“La ministro è incinta”: A Twitter Account of Women’s Job Titles in Italian
Authors: Alessandra Teresa Cignarella, Mirko Lai, Andrea Marra, Manuela Sanguinetti (Università di Torino, Universitat Politècnica de València, Università di Cagliari, 2021)
Topic: Gender and Inclusive Language Studies

Abstract
We analyze the use of feminine forms indicating professions and roles held by women in Italian. The study is based on Twitter and collects data from 2006 to 2021. This allows us to set up both the quantitative and the qualitative study in a diachronic perspective on a time span of 15 years. We observe the distribution over time of a selection of feminine job titles (i.e., minister, mayor, rector, engineer and lawyer), compared to their masculine counterparts, distinguishing in particular the following cases: use of marked forms and use of semi-marked forms. The analysis shows that the trend of using feminine (i.e. marked) forms is generally growing through time. However, the unbalance between the actual number of women employed in some professions and the use of the correspondent feminine job title is wide.

Introduction
The studies on how sexes are represented in language pertain to a transdisciplinary field of research where linguistic aspects intersect with psychological and social issues <cit.>. The various types of gender representations in language, along with their asymmetries, is a matter widely studied in linguistics <cit.> as well as in social psychology <cit.>. Some of these studies have also affected Italian <cit.>, where a renewed debate has spread in the recent past on the use of a more gender-inclusive language.[Elsewhere also defined as gender-fair, gender-neutral or non-sexist language <cit.>.][<https://www.valigiablu.it/linguaggio-inclusivo-dibattito/>.]  The presence of gender biases and stereotypes has drawn much attention even in the Natural Language Processing community.[See, for example, the Workshop Series on Gender Bias in NLP: <https://genderbiasnlp.talp.cat/>.] Research in this field mainly focuses on the study of a model's performance on data associated with a certain gender, or rather on the association between gender and certain concepts as found in language models <cit.>.  The present work, instead, aims at giving an exploratory account of the linguistic visibility of women in Italian language, with a focus in particular on job titles. For this purpose, we analyze the use of feminine forms used for job titles and professional roles in Twitter.  Studies on corpus-based discourse analysis have already focused on gender issues with respect to job titles in Italian. They either quantitatively evaluate the mostly used gendered forms in texts when referring to female referents <cit.>, or rather assess, by means of a survey among native speakers, the degree of acceptability of some feminine job titles <cit.>.    From a theoretical point of view, such works revolve (overtly or more indirectly) around the notion of markedness in language, that can be intended here as the “contrast between the unmarked (general, usual, non-salient) and the marked (special, emphatic)” (Clyne2009 cited in [p.50]Formato2019b).[In its most general sense, this term refers to an opposition between two - otherwise equal - linguistic elements, one of which is characterized by the presence of a mark and the other by its absence (e.g. voicing in voiced vs voiceless stops). However, the notion underwent a number of different interpretations and applications. For an in-depth analysis of the different perspectives with which this concept is treated, we refer to Moravcsik and Wirth Moravcsik1986 and Haspelmath Haspelmath2006.] In the present context, the “general, usual, non-salient” case is represented by masculine forms when used to express a generic reference. This means that grammatical masculine nouns are perceived and used as unmarked terms (for both men and women) based on the idea that they represent how the world is, opposing marked feminine terms which are seen as new, ungrammatical and `sounding bad'.    While sharing with the studies mentioned above the same theoretical premise, the present work addresses the issue of women visibility in Italian language relying on user-generated data retrieved from Twitter: its peculiar nature as language data source, along with the opportunity it offers to extract and filter data based on specific keywords and time spans, makes this platform particularly useful for our purposes.  More precisely, we aimed at studying the distribution over time of a selection of feminine job titles, distinguishing in particular the following cases:     * the use of marked forms, i.e. feminine forms referring to female professionals (e.g. la sindaca Raggi (`mayorfem Raggi'));   * (for a restricted set of examples) the use of semi-marked forms <cit.>, i.e. the combination of masculine forms and feminine modifiers when referring to female professionals (e.g. la neo-ministro è incinta (‘thefem newmasc ministermasc is pregnant’)).  We thus provide some background knowledge on the main linguistic conventions of Italian language in the assignment of grammatical gender, also mentioning some of the well-known studies that have challenged such conventions over the years, towards a more inclusive use of feminine forms, especially for professions. We then describe how data has been collected and filtered, and show the distribution of the selected job titles in both forms and across a 15-year time span.

Conclusion
In this paper, we reported the results of a corpus-based account of the linguistic visibility of women in Italian language, with a focus in particular on job titles, and using Twitter as data source. From a preliminary analysis of a selection of profession nouns, we found that some marked forms are increasingly being preferred in spite of semi-marked expressions. Besides extending and systematizing this analysis to other case studies, we also aim to observe the usage of such forms by Italian native speakers by tackling the issue as a stance detection task, so to assess how the users value a given marked form and, more in general, the adoption of more gender-inclusive linguistic habits. Furthermore, the messages leveraged on this topic might overlap with the task of misogyny detection and hate speech detection as well, broadening the horizons of three different NLP detection tasks. This design choice can also be motivated with regard to contextual stance detection <cit.>, to investigate how supporters/opponents of inclusive language strategies are segregated in different online social network communities. Finally, due to its preliminary and exploratory nature, this work only reports the distribution of feminine and masculine forms, which are the two values for gender assignment taken in consideration for the analysis.  We are well aware, however, that a comprehensive study of gender-inclusive language must necessarily cover all those linguistic forms that refer to the multiple and diverse identities in the gender spectrum. With respect to this point, innovative forms have been proposed in the last years, in order to overcome the binary opposition, even in a grammatical gender language as Italian, such as the schwa (ə), the asterisk (*), the `at' sign (@), and other graphic solutions. This is another aspect that is worth exploring in a stance detection perspective, so to assess users' stance regarding the use of such linguistic innovations and their spread in everyday language.