Valentino Zurloni

Linguistic Intergroup Bias in Political Communication

The Linguistic Intergroup Bias (LIB) illustrates the disposition to communicate positive in-group and negative out-group behaviors more abstractly than negative ingroup and positive out-group behaviors. The present research examined the function of language in reinforcing this bias in political communication. To illustrate the LIB, the Linguistic Category Model (LCM) was used, including a nouns category. Because social stereotypes are usually conveyed by nominal terms, the aim was to observe the relationship between stereotypes and language in political communication. Moreover, we were interested in analyzing the psychological processes that drive the LIB. Therefore, we verified whether the LIB is more related to language abstractness than to agent-patient causality. Several political debates and interviews, which took place before the latest Italian provincial elections, were analyzed. Results suggested that the language politicians use in communicating about political groups are conceptualized as stereotypes rather than as trait-based categories. Moreover, it seems that the LIB could not be explained only at a lexical level. Social implications of the present findings in interpersonal relations and causal attribution were discussed.

A multimodal database as a background for emotional synthesis, recognition and training in e-learning systems

This paper presents a multimodal database developed within the EU-funded project MYSELF. The project aims at developing an e-learning platform endowed with affective computing capabilities for the training of relational skills through interactive simulations. The database includes data coming from 34 participants and concerning physiological parameters, vocal nonverbal features, facial expression and posture. Ten different emotions were considered (anger, joy, sadness, fear, contempt, shame, guilt, pride, frustration and boredom), ranging from primary to self-conscious emotions of particular relevance in learning process and interpersonal relationships. Preliminary results and analyses are presented, together with directions for future work.

How Game Location Affects Soccer Performance: T-Pattern Analysis of Attack Actions in Home and Away Matches

The influence of game location on performance has been widely examined in sport contexts. Concerning soccer, game-location affects positively the secondary and tertiary level of performance; however, there are fewer evidences about its effect on game structure (primary level of performance). This study aimed to detect the effect of game location on a primary level of performance in soccer. In particular, the objective was to reveal the hidden structures underlying the attack actions, in both home and away matches played by a top club (Serie A 2012/2013—First Leg). The methodological approach was based on systematic observation, supported by digital recordings and T-pattern analysis. Data were analyzed with THEME 6.0 software. A quantitative analysis, with nonparametric Mann–Whitney test and descriptive statistics, was carried out to test the hypotheses. A qualitative analysis on complex patterns was performed to get in-depth information on the game structure. This study showed that game tactics were significantly different, with home matches characterized by a more structured and varied game than away matches. In particular, a higher number of different patterns, with a higher level of complexity and including more unique behaviors was detected in home matches than in the away ones. No significant differences were found in the number of events coded per game between the two conditions. THEME software, and the corresponding T-pattern detection algorithm, enhance research opportunities by going further than frequency-based analyses, making this method an effective tool in supporting sport performance analysis and training.

Multimodal Deception Detection: A t-pattern Approach

This work proposes a new approach to deception detection, based on finding significant differences between liars and truth tellers through the analysis of their behavior, verbal and non-verbal. This is based on the combination of two factors: multimodal data collection, and t-pattern analysis. Multimodal approach has been acknowledged in literature about deception detection and on several studies concerning the understanding of any communicative phenomenon. We believe a methodology such as T-pattern analysis could be able to get the best advantages from an approach that combines data coming from multiple signaling systems. In fact, T-pattern analysis is a recent methodology for the analysis of behavior that unveil the complex structure at the basis of the organization of human behavior. For this work, we conducted an experimental study and analyzed data related to a single subject. Results showed how T-pattern analysis allowed to find differences between truth telling and lying. This work aims at making progress in the state of knowledge about deception detection, with the final goal to propose a useful tool for the improvement of public security and well-being.

Imposing cognitive load to unmask prepared lies

The aim of our study is to examine whether the overall organization of behavior differs when people report truthful vs. deceptive messages within the framework of the T-pattern model. We tested the hypothesis that the differences between liars and truth tellers will be greater under high cognitive load conditions. We argue that recalling stories in reverse order will produce cognitive overloading in subjects, because their cognitive resources are already partially spent on the lying task; this should emphasize nonverbal differences between liars and truth tellers. Results support the hypothesis that discriminating behavioral patterns between truth and lie could be easier under high cognitive load condition. Moreover, they suggest that future research on deception detection may focus more on patterns of behavior rather than on individual cues.

Fallacies as Argumentative Devices in Political Debates

The current paper attempts to contribute to the study of argumentation in political debates. We propose an examination of the role of fallacies in political argumentation. In the first two sections we conduct a brief review of literature on the concepts of argumentation and fallacies to show that they both converge in emphasizing the role of discourse type when evaluating the efficacy of communicative strategies. This perspective is then applied in the analysis section to look at the role of fallacies in a political debate on nuclear energy held in Italy. We conduct a discourse analysis of the transcript based on which we identify a variety of relevant paths followed by speakers when constructing arguments. The findings demonstrate how several informal fallacies argumentum ad baculum, argumentum ad hominem, argument from analogy, argumentum ad consequentiam are strategically used by politicians in order to put forward coherent and strong positions.

