Mining Italian Short Argumentative Texts
Authors: Ivan Namor, Pietro Totis, Samuele Garda, Manfred Stede (Università di Padova, KU Leuven, University of Potsdam, 2019)
Topic: Lexical and Semantic Resources and Analysis

Abstract
We present the first model for argumentation mining for Italian short argumentative texts. We adapted to Italian the software developed by (Peldszus and Stede, 2015) and built a suitable corpus of Italian "microtexts" by semi-automatically translating the original English corpus. Our results are comparable to those of (Peldszus and Stede, 2015), which proves that their model is applicable successfully to languages other than English and German.

Introduction
In recent years, argumentation mining (Lippi and Torroni, 2016) has become an area of big interest in the field of natural language processing. Argumentation mining seeks to automatically recognize the structure of the argumentation in a text by identifying, classifying and connecting the central claim of a text, supporting premises, possible objections and counter-objection. Argumentation mining has many possible applications in very different fields. Recognizing automatically the argumentative structure of a text can be useful as an extension of opinion mining, in retrieval of court decisions from databases (Palau and Moens, 2011), in automatic document summarization (Teufel and Moens, 2002), in analysis of scientific papers as in biomedical text mining (Teufel, 2010; Liakata et al., 2012) in essay scoring, and more. This task can be decomposed into several subtasks: segmentation of the text in elementary discourse units (EDUs), identification of argumentative discourse units (ADUs), classification of argumentative discourse units, identification of the relations between argumentative discourse units and classification of these relations. The argumentation structure of a text can be presented as a tree structure, with a node for each argumentative discourse unit and different edges between nodes representing the different types of relations. There are many simple models that recognize automatically the argumentation structure of a micro-text. Our starting point is the model by (Peldszus and Stede, 2015), who developed a software to automatically mine the argumentation structure of short texts for English and German. In this paper we perform argumentation mining on a corpus of short Italian argumentative texts. To transfer the approach to Italian, we assembled a suitable corpus by semi-automatically translating the original German corpus and we adapted the features used by the software, by assembling a list of Italian connectives necessary to fulfill the task. Our results are slightly lower than the ones for German and English, but they demonstrate that the model can be considered valid also for Italian. Besides, a major contribution of this paper is the free availability of the annotated Italian corpus.

Conclusion
We presented, to our knowledge, the first model that transfers on an Italian microtexts corpus the approach developed by (Peldszus and Stede, 2015). We ran the experiment on an Italian corpus obtained by translating the original German one and by designing a suitable list of connectives. We adapted the code by changing the sections related to the corpus and the NLP tools. Our results are comparable to those of Peldszus and Stede, which proves that their model is applicable successfully to languages other than English and German.