A Comprehensive Overview of Consumer Conflicts on Social Media.

The use of social media platforms is increasingly prevalent in society, providing brands with a multitude of opportunities to interact with consumers. However, literature has shown this increased usage has negative impacts for users who have experienced depression, anxiety, and stress and brands who see increasing volumes of hate within their communities such as bullying, conflicts, complaints, and harmful content. Existing research focuses on extreme forms of conflict, largely ignoring the lesser forms which still pose a significant threat to consumer and brand welfare. This research aims to capture the full spectrum of online conflict, providing a comprehensive overview of the problem from an interdisciplinary marketing and computer science perspective. I propose a further investigation into online hate, utilising big data analysis to establish an understanding of triggers, consequences and brand responses to online hate. Initially, I will conduct a systematic literature review exploring the definitions and methodology used within the hate research domain. Secondly, I will conduct an investigation into state-of-the-art models and classification systems, producing an analysis on the prevalence of hate and its various forms on social media. Finally, I plan to establish the features of social media data which constitute triggers for online conflicts. Then, through a combination of user studies, sentiment analysis, and emotion detection I will examine the consequences of these conflicts. This project represents a unique opportunity to combine cutting edge marketing theories with big data analysis, this collaborative approach will offer a considerable contribution to academic literature.