Name
Abstract | ||
|---|---|---|
The socioeconomic status of a population or an individual provides an understanding of its access to housing, education, health or basic services like water and electricity. In itself, it is also an indirect indicator of the purchasing power and as such a key element when personalizing the interaction with a customer, especially for marketing campaigns or offers of new products. In this paper we study if the information derived from the aggregated use of cell phone records can be used to identify the socioeconomic levels of a population. We present predictive models constructed with SVMs and Random Forests that use the aggregated behavioral variables of the communication antennas to predict socioeconomic levels. Our results show correct prediction rates of over 80% for an urban population of around 500,000 citizens. |
Year | Venue | Keywords |
|---|---|---|
2011 | UMAP | correct prediction rate,aggregated behavioral variable,socioeconomic status,urban population,random forests,cell phone record,basic service,communication antenna,socioeconomic level,aggregated use,design pattern,framework |
Field | DocType | Volume |
Population,Data mining,Feature selection,Electricity,Computer science,Support vector machine,Phone,Random forest,Environmental economics,Socioeconomic status,Purchasing power | Conference | 6787 |
ISSN | Citations | PageRank |
0302-9743 | 27 | 2.21 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Victor Soto | 1 | 103 | 8.86 |
| Vanessa Frias-Martinez | 2 | 213 | 17.79 |
| Jesus Virseda | 3 | 59 | 5.73 |
| Enrique Frias-Martinez | 4 | 238 | 17.11 |