Add to ORKGThis paper describes the submission of the University of Washington's Center for Data Science to the PAN 2014 author profiling task. We examine the predictive quality in terms of age and gender of several sets of features extracted from various genres of online social media. Through comparison, we establish a feature set which maximizes accuracy of gender and age prediction across all genres examined. We report accuracies obtained by two approaches to the multi-label classification problem of predicting both age and gender; a model wherein the multi-label problem is reduced to a single-label problem using powerset transformation, and a chained classier approach wherein the output of a dedicated classier for gender is used as input for a cla...
This paper describes approaches for the Author Profiling Shared Task at PAN 2018. The goal was to cl...
[Abstract] Automatic user profiling from social networks has become a popular task due to its commer...
Demographic lexica have potential for widespread use in social science, economic, and business appli...
This paper describes the submission of the University of Washington's Center for Data Science to the...
This paper gives a brief description on the methods adopted for the task of author-profiling as part...
This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, de...
Abstract Would you target your audience differently, knowing the real age and gender of the text aut...
There is a growing interest in automatically predicting the gender and age of authors from texts. Ho...
The paper presents an interdisciplinary study in the field of automatic gender and age identificatio...
The growth of social networking platforms such as Facebook and Twitter has bridged communication cha...
There is a growing interest in automatically predicting the gender and age of authors from texts. Ho...
There is a growing interest in automatically predicting the gender and age of authors from texts. Ho...
The user profile information is important for many studies, but essential information, such as gende...
Online social networking services have come to dominate the dot com world: Countless online communit...
The paper presents an interdisciplinary study in the field of automatic gender and age identificatio...
This paper describes approaches for the Author Profiling Shared Task at PAN 2018. The goal was to cl...
[Abstract] Automatic user profiling from social networks has become a popular task due to its commer...
Demographic lexica have potential for widespread use in social science, economic, and business appli...
This paper describes the submission of the University of Washington's Center for Data Science to the...
This paper gives a brief description on the methods adopted for the task of author-profiling as part...
This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, de...
Abstract Would you target your audience differently, knowing the real age and gender of the text aut...
There is a growing interest in automatically predicting the gender and age of authors from texts. Ho...
The paper presents an interdisciplinary study in the field of automatic gender and age identificatio...
The growth of social networking platforms such as Facebook and Twitter has bridged communication cha...
There is a growing interest in automatically predicting the gender and age of authors from texts. Ho...
There is a growing interest in automatically predicting the gender and age of authors from texts. Ho...
The user profile information is important for many studies, but essential information, such as gende...
Online social networking services have come to dominate the dot com world: Countless online communit...
The paper presents an interdisciplinary study in the field of automatic gender and age identificatio...
This paper describes approaches for the Author Profiling Shared Task at PAN 2018. The goal was to cl...
[Abstract] Automatic user profiling from social networks has become a popular task due to its commer...
Demographic lexica have potential for widespread use in social science, economic, and business appli...