Gender and Genre Linguistic profiling: a case study on female and male journalistic and diary prose
Authors: Eleonora Cocciu, Dominique Brunato, Giulia Venturi, Felice Dell'Orletta (Università di Pisa, CNR-ILC, 2018)
Topic: Textual Genres & Literature Linguistics

Abstract
This paper intends to investigate English. This paper intends to investigate the linguistic proﬁle of maleand femaleauthored texts belonging to two very different textual genres: newspaper articles and diary prose. By using a wide set of linguistic features automatically extracted from text and spanning across different levels of linguistic description, from lexicon to syntax, our analysis highlights the peculiarities of the two examined genres and how the genre dimension is inﬂuenced by variation depending on author’s gender (and vice versa).

Introduction
Authorship proﬁling is the task of identifying the author of a given text by deﬁning an appropriate characterization of documents that captures the writing style of authors. It is a well-studied area with applications in various ﬁelds, such as intelligence and security, forensics, marketing etc. Over the last years, progress in different disciplines such as Artiﬁcial Intelligence, Linguistics and Natural Language Processing (NLP) stimulates new research directions in this ﬁeld leading to the development of ‘computational sociolinguistics’, a multidisciplinary ﬁeld whose goal is to study the relationship between language and social groups using computational methods (Nguyen et al., 2016). With this respect, a particular attention has been paid to the inﬂuence of gender as a demographic variable on language use. This is a topic that has attracted linguistic research for decades (see e.g. (Lakoff, 1973)) and has received a renewed interest in recent years in the NLP community. The investigation of possible differences between men’s and women’s linguistic styles has been carried out by using multivariate analyses taking into account gender-preferential stylistic features (Herring and Paolillo, 2006) and machine learning techniques inferring language models that differ at the level of linguistic patterns learned (e.g. based on n-grams of characters, on lexicon, etc.) (Argamon et al., 2003; Sarawgi et al., 2016). These studies have also moved the interest towards the analysis of possible effects driven by textual genres and topics on gender-speciﬁc language preferences. With this respect, in the context of the annual PAN evaluation campaign organized since 20131, a crossgenre gender identiﬁcation shared task was newly introduced (Rangel et al., 2016) in 2016, where participants were asked to predict author’s gender with respect to a textual typology different from the one used in training. This scenario turned out to be much more challenging for state-of-the art systems, suggesting that females and males can possibly use a different writing style according to genre. While the cross-genre gender prediction task has received attention for many languages, e.g. English, Portuguese, Arabic, the Italian language will be addressed for the ﬁrst time by the GxG (Gender X-Genre) shared task in the context of the 2018 EVALITA campaign2. In line with this interest in the international community, this paper presents a study on gender variation in writing styles with the aim of investigating if there are gender-speciﬁc characteristics that are constant across different genres. We deﬁne a methodology to carry out an in-depth linguistic analysis to detect differences and similarities in female- and male-authored writings belonging to two different genres. Similarly to the early work by Argamon et al. (2003) for English, our focus is on the linguistic phenomena that contribute to model men’s and women’s writings in a cross-genre perspective. The main novelty of this work is that we rely on a very wide set of linguistic features automatically extracted from text and capturing lexical, morpho-syntactic and syntactic phenomena. We choose not to focus our analysis on computer-mediated communication texts, which are more typically used in this context, but on two traditional textual genres, i.e. newspaper articles and diary prose.

Conclusion
We have presented a cross-genre linguistic proﬁling investigation comparing male and female texts in Italian. We examined a large set of linguistic features, intercepting lexical and syntactic phenomena, which were extracted from two very different textual genres: newspaper articles and diary prose. As expected, the comparative analysis highlighted a number of differences between the two genres, due to the more subjective language characterizing diaries with respect to journalistic prose. Interestingly, we also highlighted that some linguistic features characterize gender dimension and, even more interestingly, we found statistically signiﬁcant variations also in an objective prose such as newspaper articles.