Automatic extraction of information about authors of texts (gender, age, psychological type, etc.) based on the analysis of linguistic parameters has gained a particular significance as there are more online texts whose authors either avoid providing any personal data or make it intentionally deceptive despite of it being of practical importance in marketing, forensics, sociology. These studies...

Gender Identification is a task where we have to identify the gender of the author for written texts. An hybrid approach has been designed by combining deep neural network and a rule-based classifier for russian texts. LSTM and BiLSTM have been used as a part of Neural Network due to their capability to learn long-term dependencies.

Gender differences in language use have long been of interest in linguistics. The task of automatic gender attribution has been considered in computational linguistics as well. Most research of this type is done using (usually English) texts with authorship metadata. In this paper, we propose a new method of male/female corpus creation based on gender-specific first-person expressions. The meth...

the feminist literary criticism is a kind of criticism which deals with the masculine works and unveils the gynophobia of literary system. this school of thought believes that the masculine norms rule over literature and feminine experiences, desires, interests and emotions have turned pale and have been shown unimportant under these norms. so, the feminist literary criticism intends to reveal ...

using cross-provinces and panel regressions, this paper investigates the interrelationship between gender equality and fertility in iran for the period 2007-2012. the article attempts to explain the low fertility rate in iran by distinguishing between two types of gender equity, i.e. gender equity in individual-oriented institutions and gender equity in family-oriented institutions. for this pu...

The widespread use of deception in online sources has motivated the need for methods to automatically profile and identify deceivers. This work explores deception, gender and age detection in short texts using a machine learning approach. First, we collect a new open domain deception dataset also containing demographic data such as gender and age. Second, we extract feature sets including n-gra...

The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author’s gender has a powerful, clear signal in originals texts, but this signal is obfuscated in ...