Abstract
Social Media specifically Micro-blogging sites have become very rich data repositories. However the generated data is dynamic by nature, tied to temporal conditions and the subjectivity of its users. Everyday life experiences, discussions or events have a direct impact on the behaviors reflected in social networks. It is therefore of great importance to asses the impact these interactions are having over a social group. An alternative to answer this is determining how influential a topic is according to the behavior presented on a social network over time. It is then necessary to find and develop methods that can contribute towards this task. Having identified a topic in social media we can first classify it as time specific or long term, then posts relevant to the topic are collected and each one is assigned an emotion label. We then propose an Influence Value score which will be given to each topic based on its lifespan, emotion transition and reach. This lays ground to quantify how influential a topic is over a social group, specifically from events detected on twitter.