Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1142/S0219622017400016 | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING |
Keywords | Field | DocType |
Early-warning systems, localized social media, social media sensor, social media insights, polarity | Customer acquisition,Warning system,Data mining,Social media,Quality of service,Communication channel,Service provider,Exploit,Mathematics,Competitor analysis | Journal |
Volume | Issue | ISSN |
17 | 1 | 0219-6220 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Bernabé-Moreno | 1 | 19 | 5.62 |
| Álvaro Tejeda-Lorente | 2 | 97 | 7.88 |
| Carlos Porcel | 3 | 450 | 24.12 |
| Enrique Herrera-Viedma | 4 | 13105 | 642.24 |