In recent years, several studies have greatly increased our understanding of the genetic basis underlying human eye colour variation. A large percentage of the eye colour diversity present in humans can already be genetically explained, so much so that different DNA-based eye colour prediction models, such as IrisPlex, have been recently developed for forensic purposes. Though these models are ...

OBJECTIVE To explore how well physicians and patients predict sick-listing duration and the correspondence between their respective predictions. To study possible gender differences concerning prediction accuracy. DESIGN Prospective observational study. SETTING Two medium-sized primary care centres (PCC) in western Sweden. SUBJECTS GPs at the PCCs and attending patients sick-listed for > ...

Author profiling deals with the study of various profile dimensions of an author such as age and gender. This work describes our methodology proposed for the task of cross-genre author profiling at PAN 2016. We address gender and age prediction as a classification task and approach this problem by extracting stylistic and lexical features for training a logistic regression model. Furthermore, w...

This research extends the role incongruity analysis of employment-related gender bias by investigating the role of dispositional and situational antecedents, specifically political ideology and the salience of cues to the traditional female gender role. The prediction that conservatives would show an anti-female candidate bias and liberals would show a pro-female bias when the traditional femal...

The demographic attributes gender and age play an important role for social media applications. Previous studies on gender and age prediction mostly explore efficient features which are labor intensive. In this paper, we propose to use the multi-task convolutional neural network (MTCNN) model for predicting gender and age simultaneously on Chinese microblog. With MTCNN, we can effectively reduc...

This paper addresses the task of user gender classification in social media, with an application to Twitter. The approach automatically predicts gender by leveraging observable information such as the tweet behavior, linguistic content of the user’s Twitter feed and the celebrities followed by the user. This paper first evaluates linguistic content based features using LIWC dictionary and popul...

In this paper we present an approach for the task of author profiling. We propose a coherent grouping of features combined with appropriate preprocessing steps for each group. The groups we used were stylometric and structural, featuring among others, trigrams and counts of twitter specific characteristics. We address gender and age prediction as a classification task and personality prediction...