A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries

A new area of research involves the use of Google data, which has been normalized and scaled to predict economic activity. This new source of data holds both many advantages as well as disadvantages, which are discussed through the use of daily and weekly data. Daily and weekly data are employed to show the effect of aggregation as it pertains to Google data, which can lead to contradictory findings. In this paper, Poisson regressions are used to explore the relationship between the online traffic to a specific website and the search volumes for certain keyword search queries, along with the rankings of that specific website for those queries. The purpose of this paper is to point out the benefits and the pitfalls of a potential new source of data that lacks transparency in regards to the original level data, which is due to the normalization and scaling procedures utilized by Google.Poisson Regression, Search Engine, Google Insights, Aggregation, Normalization Effects, Scaling Effects

A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries

A new area of research involves the use of Google data, which has been normalized and scaled to predict economic activity. This new source of data holds both many advantages as well as disadvantages, which are discussed through the use of daily and weekly data. Daily and weekly data are employed to show the effect of aggregation as it pertains to Google data, which can lead to contradictory findings. In this paper, Poisson regressions are used to explore the relationship between the online traffic to a specific website and the search volumes for certain keyword search queries, along with the rankings of that specific website for those queries. The purpose of this paper is to point out the benefits and the pitfalls of a potential new source of data that lacks transparency in regards to the original level data, which is due to the normalization and scaling procedure utilized by Google.Poisson Regression, Search Engine, Google Insights, Aggregation, Normalization Effects, Scaling Effects

Spin tunneling properties in mesoscopic magnets: effects of a magnetic field

The tunneling of a giant spin at excited levels is studied theoretically in mesoscopic magnets with a magnetic field at an arbitrary angle in the easy plane. Different structures of the tunneling barriers can be generated by the magnetocrystalline anisotropy, the magnitude and the orientation of the field. By calculating the nonvacuum instanton solution explicitly, we obtain the tunnel splittings and the tunneling rates for different angle ranges of the external magnetic field ($\theta_{H}=\pi/2$ and $\pi/2<\theta_{H}<\pi$). The temperature dependences of the decay rates are clearly shown for each case. It is found that the tunneling rate and the crossover temperature depend on the orientation of the external magnetic field. This feature can be tested with the use of existing experimental techniques.Comment: 27 pages, 4 figures, accepted by Euro. Phys. J.