Marco Guerini

CORPS: A Corpus of Tagged Political Speeches for Persuasive Communication Processing

ABSTRACT In political speech, even if the audience is sympathetic to the speaker and does not need to be persuaded, it tends to react or respond to signals of persuasive communication (including an expected theme, a name, an expression, and the tone of the voice). In this article, we describe the creation of a corpus of political speeches tagged with audience reactions, such as applause, as indicators of persuasive expressions. We hypothesize that corpora of this kind can be usefully employed in the qualitative analysis of political communication. In addition, we present a corpus-based approach for persuasive expression mining that relies on techniques from natural language processing (NLP). We show how the approach can support the analysis of political communication, providing insights well beyond those of traditional word-counting analysis techniques.

Exploring Image Virality in Google Plus

Reactions to posts in an online social network show different dynamics depending on several textual features of the corresponding content. Do similar dynamics exist when images are posted? Exploiting a novel dataset of posts, gathered from the most popular Google+ users, we try to give an answer to such a question. We describe several virality phenomena that emerge when taking into account visual characteristics of images (such as orientation, mean saturation, etc.). We also provide hypotheses and potential explanations for the dynamics behind them, and include cases for which common-sense expectations do not hold true in our experiments.

A TAXONOMY OF STRATEGIES FOR MULTIMODAL PERSUASIVE MESSAGE GENERATION

Future intelligent systems will have contextual goals to pursue. As opposed to more traditional scenarios of human computer interaction, intelligent persuasive systems may also aim to induce the user or, in general, the audience, to perform some actions in the real world. Some scenarios of application are dynamic advertisement, preventive medicine, social action, and edutainment. As a step in this direction, a prototype called Promoter was developed for the production of persuasive messages. In modeling persuasion, the cognitive state of the participants (beliefs, desires, and intentions) is taken into account, as well as their social relations, their emotions, and the context of interaction. In this article, a taxonomy of persuasive strategies and the meta-reasoning model that works on this taxonomy is described. The taxonomy is built by taking into consideration studies coming both from social psychology and philosophy, and from the area of natural argumentation. The taxonomy is not domain specific and it helps to bridge persuasion strategies and rhetorical relations, a fundamental element in text planning. The use of this taxonomy also permits reasoning on the basis of emotion expression in accordance with persuasion strategies for multimodal message generation.

Slanting existing text with Valentino

In this paper we present a tool for valence shifting of natural language texts, named Valentino (VALENced Text INOculator). Valentino can modify existing textual expressions towards more positively or negatively valenced versions. To this end we built specific resources, gathering valenced terms that are semantically or contextually connected to the original one, and implemented strategies that use these resources in the substitution process. Valentino is meant to be a modular component. It is non-domain specific and it requires as its input a coefficient that represents the desired valence for the final expression.

Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and Virality

This article provides a comprehensive investigation on the relations between virality of news articles and the emotions they are found to evoke. Virality, in our view, is a phenomenon with many facets, i.e. under this generic term several different effects of persuasive communication are comprised. By exploiting a high-coverage and bilingual corpus of documents containing metrics of their spread on social networks as well as a massive affective annotation provided by readers, we present a thorough analysis of the interplay between evoked emotions and viral facets. We highlight and discuss our findings in light of a cross-lingual approach: while we discover differences in evoked emotions and corresponding viral effects, we provide preliminary evidence of a generalized explanatory model rooted in the deep structure of emotions: the Valence-Arousal-Dominance (VAD) circumplex. We find that viral facets appear to be consistently affected by particular VAD configurations, and these configurations indicate a clear connection with distinct phenomena underlying persuasive communication.

PerKApp: A context aware motivational system for healthier lifestyles

In this paper we present PerKApp, a context-aware system for inducing the user to adopt healthier lifestyles, based on a novel combination of persuasion technologies, natural language generation techniques, and deep knowledge representation tools. In our view, personalized and tailored messages generated according to the characteristic of user, user preferences and the context are extremely useful to increase the effectiveness of persuasion efforts in terms of user acceptance of the proposed behaviors. The architecture of PerKApp is designed with the goal of ease scalability and extendibility to other domains by redefinition of the knowledge and linguistic content.

Sentiment Variations in Text for Persuasion Technology

Accurate wording is essential in persuasive verbal communication. Through it speakers can provide an affective connotation to the text and reveal their disposition or induce a similar disposition on the recipient. All this is apparent in persuasion texts par excellence, such as political speech and advertisement. Automatic sentiment variations of existing linguistic expressions open the way to promising applications, yet it is a challenging problem. In this paper we describe a system which takes up this challenge, together with a framework for evaluating the persuasiveness of the newly produced expressions.

Echoes of Persuasion: The Effect of Euphony in Persuasive Communication

While the effect of various lexical, syntactic, semantic and stylistic features have been addressed in persuasive language from a computational point of view, the persuasive effect of phonetics has received little attention. By modeling a notion of euphony and analyzing four datasets comprising persuasive and non-persuasive sentences in different domains (political speeches, movie quotes, slogans and tweets), we explore the impact of sounds on different forms of persuasiveness. We conduct a series of analyses and prediction experiments within and across datasets. Our results highlight the positive role of phonetic devices on persuasion.

Approaches to verbal persuasion in intelligent user interfaces

People tend to treat computers as social actors, even if these are usually designed as mere tools. This forces computers to play a social role without having the social skills to be successful (Reeves and Nass, 1996).

The New Release of CORPS: A Corpus of Political Speeches Annotated with Audience Reactions

In this paper we present the new release of CORPS CORpus of tagged Political Speeches that contains transcripts of political speeches tagged with audience reactions, such as APPLAUSE or LAUGHTER. The corpus has been built with the goal of allowing automatic processing of the stored data. These tags signal hot-spots about persuasive communication and can be usefully employed in many theoretical and applied fields, providing insights well beyond those of traditional word-count approaches. After introducing the main characteristics of the corpus and some quantitative descriptions, we discuss possible uses of this resource.