Case Study: Who directs the conversation of the Catalan Independence?

barcelona smart city
Events in Catalonia, including the 1-Oct referendum, divided opinions. We used machine learning to compare Twitter responses in Barcelona and Madrid –and showed key differences and what unites both cities.

Politics worldwide in the year 2017 showed that we are more divided than ever. Brexit negotiations continued to split the U.K. population. The gulf between Trump supporters and Democrats in America is growing. And in Spain, Catalonia’s bid for independence provoked diverse opinions.

Expert sociologists and psychologists say it is crucial that we “learn to understand people on the other side of the divide” –and crucial that policy-makers use empathy to seek access “to a range of diverse lived experiences”.

Healing divided communities means listening and understanding. #civictech platforms like Citibeats let leaders hear what both sides are saying.

We put our machine-learning algorithm to the test, analyzing citizens’ concerns around Catalan independence throughout late September and October. We traced responses from the lead-up to the 1 October (1-Oct) referendum throughout the month that followed, including key events like:
We used data from social networks in Barcelona and Madrid –cities with polarized opinions on the issue. The Citibeats technology generated a comparative map of who was speaking, what they said and when they said it, filtered through various other analytics. We observed key differences and similarities –important insights that can support cities and citizens in better understanding the situation.
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So, who drove the conversation around Catalan independence?

Barcelona spoke first: in the leadup to 1-Oct and immediately afterwards, Barcelona-based Twitter users directed the conversation. But soon Madrid’s voice grew in response, and towards the end of October, Madrid’s social networks were discussing the topic even more than Barcelona.
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One key difference was the major actors. Barcelona’s fast start was driven by its politicians, who were the most active participants in the early Twitter conversation. But in Madrid, ordinary citizens were the ones who began discussing the situation. Politicians in Madrid responded several days after Madrid citizens’ voices  reached their peak.
ai data analytics

How do citizens feel about the situation?

Barcelona and Madrid showed polarized views: major political events spiked opposing sentiments. For example, the suspension of Catalan autonomy produced a negative Twitter reaction in Barcelona, but many different feelings in Madrid.
But one aspect united citizens across both cities. The most representative keywords overall had to do with information manipulation and the media.
The topic citizens on both sides worried most about was misrepresentation of information.
2017 taught us about fake news, filter bubbles, and information bias worldwide. The Catalan situation shows how strongly Madrid and Barcelona citizens feel about accessing unbiased, trustworthy information. It is a message from citizens to their city leaders: we want to hear the full story. To overcome our divides, we will first need to build this trust.
#civictech tools like Citibeats let leaders listen to their communities so that they can respond and create trust in their cities. Smart leaders listen better.

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