using the Report As Spam links, what makes you think they would be able to keep up with an automated version? +1. It's time someone created an anti-spam product that auto-blocks Twitter users that are determined to be spammers. Expecting Twitter to do this is unreasonable at this point, and probably undermines their entire business model of selling ad-blasting accounts to companies. -- Dossy Shiobara | do...@panoptic.com | http://dossy.org/ Panoptic Computer Network | http://panoptic.com/ He realized the fastest way to change is to laugh at your own folly -- then you can let go and quickly move on. (p. 70)
Re: [twitter-dev] Call for action #StopBritneyBots
Sign in to your Twitter account, go to http://twitblock.org, and drop EVERY SINGLE JUNK FOLLOWER YOU HAVE. No, the junk followers aren't britbots, but if you don't have any losers following you your britbot exposure goes way, way, way down. I'm particularly suspicious of the followers that have 800 people they watch, no profile information, and no one following them back. That's an obvious sleeper/query type thing that could be feeding such behavior. Of course, you have to start valuing your followers differently - total count is meaningless unless you're factoring in their @Klout or something similar. My 600 real people followers are worth far more than 60,000 random Twitter users that never actually read the things those marketing drone accounts are saying ... On Mon, Nov 30, 2009 at 3:19 PM, M. Edward (Ed) Borasky zzn...@gmail.comwrote: I'm hearing from many Twitter users that the frustration level caused by the Britney Bots is rising. I'm going to use some euphemisms to make this message safe for work, but the particular bots in question are certainly not work-safe. The _modus operandi_ of these bots is as follows: 1. Get a Twitter account. These are usually of the form small English word5 digit number. The profile picture is typically not safe for work. 2. Collect screen names somehow. They must at least be polling the public timeline. Frequent tweeters seem to get more of them. Perhaps they are doing searches as well, or mining the profiles of the screen names they've collected for more screen names. 3. Send an @ reply to each name collected. These come in bursts - I haven't done any research into the frequency at which they are sent but a number of tweets go out in a burst. The tweets themselves are not safe for work. The bots do *not* appear to be following anybody - they only show up if you do a mentions search. What's worse, though, is that people are retweeting these things! There is a movement on Twitter, using the hashtag #StopBritneyBots, to attempt to get Twitter to put some kind of filtering in place. I'm not sure what the status of that is in Twitter - perhaps some of the Twitter people on this list can chime in. Meanwhile, this particular bot has an easily-detected signature - you can collect the bot names via Twitter search! 1. Do a Twitter search for the following string (the double quotes are part of the string!): '(Click the link at top right of my profile)' Note that the returned tweets from this search will mostly be not safe for work! 2. Break each resulting tweet into space-separated tokens. 3. Scan the tokens from right to left. The first @name you encounter will be the destination victim. The second one you encounter will be the bot that sent it. At this point, you could build a bot to report the bots as spammers. Personally, I think anyone who retweets one of these ought to be considered a spammer as well. ;-) In any event, I've got some code using the Net::Twitter Perl library that collects the tweets, and I can supply a list of names to Twitter if they'd like. I'd prefer, of course, that Twitter deal with this at the inlets to the tweet stream. But I think there's a significant enough groundswell in the community that we will see bots arise using the algorithm I've described above. I've been asked to create one, but I'm holding off - there are some murky legalities involved and I have more interesting research in Twitter text mining I want to do. ;-) Twitter, what say you? Developer community, what say you? -- M. Edward (Ed) Borasky http://borasky-research.net/smart-at-znmeb I've always regarded nature as the clothing of God. ~Alan Hovhaness -- mailto:n...@layer3arts.com // GoogleTalk: nrauhau...@gmail.com IM: nealrauhauser