You are here

Twitter and the Rescue of the Chilean Miners

Seattle.
The next panel at AoIR 2011 starts with the excellent Luca Rossi, whose focus is on the Twitter coverage of the Chilean mining accident and the subsequent rescue of the miners. Luca begins, though, by pointing to the underlying theory of media events – from the royal wedding (as a kind of 2.0 version, now with added social media, of the Charles & Diana a few decades ago wedding) to crisis and disaster events.

Twitter coverage of the mine rescue in Chile was coordinated through the #rescatemineros hashtag. The miners were trapped underground for some three months, following the 5 August 2010 mine collapse; the event transformed from a crisis event to a more organised media event as it gradually unfolded. How did Twitter cover this; how did messages propagate through the network; and how did Twitter interleave with the wider mediasphere?

Luca captured some 30,000 tweets containing the #rescatemineros (specific rescue discussion) and #mineros (general crisis discussion) hashtags between 12 and 14 October 2010. In the first place, he examined direct interaction between specific users (through @replies and/or mentions – here excluding manual retweets); the majority of these are brief one-on-one exchanges, but also a handful of longer, more complex interactions, taking place especially around more important users (Chilean government representatives, media actors, etc.).

Messages around these major accounts include general public expressions of thanks to the rescuers and politicians, as well as some more playful interactions directed at them; this are acts of direct communication performed in public. There are also geographically-based clusters, involving users from specific South American countries (even though they are mostly using Spanish as a common language).

Message propagation through Twitter can also be studied, by examining the network of retweets. Here, key actors remain the same – the major nodes receiving @replies are also the major, official nodes whose messages are widely retweeted. Apparently trusted sources are more frequently retweeted. Message propagation happens from several starting points at the same time, simultaneously.