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Social Media (SM) has become the easiest, cheapest and fastest channel for companies to identify the events that affect their customers. The geo-location capabilities of the SM interactions enable Early Warning Systems to alert not only when the quality of service decays, but also where and how many customers are impacted. In this paper we present a system and a set of supporting metrics that exploit the geo-localized SM stream, quantify the perceived impact of events, incidents, etc. on a particular area over time. Industrial service providers can add this perceptional perspective to their standard monitoring tools to enable a prompt and appropriate reaction, the decision-making in marketing activities and to unveil customer acquisition opportunities applying the system to the competitors' customers. [ABSTRACT FROM AUTHOR]

Social Media can be used as a thermometer to measure how society perceives different news and topics. With the advent of mobile devices, users can interact with Social Media platforms anytime/anywhere, increasing the proportion of geo-located Social Media interactions and opening new doors to localized insights. This article suggests a new method built upon the industry standard Recency, Frequency and Monetary model to quantify the impact of a topic on a defined geographical location during a given period of time. We model each component with a set of metrics analyzing how users in the location actively engage with the topic and how they are exposed to the interactions in their Social Media network related to the topic. Our method implements a full fledged information extraction system consuming geo-localized Social Media interactions and generating on a regular basis the impact quantification metrics. To validate our approach, we analyze its performance in two real-world cases using geo-located tweets. [ABSTRACT FROM AUTHOR]

Abstract: Social Media is more and more positioning as the channel to implement early warning systems for prompt reaction to events that might affect a company's core business. The enabling of geo-location for social media interactions unlocks new possibilities for decision making scenarios aiming at triage situation where the quality of service decays. In this work we provide a system and a set of soft metrics to quantify the impact created by the reaction of people directly affected by an incident in a particular area in order to facilitate the service providers’ appropriate reaction, the decision making in marketing activities and to unveil customer acquisition opportunities applying the system to the competitors’ customers. [Copyright &y& Elsevier]