Name
Title | ||
|---|---|---|
Marketing analysis of wineries using social collective behavior from users ’ temporal activity on Twitter |
Abstract | ||
|---|---|---|
•This work proposes a new methodology to extract the social collective behavior of Twitter users concerning a group of brands based on the users' temporal activity•Time series of mentions made by individual users to each company's Twitter account are aggregated to obtain collective activity data for the companies•Classical unsupervised machine learning techniques, such as temporal clustering and hidden Markov models, are used to extract collective temporal behavior patterns and models of the dynamics of customers over time•The methodology is validated in a case study from the wine market using data gathered from four regions of different countries around the world with important wineries (Italy: Veneto, Portugal: Porto and Douro Valley, Spain: La Rioja, and United States: Napa Valley)•The findings presented show that the proposed methodology provides winery companies with new collective knowledge that can be very valuable |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ipm.2020.102220 | Information Processing & Management |
Keywords | DocType | Volume |
Social networks,Marketing analysis,Temporal Twitter Activity,Social collective behavior,Temporal clustering,Hidden Markov models,Wineries | Journal | 57 |
Issue | ISSN | Citations |
5 | 0306-4573 | 1 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gema Bello Orgaz | 1 | 116 | 10.36 |
| Rus M. Mesas | 2 | 1 | 0.36 |
| C. Zarco | 3 | 39 | 1.89 |
| Victor Rodriguez | 4 | 1 | 0.36 |
| Oscar Cordon | 5 | 75 | 9.21 |
| David Camacho | 6 | 331 | 43.45 |