Author profiling is the analysis of a given set of texts in an attempt to uncover various characteristics of the author based on stylistic- and content-based features, or to identify the author. Characteristics analysed commonly include age and gender, though more recent studies have looked at other characteristics, like personality traits and occupation.
Author profiling is one of the three major fields in automatic authorship identification (AAI), the other two being authorship attribution and authorship identification.
데이터셋
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
Although research on author profiling has quite progressed in abundant resources languages, it is still infancy for limited resources languages such as Bengali. This repository contains our Bangla Author Profiling Dataset (BN-AuthProf). The primary objective is to introduce and benchmark the performance of machine learning approaches on Age and Gender Classification tasks from the social media status of people. BN-AuthProf dataset consists of 300 anonymized authors and 30,131 manually curated Facebook posts in Bangla, tagged with age and gender information.