Annotation and Analysis of the PoliModal Corpus of Political Interviews
Authors: Daniela Trotta, Sara Tonelli, Alessio Palmero Aprosio, Annibale Elia (Università di Salerno, Fondazione Bruno Kessler, 2019)
Topic: Multimodal

Abstract
In this paper, we present the first available corpus of Italian political interviews with multimodal annotation, consisting of 56 face-to-face interviews taken from a political talk show. We detail the annotation scheme and we present a number of statistical analyses to understand the relation between these multimodal traits and language complexity. We also exploit the corpus to test the validity of existing studies on political orientation and language use, showing that results on our data are not as clear-cut as on English ones.

Introduction
In the context of a political interview, the host, typically a journalist, acts as a representative of the audience. This means that, if a politician manages to convince or deal with the criticism that the host addresses, then her/his trustworthiness, reliability and credibility will be easily established. In this situation, a politician is judged not only based on one’s arguments and rhetorical choices, but also on the attitude, self-confidence, and in general on an overall convincing behaviour. For example, if a politician seems to be conversationally dominant and manages interruptions to a satisfactory degree, it is more likely that the host, and therefore the audience, will be convinced by the arguments put forward by the interviewee. For this reason, analysing the combination of verbal and non-verbal elements in a political interview could be very interesting for scholars in political science and communication science, and in general to study consensus mechanisms. In this light, we present the first multimodal corpus of political interviews in Italian, and analyze how the combination of verbal and non-verbal elements can shed new light into political agendas and politicians’ attitude. By ‘multimodal’ we mean that the corpus is composed of manual transcriptions of interviews broadcast on TV and annotated with information not only about the linguistic structure of the utterances but also about non-verbal expressions. The corpus, which we call PoliModal, addresses the need to make up for the lack of Italian linguistic resources for political-institutional communication and is annotated in XML following the standard for the transcriptions of speech TEI Guidelines for Electronic Text Encoding and Interchange. In all transcripts, interviewers, interviewees and other guests’ turns have been enriched with the manual annotation of non-lexical and semi-lexical aspects such as breaks, interruptions, false starts, overlaps, interjections, etc. Furthermore, additional linguistic traits related to language complexity, use of pronouns and persons’ mentions have been automatically tagged, enabling an in-depth analysis of speakers’ attitude and communication strategy. In this work we present not only the corpus, which is made freely available at the link https://github.com/dhfbk/InMezzoraDataset, but also an analysis that, combining verbal and non-verbal elements, shows how these traits contribute to making an interview more or less convincing.

Conclusion
In this work, we present PoliModal, the first freely-available multimodal corpus of political interviews, manually annotated with six non-verbal traits. The corpus covers 56 interviews, where each guest is associated with a role (for non politicians) or a political party. We also present a first statistical analysis of the traits and their association with language complexity and with the speakers’ political orientation. In the future, we plan to start from the annotated material not only to extend the corpus, but also to investigate other aspects of political communication. For example, the choice to note non-verbal expressions is motivated by the will to study the strategies of persuasion used by the speakers. According to Poggi (2005), persuasion strategies are multimodal constructs because politicians – specifically in televised political interviews – attempt to persuade their supporters not only by their discursive style and argumentative speech, but also through their personality and their interactional behaviour. In the context of a political interview, persuasion is related to conversational dominance, i.e. a speaker’s tendency to control the other speaker’s conversational actions over the course of an interaction (Itakura, 2001), which is made evident through the kind of non-verbal expressions annotated in our corpus. Finally, since at the moment only one annotator has performed the transcription, segmentation and tagging task, we plan to compute inter-annotator agreement in the near future. The annotation task addressed so far falls – from a qualitative point of view – in the first of the general types identified by (Mathet et al., 2015), in which the subjective interpretation is limited. Indeed, it deals with the “identification of units” (Krippendorff, 2018), in which the annotator, given a written or spoken text, must identify the position and boundary of linguistic elements (e.g. identification of prosodic or gestural units, topic segmentation). We therefore expect agreement to be at least fair, but we plan to measure it using standard metrics.