Massimiliano Elia

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.

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.

COLLEGO: An Interactive Platform for Studying Joint Action During an Ecological Collaboration Task

We describe the implementation and preliminary validation of an interactive platform – COLLEGO – to investigate joint action in a goal-oriented collaborative task. The platform records the interaction sequence of two partners alternating their leader/follower role. Two sensitized wooden surfaces are placed in front of each participant, who can use 6 cubes to build the tower. Any time a cube is picked/released, time stamp (ms) and position of selected objects are recorded. A case study showing how data are collected and analyzed to study dyad performance during the task is described. Finally, potential applications of the proposed solution are discussed.