Effective Communication without Verbs? Sure! Identification of Nominal Utterances in Italian Social Media Texts
Authors: Gloria Comandini, Manuela Speranza, Bernardo Magnini (Università di Trento, Fondazione Bruno Kessler, 2018)
Topic: Lexical and Semantic Resources and Analysis

Abstract
Nominal utterances are very freEnglish. Nominal utterances are very frequent, especially in social media texts, and play a crucial role as they are very dense from a semantic point of view. In spite of this, their automatic identiﬁcation has received little to no attention. We have thus developed a framework for the annotation of nominal utterances and created the manually annotated corpus COSMIANU (Corpus Of Social Media Italian Annotated with Nominal Utterances), which could be used to train automatic systems.

Introduction
Syntactic declarative constructions built around a non-verbal head (as in, for example, “What a nice movie!”) are very common linguistic phenomena in many Indo-European, Slavic and Semitic languages (such as Latin, Hebrew, Arabic, Russian, Ugric and Bantu languages (Benveniste, 1990; Simone, 2013). Not all of these nominal constructions can be unanimously considered sentences, although they can surely be considered utterances, deﬁned as concrete units of actually produced text, devoid of any pre-determined syntactic or semantic form (Sabatini and Coletti, 1997; Adger, 2003; Grafﬁ, 2012; Ferrari, 2014). It has been clearly shown that nominal utterances (NUs) occur with relatively high frequency not only in spoken language (Cresti, 1998; Landolﬁet al., 2010; Garcia-Marchena, 2016) but also in written texts. Literary and journalistic prose certainly offer some ﬁne examples of NUs (Mortara Garavelli, 1971; Dardano and Trifone, 2001), but nonetheless texts produced with computer mediated communication (CMC) or, more generally, within social media, are also a fertile ground for this phenomenon. In fact, NUs are extremely important from the semantic point of view as they allow speakers or writers to provide a lot of information using only a few words (high semantic density), often without any explicit hierarchical relationship (Sornicola, 1981; Ferrari, 2011a), which is a typical feature of CMC (Ferrari, 2011b). Yet NUs pose signiﬁcant challenges when it comes to both their automatic processing, because of the absence of a verbal head, and identiﬁcation, due to the fact that they can have diverse syntactic structures, containing, for example, dependent clauses with ﬁnite verbs. So far, little or no attention has been paid to the identiﬁcation and processing of NUs in NLP areas such as information extraction/retrieval, sentiment analysis, and opinion mining. However, in order to address newly emerging challenges, these research ﬁelds could greatly beneﬁt from tackling NUs speciﬁcally. This is the case, for instance, with aspect-based sentiment analysis, which aims to identify the main (e.g., the most frequently discussed) aspects (e.g., food, service) of given target entities (e.g., restaurants) and the sentiment expressed towards each aspect, instead of detecting the overall polarity of a text span (as sentiment analysis usually does). Similarly, argumentation mining, which takes one step forward with respect to opinion mining by extracting not only information about people’s attitudes and opinions, but also about the arguments they give in favor of and against their target entities (e.g., products, institutions, politicians, celebrities, etc.), could dramatically improve by focusing on NUs, which are often used, just like slogans, as the most emphatic part of the argumentation. As a ﬁrst step towards enabling automatic systems to process NUs, we have developed a complete framework for their annotation, and have created the Corpus Of Social Media Italian Annotated with Nominal Utterances (COSMIANU), which will be freely distributed with a Creative Commons (CC-BY) licence and can therefore be used to train automatic systems. In this paper, we ﬁrst summarize the main criteria adopted for the annotation of NUs (Section 3); in Section 4 we describe the annotated corpus; in Section 5 we present the results of some preliminary experiments on automatic identiﬁcation of NUs, and ﬁnally, in Section 6, we draw some conclusions.

Conclusion
This work shows how common NUs are in written informal language, as well as how important they are in conveying semantically dense concepts in emphatic informative peaks, which could be useful for many NLP ﬁelds (e.g., argumentation mining and aspect-based sentiment analysis). By creating COSMIANU, an Italian corpus annotated with NUs, and making it freely available to the research community, we made a ﬁrst step towards the development of automatic tools for the identiﬁcation and classiﬁcation of NUs. In our preliminary experiments on NU identiﬁcation (performed using an SWM classiﬁer), with our best conﬁguration, we obtained a performance of 73.40% in terms of F1 on all NUs (i.e. including metadata). In the future, we intend to further expand COSMIANU, both in terms of its size and in terms of the annotations it includes, hoping that this will encourage more research on this extremely common, and yet almost neglected, linguistic phenomenon. We also plan to work on the analysis and automatic recognition of NUs, especially when they are used to convey hate speech, in the form of racist, sexist, homo/transphobic or classist slogans and insults. Acknowledgments We would like to thank Isabella Chiari for providing us the Web2Corpus IT, from which we selected the raw texts to build COSMIANU. We also thank our colleagues Roberto Zanoli and Rachele Sprugnoli for their valuable advice and contributions in performing the experiments and deﬁning the annotation guidelines.