Related papers: Quantifying Institutional Gender Inequality in Con…
Although the gender gap in academia has narrowed, females are underrepresented within some fields in the USA. Prior research suggests that the imbalances between science, technology, engineering and mathematics fields may be partly due to…
Interactions between bids to show ads online can lead to an advertiser's ad being shown to more men than women even when the advertiser does not target towards men. We design bidding strategies that advertisers can use to avoid such…
The participation of women in academia has increased in the last few decades across many fields (e.g., Computer Science, History, Medicine). However, this increase in the participation of women has not been the same at all career stages.…
Gender imbalance persists across science, technology, engineering, and mathematics (STEM) fields, including computer science, where it appears in researcher demographics, productivity, recognition, hiring, and career progression. Given…
In the fields of Experimental and Computational Aesthetics, numerous image datasets have been created over the last two decades. In the present work, we provide a comparative overview of twelve image datasets that include aesthetic ratings…
The attrition of women in academic careers is a major concern, particularly in Science, Technology, Engineering, and Mathematics subjects. One factor that can contribute to the attrition is the lack of visible role models for women in…
Discovering the creative potentials of a random signal to various artistic expressions in aesthetic and conceptual richness is a ground for the recent success of generative machine learning as a way of art creation. To understand the new…
In this article we make a case for a systematic application of complex network science to study art market history and more general collection dynamics. We reveal social, temporal, spatial, and conceptual network dimensions, i.e. network…
Automatic Gender Recognition (AGR) systems are an increasingly widespread application in the Machine Learning (ML) landscape. While these systems are typically understood as detecting gender, they often classify datapoints based on…
In computer vision, visual arts are often studied from a purely aesthetics perspective, mostly by analysing the visual appearance of an artistic reproduction to infer its style, its author, or its representative features. In this work,…
Women have always been underrepresented in movies and not until recently has the representation of women in movies improved. To investigate the improvement of female representation and its relationship with a movie's success, we propose a…
We study how deep learning can improve valuation in the art market by incorporating the visual content of artworks into predictive models. Using a large repeated-sales dataset from major auction houses, we benchmark classical hedonic…
This paper makes the first attempt to introduce the tools from computer graphics into the art pricing research. We argue that the creation of a painting calls for a combination of conceptual effort and painting effort from the artist.…
Women's access to academic careers has been historically limited by discrimination and cultural constraints. Comprehensive information about gender inequality within disciplines is needed to understand the problem and target remedial…
Online science dissemination has quickly become crucial in promoting scholars' work. Recent literature has demonstrated a lack of visibility for women's research, where women's articles receive fewer academic citations than men's. The…
Contemporary real-world online ad auctions differ from canonical models [Edelman et al., 2007; Varian, 2009] in at least four ways: (1) values and click-through rates can depend upon users' search queries, but advertisers can only partially…
Numerous studies in the literature highlight that women are underrepresented in the scientific domain which further leads to the underrepresentation of women in prestigious publications, authorship positions, and collaboration. However, the…
While research on applications and evaluations of explanation methods continues to expand, fairness of the explanation methods concerning disparities in their performance across subgroups remains an often overlooked aspect. In this paper,…
Supporting equitable instruction is an important issue for teachers attending diverse STEM classrooms. Visual learning analytics along with effective student survey measures can support providing on time feedback to teachers in making…
Gender inequity is one of the biggest challenges facing the STEM workforce. While there are many studies that look into gender disparities within STEM and academia, the majority of these have been designed and executed by those unfamiliar…