Last week I did an article about people-imitating bots on Twitter and why they should concern you. I tried to make it clear that Twitter bots are software programs, and therefore can run the gamut from simple and uncomplicated to complex and dangerous.
But I’m afraid I left the impression that Twitter bots are without exception bad. And that’s not the case; not only are there non-dangerous bots, but there are Twitter bots made for benevolent purposes. They’re doing a lot of good for transparency and communication on Twitter. Let me give you an overview with some pointers to more information .
Wikipedia Monitoring Bots
If you’ve been following Twitter for a while you might be familiar with @CongressEdits, which monitors Wikipedia for articles edited by IP ranges associated with the United State Congress. When it finds one, it sends out a tweet with a little detail and a link to the edit. Another one, @CongressEditors, monitors the Wikipedia articles of members of Congress and sends out a tweet when they are edited. (Looking at the edits for some of these, I can understand why many of these pages are locked.)
And these are just two of them. There are so many Wikipedia-monitoring bots that Randall M. Livingstone, in an article on BotWatch, called them Wiki Watchers. That article includes many examples of Wiki Watchers for governments around the world. (At least one Wikipedia monitor for local government has been set up – WRAL in Raleigh, North Carolina created @NCGAEdits, though it’s not clear if that account is still active.)
There’s another wiki watcher that works a little differently. @WikiLiveMon attempts to identify potential breaking news by tweeting Wikipedia articles which are getting rapid numbers of changes by multiple editors. You can read about the thinking behind this Twitter bot in a paper at Cornell: MJ no more: Using Concurrent Wikipedia Edit Spikes with Social Network Plausibility Checks for Breaking News Detection. From that paper’s abstract: “Wikipedia articles in different languages are highly interlinked. For example, the English article en:2013_Russian_meteor_event on the topic of the February 15 meteoroid that exploded over the region of Chelyabinsk Oblast, Russia, is interlinked with the Russian article on the same topic. As we monitor multiple language versions of Wikipedia in parallel, we can exploit this fact to detect concurrent edit spikes of Wikipedia articles covering the same topics, both in only one, and in different languages. We treat such concurrent edit spikes as signals for potential breaking news events, whose plausibility we then check with full-text cross-language searches on multiple social networks.” Looking over these, I was struck at how many of the entries were sports-related, though the tool did pick up “covfefe” and the firing of Kathy Griffin.
In addition to monitoring Wikipedia, Twitter bots also help make government more transparent by surfacing Federal data and breaking events. There was once a Twitter bot that monitored changes to United States Supreme Court decisions and published PDFs of the “before” and “after” of possible changes. (You didn’t know SCOTUS revised opinions after publishing them? Yup, it sure does.) @SCOTUS_Servo was able to retire after SCOTUS started making its revisions more public in 2015, but there are still bots out there working to make your government more transparent.
Transparency & Government Bots
It seems simple, but also useful: @earthquakeBot tweets whenever USGS detects an earthquake of magnitude 5.0 or greater. If you experience what you think might be an earthquake (I live in North Carolina but I went through this in August 2011) It’s useful to have a Twitter account you can instantly refer to – or even follow, if you live in a more earthquake-prone region like California. (Actually, if you’re in California, you might want to check out California-specific Twitter accounts from the maker of Earthquake Bot.)
Wondering where all the money went? @TreasuryIO sends out regular tweets of information from the US Treasury.
The tweets are interesting bits of data but look a bit random; for more in-depth information on government spending you can visit http://treasury.io/ and query the data yourself (if you’re looking for an informative way to brush up on your SQL queries, here ya go.)
Most of the examples of government transparency bots I found were oriented toward federal government; I didn’t find many examples of state or municipal transparency bots. One I did find was @FiscalPhilly, which is described in its Twitter bio as “A civic application that regularly tweets commodities contract info from the City of Philadelphia.” However it has not tweeted since February 2016 and may be defunct.
I did find a transparency bot that manages to cover the entire world. Check out this article from The Verge: This Twitter bot is tracking dictators’ flights in and out of Geneva . @GVA_Watcher was designed to track planes, owned by authoritarian governments, flying into and out of Geneva, Switzerland. You can get more information on the methodology at DictatorAlert.org.
Looking to the Future
A lot of the resources I’ve linked to here have projects on GitHub, which makes me hopeful that there’s more development to come in the field of helpful, transparency-promoting Twitter bots. I was excited to see another kind of bot while I was researching this article – a bot that’s designed to automatically combat the spread of misinformation: “we identified an article published by Fox news that was spreading false facts about the World Economic Forum. We drafted a lengthy, accurate reply and published it on our own platform. We then programmed the bot to identify significant users on Twitter – those who are verified users, or who have over 2,000 followers — and reply to those users with an @mention, attaching the accurate story.”
I’m not sure that such a bot would change the mind of someone who was distributing misinformation, but to me that’s not the point. The point is that some of these misinformed tweets will have a correction attached.
Like any software program, Twitter bots can be good and bad, malevolent and benign. While it’s important to understand the implications of fake Twitter personas, it’s equally vital to realize that Twitter bots can do good, can promote transparency – and that there are some very useful ones out there.