Abstract
The spread of messages on social media has a profound impact on many areas of life, including business and politics. Understanding the diffusion of information, emotions and opinions is therefore essential to limiting the impact of manipulation, false information and bots on social media. The burgeoning research field of social media analytics can help solve this problem. This thesis addresses methodological challenges in information diffusion research and examines the factors that shape the spread of information, emotions and opinions on social media. Its key contributions to research are an improved understanding of how to address the challenges associated with social media analytics and a proposed mechanism for the influence of individuals with malicious aims on public opinion formation.
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