English. This paper intends to investigate the linguistic profile of male- and 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).
Italiano. Questo lavoro nasce con lo scopo di definire il profilo linguistico di testi scritti da uomini e da donne appartenenti a due generi testuali molto diversi: la prosa giornalistica e le pagine di diario. Attraverso lo studio di una ampia gamma di caratteristiche linguistiche estratte automaticamente dai testi e riguardanti diversi livelli di descrizione linguistica, che vanno dall’analisi lessicale del testo a quella sintattica, questo lavoro mette in luce le peculiarita` dei due generi testuali presi in esame e come la dimensione del dominio dei testi venga influenzata dalla dimensione del genere uomo/donna (e viceversa).
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
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. 2
The comparative investigation was carried out on two collection of texts, equally divided by gender, and selected to be representative of two different genres: journalistic prose and diary pages.
Women Men TOTAL
Tokens 45,155 35,493 80,648
Diaries
Document 100 100 200
Newspapers Tokens Document 62,469 100 66,860 100 129,329 200
For the journalistic genre we collected 200 documents through the advanced search engine available on the website of La Repubblica.
For the second textual genre, we collected 200 texts from the website of the Fondazione Archivio Diaristico Nazionale (National Diaristic Archive Foundation). In 1984, the Foundation (which is located in Pieve Santo Stefano in the province of Arezzo (Tuscany)) founded a first public archive containing writings of ordinary people, which was changed into the National Diaristic Archive Foundation in 1991. Since 2009 the documentary heritage of the archive has been included in the Code of Cultural Heritage of the State.
All selected texts were automatically tagged
by the part-of-speech tagger described in
Our approach relies on multi-level linguistic
features, which were extracted from the corpus
morpho-syntactically tagged and
dependencyparsed. They range across different levels of
linguistic description and they qualify lexical
and grammatical characteristics of a text. These
features are typically used in studies focusing on
the “form” of a text, e.g. on issues of genre, style,
authorship or readability (see e.g.
Raw Text Features: Token Length and Sentence Length (features 1 and 2 in Table 2): calculated as the average number of characters per tokens and of tokens per sentences.
Number of sentences (feature 3): calculated as the number of sentences of a document.
Lexical Features: Basic Italian Vocabulary rate
features, all calculated both in terms of lemmata
(L) and token (f ), referring to a) the internal
composition of the vocabulary of the text; we took as
a reference resource the Basic I
Type/Token Ratio: this feature refers to the ratio between the number of lexical types and the number of tokens. Due to its sensitivity to sample size, this feature is computed for text samples of equivalent length, i.e. the first 100 and 200 tokens (feature 8).
probability of Part-Of-Speech unigrams: this feature refers to the distribution of unigram
Lexical density: this feature refers to the ratio of content words (verbs, nouns, adjectives and adverbs) to the total number of lexical tokens in a text.
Verbal morphology: this feature refers to the distribution of verbs (both main and auxiliary) according to their grammatical person, tense and mood (feature 10).
Syntactic Features Unconditional probability of dependency types: this feature refers to the distribution of dependency relations (feature 11). Subordination features: these features (feature 12) include a) the distribution of subordinate vs main clauses and their average length, b) their relative ordering with respect to the main clause, c) the average depth of ‘chains’ of embedded subordinate clauses and d) the probability distribution of embedded subordinate clauses ‘chains’ by depth. Parse tree depth features: this set of features captures different aspects of the parse tree depth and includes the following measures: a) the depth of the whole parse tree, calculated in terms of the longest path from the root of the dependency tree to some leaf (feature 13); b) the average depth of embedded complement ‘chains’ governed by a nominal head and including either prepositional complements or nominal and adjectival modifiers and their distribution of embedded complement ‘chains’ by depth (feature 14).
Verbal predicates features: this set of features ranges from the number of verbal roots with respect to number of all sentence roots occurring in a text to their arity. The arity of verbal predicates is calculated as the number of instantiated dependency links sharing the same verbal head. Length of dependency links: the length is measured in terms of the words occurring between the syntactic head and the dependent (feature 15). 4
For each considered features we calculated the average value and their standard deviation. To investigate which features characterize male vs. female writings, and the possible influence of genre, we assessed the statistical significance of their variation comparing i) male and female writings, independently from the textual genre and ii) diaries and newspaper articles written by women and men. Table 2 reports features that resulted to vary significantly for at least one of the comparisons we considered. In the second and third columns, headed with Gender, it is marked the variation with respect to the textual genre, independently from gender’s author, the forth and fifth columns, headed with Genre, show the statistical significance of variations with respect to gender.
As it can be seen, the number of features that significantly vary is higher in diaries than in newspaper articles (i.e. 23 vs 11); this may suggest that newspapers are characterized by a quite codified writing style with few variations between female and male authors. When we focus on gender, the effect of genre is more prominent for women, as suggested by the greater number of features (i.e. 35) that significantly varies between female diaries and newspaper articles.
Independently from gender, newspapers are
characterized by longer words and, among the
considered parts-of-speech, by a higher
occurrence of prepositions (both simple and
articulated), of nouns and proper nouns, as well as by a
more extensive use of punctuation. The nominal
style characterizing this genre and suggested by
the higher proportion of nouns comes out clearly
at syntactic level: newspapers articles greatly
differ from diary pages since they present a higher
percentage of complements modifying a nouns
([11] Compl. and [11] Prep.) also organized in
longer embedded chains ([14]), two features which
are more common in highly informative texts than
in narrative texts like diaries
As expected, the language of diaries is identified by features typically characterizing narrative texts: the considered collection contains longer sentences, especially male diaries, and a lower percentage of high usage ([6] (f)) and high availability ([7] (f)) lexicon belonging to the Basic Italian Vocabulary (BIV). Features capturing the verbal morphology reflect the narrative style used to refer to experiences occurred in the past: the diaries (especially those by male authors) contain a higher usage of imperfect tense and more auxiliary verbs, possibly composing past tenses. In addition, a number of features suggests that the diary
Diaries
Women Gender
J
Genre Men
Newspaper articles
Women Men prose is typically characterized by a more subjective writing style. Namely, the collected diaries present a more extensive use of the first and second singular person verbs, especially those written by women (i.e. 1st person verb: 20.9 women vs 14.5 men), and a higher distribution of possessive adjectives.
If we focus on the gender dimension, our
results show that female writings are characterized
by features typically found in easier-to-read texts,
according to the literature on readability
assessment
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. 6
The work reported in the paper was partially supported by the 2–year project (2017-2019) UBIMOL, UBIquitous Massive Open Learning, funded by Regione Toscana (BANDO POR FESR 2014-2020). R. Sarawgi, K. Gajulapalli, and Y. Choi. 2011. Gender Attribution: Tracing Stylometric Evidence Beyond Topic and Genre. Proceedings of the Fifteenth Conference on Computational Natural Language Learning (CoNLL 2011), Portland, Oregon, USA, June 2324, 2011, pp. 78–86.