Blog Posts, Digital 100 June 20, 2018 0

Social Unrest, Social Media and Our Digital Network


Another Saturday, another exciting session! As part of our ambitious goal to build up a network of 100 young experts with data, ICT and technology related skills, we hold monthly meet-ups. These meet-ups are designed for young people who want to use their knowledge for good. A specific data challenge is presented to these young experts, who are asked to find data science or data analysis solutions and offer their thoughts on the best way to move forward.

This week we discussed the exciting groundTruth Global case. GroundTruth is an early warning system for social and business disruption. One way they collect data about social unrest is through Twitter and Facebook data. The question our network dealt with was as follows: ‘How can we use social media language analysis to improve the predictive model for social unrest?’ First, we considered underlying considerations, such as which social media are being used and which people are using these mediums. We then moved to thinking about the specific model and what we would need for the model itself. For example, would we use a one word search, or a sequence of words? How many people should be present at a gathering for us to define it as a ‘protest’? Lastly, we created step-by-step instructions for creating such a model. 

In the future, we would like to expand on these steps by beginning to test actual predictive models and their accuracy. We’re thus planning to organise ourselves into groups with different skills and continue moving forward with this exciting project.

Our next meet-up will be on (lucky) Friday July 13th! Have data skills and want to be part of this experience? Click here to fill in the form and we’ll be in touch with you as soon as possible. If you’re a business or an NGO and could use our data experts for your project, get in contact with us through email or use the contact details below!


Lilly Wiggers

Junior Research and Communications Officer, PeaceTech Lab NL

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