what it had to say.

By accessing information from satellites and weather monitoring systems of the world's most advanced environmental trackers on wildfires, temperature records, air quality and CO2 levels around the world, we managed to create a way of expression, an already seen social media channel, but in a way not used in earth's 4,543 billion years, with messages of its problematics, directed straight at the incumbent people and organizations responsible for take immediate action.

All the natural disasters that we witness are more than that, it´s planet earth trying to communicate with us a message in the form of hurricanes, glacial melt, highest or lowest temperatures ever, sandstorms, and all sorts of natural phenomena. And what is the message behind this? planet earth telling us to stop sending plastic to the oceans, to stop starting fires in the Amazon forest, in Australia, the Patagonia or California, to reduce the air pollution that deteriorates the ozone layer, so we can care for the air we all breathe. All of this is what planet Earth is trying to make us aware of with its language. Even worse, that information is sometimes kept in secret or manipulated.

For all of these reasons it was about time to get the message straight, so we can take action and take care of the earth, before it is too late.

We gave earth its own Twitter account @EarthIsSaying and synchronized it with satellites and environmental monitors around the world. Using Machine Learning, we converted data from floods, forest fires, air quality, temperature and CO2 levels, into tweets from the earth in real time. The alert determines not only the message, but also precise data on real time to illustrate the potential natural disasters and give it a context, but also tagged the relevant people that should take action. In that way earth itself without human intervention, made its health condition a trend among its inhabitants and leaders around the world. Reaching younger generations and not only creating a conversation on twitter but urging authorities and people to take action before it´s too late.

After identifying the sources of data on the different topics and configurating the correct parameters; the algorithm determines the frequency and/or triggers that generate alarms according to the sources. According to the alert, it determines the message to be sent, tagging the people or institutions that should take action on it and the appropriate hashtags to be combined according to the matrix of predetermined configuration values. Once the process is made, it automatically sends a message from its twitter account once the alert is detected by the tool.

Developing an automated system of generation of messages tweet type based on analysis and parameterization of answers of known sources related to earth monitoring, we not only impact the environmental audience, but also generate consciousness in the new generations that are so engaged in social networks to which Greenpeace wanted to reach in a new, different, and disruptive way.

After identifying the sources of data on the different topics and configurating the correct parameters; the algorithm determines the frequency and/or triggers that generate alarms according to the sources. According to the alert, it determines the message to be sent, tagging the people or institutions that should take action on it and the appropriate hashtags to be combined according to the matrix of predetermined configuration values. Once the process is made, it automatically sends a message from its twitter account once the alert is detected by the tool.

Developing an automated system of generation of messages tweet type based on analysis and parameterization of answers of known sources related to earth monitoring, we not only impact the environmental audience, but also generate consciousness in the new generations that are so engaged in social networks to which Greenpeace wanted to reach in a new, different, and disruptive way.

Results on Earth’s day:

• Verified by Twitter – (Non human intervention account).

• + 171,2 MM impressions

• Trending topic in an hour on launch date

• 570 early alerts generated on potential natural disasters

• 43 countries interacted:

Colombia, España, Chile, Argentina, Bangladesh, Italy, Afghanistan, Japan, Indonesia, Nepal, Vietnam, China, Bulgaria, South Korea, Peru, Malasia, UAE, Iceland, India, Mexico, Russia, USA, Kuwait, Israel, Egypt, Singapur, England, South Africa, Canada, Hungary, France, Iran, Uganda, Pakistan, Bahrein, Romania, Eslovaquia, Phillipines, Mongolia, Bosnia-Herzegovina, Macedonia, Ghana.

• 12 languages tweeted