Addressing emotions within e-learning systems

Emotions are attracting growing attention within the instructional design research community. However, clarification is still required as to how exactly to address emotions within the field of e-learning. The aim of this chapter is twofold. Firstly, we will focus on the reasons for including emotions within the instructional technology domain, and in particular, on the relevance of emotions to computer-based learning. The need for specific theory in this regard is heightened by the current drive to design instructional devices that interact with learners in a motivating, engaging, and helpful way. Secondly, within the of the framework affective computing paradigm, the different modalities for detecting emotions in instructional technology contexts will be systematically reviewed, and the strengths and limits of each will be discussed on the basis of the most up-to-date research outcomes. Finally, a tentative architecture for emotion recognition in computerbased learning will be proposed, focusing on the adoption of a multimodal approach to emotion recognition, in order to overcome the limitations and the difficulties associated with individual modalities. Valentino Zurloni CESCOM, University of Milan Bicocca, Italy Fabrizia Mantovani CESCOM, University of Milan Bicocca, Italy & ATN-P LAB, Istituto Auxologico Italiano, Italy Marcello Mortillaro CESCOM, University of Milan Bicocca, Italy & CISA University of Geneva, Switzerland Antonietta Vescovo CESCOM, University of Milan Bicocca, Italy Luigi Anolli CESCOM, University of Milan Bicocca, Italy Addressing Emotions within E-Learning Systems

T-Pattern Analysis and Cognitive Load Manipulation to Detect Low-Stake Lies: An Exploratory Study

Deception has evolved to become a fundamental aspect of human interaction. Despite the prolonged efforts in many disciplines, there has been no definite finding of a univocally “deceptive” signal. This work proposes an approach to deception detection combining cognitive load manipulation and T-pattern methodology with the objective of: (a) testing the efficacy of dual task-procedure in enhancing differences between truth tellers and liars in a low-stakes situation; (b) exploring the efficacy of T-pattern methodology in discriminating truthful reports from deceitful ones in a low-stakes situation; (c) setting the experimental design and procedure for following research. We manipulated cognitive load to enhance differences between truth tellers and liars, because of the low-stakes lies involved in our experiment. We conducted an experimental study with a convenience sample of 40 students. We carried out a first analysis on the behaviors’ frequencies coded through the observation software, using SPSS (22). The aim was to describe shape and characteristics of behavior’s distributions and explore differences between groups. Datasets were then analyzed with Theme 6.0 software which detects repeated patterns (T-patterns) of coded events (non-verbal behaviors) that regularly or irregularly occur within a period of observation. A descriptive analysis on T-pattern frequencies was carried out to explore differences between groups. An in-depth analysis on more complex patterns was performed to get qualitative information on the behavior structure expressed by the participants. Results show that the dual-task procedure enhances differences observed between liars and truth tellers with T-pattern methodology; moreover, T-pattern detection reveals a higher variety and complexity of behavior in truth tellers than in liars. These findings support the combination of cognitive load manipulation and T-pattern methodology for deception detection in low-stakes situations, suggesting the testing of directional hypothesis on a larger probabilistic sample of population.

Negative social emotions and cognition: Shame, guilt and working memory impairments

Negative emotions can have an impact on a variety of cognitive domains, including Working Memory (WM). The present work investigated whether shame and guilt modulate WM performance in a dual-task test both in a non-clinical and a clinical population. In Experiment 1, 76 non-clinical participants performed a dual-task before and after being randomly assigned to shame, guilt or neutral inductions elicited by the writing of autobiographical past experiences. Shame and guilt elicitations were related to impaired WM performances. In Experiment 2, 65 clinical inpatients with eating disorders were assigned to the same procedure. The negative relationship of self-conscious emotions and WM was confirmed. Taken together these results suggest that shame and guilt are related to impairments of WM in both clinical and non-clinical participants.

Cultural Diversities Across and Within Cultures: The Bicultural Mind

In the current transition from structural to process models in the scientific inquiry on culture dynamics, culture is not viewed as consensual, enduring, and context-general, but as fragmented, fluctuating, and context-specific (situated cognition model). Bicultural individuals that, through enduring exposure to at least two cultures, have come to possess a bicultural mind, that is, systems of meaning and practices of both cultures, can therefore switch between such cultural orientations alternating them depending on the cultural cues (cultural primers) available in the immediate context (cultural frame switching). The bicultural mind roots in a dynamic bicultural brain: although culture is limited to what the brain can or cannot do, it does also shape brain functions, that is, neural connectivity is likely modified through sustained engagement in cultural practices. Built in a theoretical framework combining a co-evolutionary perspective on biology and culture with the expert-novice dynamics of cultural transmission and appropriation, the bicultural mind thus provides an articulated theoretical milieu apt to address the “why” and “how” (rather than “what”) questions on the managing of cultural diversities within and across cultures. And, in Gould’s view on punctuated equilibria, it can even be considered as the next evolutionary jump within the human species.