Stokes flow near the contact line of an evaporating drop

The evaporation of sessile drops in quiescent air is usually governed by vapour diffusion. For contact angles below $90^\circ$, the evaporative flux from the droplet tends to diverge in the vicinity of the contact line. Therefore, the description of the flow inside an evaporating drop has remained a challenge. Here, we focus on the asymptotic behaviour near the pinned contact line, by analytically solving the Stokes equations in a wedge geometry of arbitrary contact angle. The flow field is described by similarity solutions, with exponents that match the singular boundary condition due to evaporation. We demonstrate that there are three contributions to the flow in a wedge: the evaporative flux, the downward motion of the liquid-air interface and the eigenmode solution which fulfils the homogeneous boundary conditions. Below a critical contact angle of $133.4^\circ$, the evaporative flux solution will dominate, while above this angle the eigenmode solution dominates. We demonstrate that for small contact angles, the velocity field is very accurately described by the lubrication approximation. For larger contact angles, the flow separates into regions where the flow is reversing towards the drop centre.Comment: Journal of Fluid Mechanics 709 (2012

External validity of sentiment mining reports: Can current methods identify demographic biases, event biases, and manipulation of reviews?

Many publications in sentiment mining provide new techniques for improved accuracy in extracting features and corresponding sentiments in texts. For the external validity of these sentiment reports, i.e., the applicability of the results to target audiences, it is important to well analyze data of the context of user-generated content and their sample of authors. The literature lacks an analysis of external validity of sentiment mining reports and the sentiment mining field lacks an operationalization of external validity dimensions toward practically useful techniques. From a kernel theory, we identify multiple threats to sentiment mining external validity and study three of them empirically 1) a mismatch in demographics of the reviewers sample, 2) bias due to reviewers' incidental experiences, and 3) manipulation of reviews. The value of external validity threat identifying techniques is next examined in cases from Goodread.com. We conclude that demographic biases can be well detected by current techniques, although we have doubts regarding stylometric techniques for this purpose. We demonstrate the usefulness of event and manipulation bias detection techniques in our cases, but this result needs further replications in more complex and more competitive contexts. Finally, for increasing the decisional usefulness of sentiment mining reports, they should be accompanied by external validity reports and software and service providers in this field should incorporate these in their offering

External validity of sentiment mining reports: Can current methods identify demographic biases, event biases, and manipulation of reviews?

Many publications in sentiment mining provide new techniques for improved accuracy in extracting features and corresponding sentiments in texts. For the external validity of these sentiment reports, i.e., the applicability of the results to target audiences, it is important to well analyze data of the context of user-generated content and their sample of authors. The literature lacks an analysis of external validity of sentiment mining reports and the sentiment mining field lacks an operationalization of external validity dimensions toward practically useful techniques. From a kernel theory, we identify multiple threats to sentiment mining external validity and study three of them empirically 1) a mismatch in demographics of the reviewers sample, 2) bias due to reviewers' incidental experiences, and 3) manipulation of reviews. The value of external validity threat identifying techniques is next examined in cases from Goodread.com. We conclude that demographic biases can be well detected by current techniques, although we have doubts regarding stylometric techniques for this purpose. We demonstrate the usefulness of event and manipulation bias detection techniques in our cases, but this result needs further replications in more complex and more competitive contexts. Finally, for increasing the decisional usefulness of sentiment mining reports, they should be accompanied by external validity reports and software and service providers in this field should incorporate these in their offering

Altering the course of schizophrenia: progress and perspectives

International audienc