The Impact of Expert Knowledge on User Behavior in Recommender Systems

Using experts in recommender systems can improve the accuracy of recommendations as well as other quality aspects of recommendations. Most studies have tested the impact of expert knowledge in offline tests. However, it is still unclear how user behavior changes when experts are used for recommendation in an online scenario. We therefore deploy a live recommender system based on rules built by employed experts on the video-on-demand platform of a large television network. We find that expert-built rules lead to a similar amount of clip views and platform visits as a standard recommender. However, experts have an influence on the consumed content, focusing users on a few popular categories

Gender Stereotyping’s Influence on the Perceived Competence of Siri and Co.

Some users express frustration with regard to virtual assistants due to their lack of perceived competence. To address this negative perception, we believe that technology companies should be aware of gender stereotypes. More specifically, it has been shown that males are attributed with rational competence more often than females. Drawing from the CASA paradigm, which states that people regularly assign human traits to computers, we expect that this stereotype might also be present for virtual assistants, i.e., male-voice virtual assistants are perceived as being more competent than female-voice virtual assistants. We test this hypothesis by conducting a controlled experiment which simulates a realistic interaction with differently voiced virtual assistants. The results indicate that gender stereotypes indeed play a role in the perception of the interaction. Male-voiced assistants are perceived more competent than their female-voiced counterpart which has practical implications in the design and development of devices that utilize these assistants

The Impact of Gender Stereotyping on the Perceived Likability of Virtual Assistants

Research on gender stereotyping suggests that females are perceived as being more likable than males are. Based on the CASA paradigm, which describes the human tendency to assign human traits to computers, we expect that this stereotype might also be present for virtual assistants, i.e., that female-voice virtual assistants are perceived as being more likable than male-voice virtual assistants. We conduct a controlled experiment that simulates a lifelike interaction with differently voiced virtual assistants to test this hypothesis. The results emphasize that gender stereotypes indeed influence users’ perception of virtual assistants, where female-voiced assistants are perceived as being more likable than male-voiced assistants. This has practical implications for the development and design of devices that utilize these virtual assistants

Association of COVID-19 mortality with COVID-19 vaccination rates in Rhineland-Palatinate (Germany) from calendar week 1 to 20 in the year 2021: a registry-based analysis

Vaccination is among the measures implemented by authorities to control the spread of the COVID-19 pandemic. However, real-world evidence of population-level effects of vaccination campaigns against COVID-19 are required to confirm that positive results from clinical trials translate into positive public health outcomes. Since the age group 80 + years is most at risk for severe COVID-19 disease progression, this group was prioritized during vaccine rollout in Germany. Based on comprehensive vaccination data from the German federal state of Rhineland-Palatinate for calendar week 1-20 in the year 2021, we calculated sex- and age-specific vaccination coverage. Furthermore, we calculated the proportion of weekly COVID-19 fatalities and reported SARS-CoV-2 infections formed by each age group. Vaccination coverage in the age group 80 + years increased to a level of 80% (men) and 75% (women). Increasing vaccination coverage coincided with a reduction in the age group's proportion of COVID-19 fatalities. In multivariable logistic regression, vaccination coverage was associated both with a reduction in an age-group's proportion of COVID-19 fatalities [odds ratio (OR) per 5 percentage points = 0.89, 95% confidence interval (CI) = 0.82-0.96, p = 0.0013] and of reported SARS-CoV-2 infections (OR per 5 percentage points = 0.82, 95% CI 0.76-0.88, p < 0.0001). The results are consistent with a protective effect afforded by the vaccination campaign against severe COVID-19 disease in the oldest age group