Social media platforms have throughout time been praised for their potential to cultivate fruitful debates. However, these platforms have also been criticized for cultivating polarization and fragmentation. This thesis enters this debate and investigates how the social media platform Twitter is being used to discuss global challenges to arrive at a better understanding of the potentials and challenges.
Specifically, this thesis focus on the issue of climate change, a global challenge that in recent years has received increasing attention within social media debates. The thesis is based on an analysis of 4,905,390 referring to the issue of climate change. The ~4.9 million tweets are analyzed using a range of big data analysis techniques, ranging from dictionary methods to more sophisticated machine learning models, both supervised and unsupervised, as well as network analysis. Using these methods, this thesis finds that the Twitter debate is inclusive and defined by equality, as not only does everyone have a voice, anyone can have an impact on the debate, even users with few followers or voices that are perceived as disruptive, for example, climate change skepticism. Furthermore, the results emphasize the importance of language within the online context, more specifically the form of shared message, as the use of moralized and formal language is found to be important in the tweets that are shared by others. However, while the Twitter debate is found to be inclusive and equal, it is also found to be a debate without an ongoing reciprocal exchange of opinions.