A (Probably) Incomplete Taxonomy of Peñabots (And Their Friends)

In this post I catalog the different ways local, state, and federal governments in Mexico have used social media bots in different ways to their advantage. This is the other side of the excellent efforts made by projects like Botivist to link activists with the use of bots. However, what may be useful to activists may also be useful to state actors. I think a list of this kind is necessary because it is important to be able to recognize the ways in which such state actors (even well-funded private actors) can subvert speech online. In this list I mention cases where large groups of people rather than software are used. Partly because it is hard to discern between the two methods, and mostly because the outcome is essentially the same. The methods for spreading or silencing information can be achieved through either means (manual or automated). I believe this to be especially true since governments usually have plenty of resources at their disposal. At the end I pose some questions yet to be answered.

  • Fake Support
    1. Spread campaign messages by tweeting the same message or similar messages in a coordinated effort
    2. Retweeting supporters or online content (news, posts, photos) that is favorable to the campaign or political agenda.
    3. Coordinating large number of people with real and fake accounts to tweet the same hashtag to get it trending (used in conjunction to bumping off hashtags)
    4. Padding Twitter follower count.
  • Drowning Out Oppositional Voices
    1. Flood hashtags with spam so that discourse is impossible. This can occur when many bots tweet a trending hashtag so often that the feed becomes difficult to read because of Twitter’s auto-refresh feature. Filling the hashtag with spam could also hinder discussion since finding meaningful conversation among in a feed can be difficult. Another consequence of filling a hashtag with spam could be the removal of a hashtag from the TT list.
    2. Knock hashtags off TT list by replacing it with other favorable hashtags.
    3. Spread misinformation?
    4. Trolling
  • Defamation and Intimidation
    1. Intimidation
    2. Defamation
      • Lydia Cacho Ribeiro, Sept 2013, from QR gov.

Subverting Speech vs. PR Campaign
If a presidential campaign hires a PR company which utilizes a large amount of volunteers or paid workers or software bots to tweet in a coordinated effort to propagate your message, is this free speech? Does this subvert other’s speech? If this army of bots floods a discussion forum, does this act as censorship? What about when an activist organization does the same thing? I think there needs to be a discussion about what’s considered ethical when employing the use of bots.

Detecting Bots
It is difficult to know when we are dealing with software bots, with a PR campaign made up of volunteers, or merely just regular citizens tweeting in support of the government. Several people have tried to analyze Twitter data to “prove” the presence of bots, but I’m still left with a lot of questions.  What if there really was a lot of non-political Twitterers who were excited about the long weekend (#EnDiaDePuente)? What if the Twitter algorithm worked against the activist hashtag? I’ve been to tech conferences where the hashtag gets spammed, what if we’re dealing with regular Twitter spam and not state-sponsored spam? Are there any dangers in misclassifying spam and bots? Are there any negative effects in constantly blaming every piece of spam on the Peñabots?

Trending Topic Algorithm
The claims that TT such as #YaMeCanse were bumped by bots are hard to prove (despite the fancy graph videos). Similar claims of censorship occurred during the Occupy Wall Street protests where many activists claimed Twitter was censoring them by not adding #occupywallstreet to the TT list. In response, several bloggers, journalists and Twitter themselves, explained that the TT algorithms look for “trendiness” and “burstiness”, and that while OWS might have had a large volume of Tweets, it did not display the spikes in volume the algorithm is constantly looking for. Although I don’t doubt the presence of bots (even State bots), I am not convinced that anything other than the regular algorithmic forces were at play in knocking #YaMeCanse off the TT list. Furthermore, more research and discussions need to be had around the importance of trending topics to activist causes. Are they crucial? Are they overvalued?

Analyzing Twitter Data
Twitter is VERY noisy. Even very specific words that seem to only talk about one specific event like “balacera” (shootout) are hard to analyze. Especially when the word becomes part of quotidian culture. For example, in Mexico people tend to tweet when there is a shootout in their city, usually to warn others to stay out of the area. In trying to analyze ‘balacera’ tweets, I’ve found that people also talk about past shootouts, potential shootouts, and even tell jokes about shootouts. So one needs to be careful when analyzing tweets. Some of the best insights on Twitter use I’ve seen have come from qualitative research methods like interviews.

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