Emotions in social networks

In this dissertation, I explore emotional dynamics in a social network and how brands can leverage emotional state in a network to create engagement. Essay 1 focuses on emotional dynamics, specifically how long certain emotions last, and how emotions follow each other in short- and long-term time frames, using emotional dimensions (valence-arousal- dominance) as predictors, analyzing millions of tweets retrieved from Twitter and processed with NLP techniques. Understanding how long emotions last and which emotions follow each other can act as a social appraisal mechanism that allows policy makers, politicians and marketing professionals be better prepared for emotional fluctuations in a society. Essay 2 focuses on the role of consumers' emotional state in receiving consumer engagement for the brand-generated social media content. Second essay highlights the importance of context for receiving consumer engagement and offers insights into the congruency between the emotional characteristics of the brand-generated content and consumers' states.