Ingroup/outgroup dynamics and agency markers in Italian parliamentary language. A gender-based socio-psychological analysis of the speeches of men and women deputies (2001 and 2006).

The most recent literature on gender differences in language use has shown that the Italian political communication enacted by men and women parliamentarians only partly reflects and reproduces the asymmetries and stereotypes widespread in society. Starting from an anti-essentialist perspective, which holds that language differences between men and women speakers are much less extensive than claimed in the past, we analysed 463 parliamentary speeches in the course of the XIVth legislature (5-2001 / 4-2006) in four parliamentarian pairs, differentiated by gender and political orientation. The general aim was to explore the socio-psychological constructs of agency and ingroup/outgroup dynamics as revealed by linguistic behaviour in men/women parliamentarians. The two constructs were detected by specific linguistic markers in the interventions of men/women parliamentarian pairs. Specifically, for agency, we detected: (1a) pronoun variations between singular and plural first person (I, we); (1b) amplitude of we as either specific or superordinate; (1c) conditional modal form of verbs. For ingroup/outgroup dynamics, we detected: (2a) pronoun variation between first and second plural person (we vs. you) and (2b) their valence. Lexicographical analysis was carried out with statistical packages TaLTaC2 and TreeTagger on a corpus of 432,671 words. Chi-square and z-test were applied to word frequencies, while Student’s t-tests were applied to gender comparisons. The results showed reduced variability between men/women parliamentarians in the use of linguistic devices, confirming the weakness of the essentialist and binary logic that has long dominated the field of studies on language and gender

Anticipatory Savoring and Consumption: Just Thinking about That First Bite of Chocolate Fills You Up Faster

Two laboratory studies examine how consumers adjust their eating to the size of the portion they expect to receive. Participants who knew in advance that they would receive six pieces of chocolate waited less time before eating each piece and ate more pieces than participants who expected to receive only two pieces when they started, even though both groups were ultimately offered six pieces. In the second study, natural variance in how long participants waited before tasting the chocolates was negatively related to how many additional pieces they thought they could eat after finishing the last piece. These results suggest that increasing the interval prior to taking the first bite of a piece of chocolate reduced overall consumption. When consumers focus their attention on eating, the interval before taking the first bite captures anticipatory savoring - psychologically looking forward to the actual consumption experience

Different usage profiles for listeners of music delivered via interactive television, free-to-air radio, and personal music collections

This study examines the audience profile and usage patterns of interactive cable/satellite audio (ICSA) listeners and compares them with listeners of free-to-air radio (FTA) and personal music collections(PMC). A survey of ICSA users in Australia reveals that heavy users of ICSA are also likely to be heavy users of FTA and PMC. However, ICSA listeners are significantly older than FTA or PMC listeners and prefer music formats different to those reflected in radio audiences and CD sales

Information Behavior and Political Preferences

This article shows that citizens consider policy positions for the formation of their political preferences when they actively seek and find high-quality information, while they dismiss passively acquired and low-quality information. The study develops an extended theory of information and political preferences that incorporates the process of information acquisition and its connection with information quality. A novel experimental design separates the effects on political preferences due to information behavior as an activity from those due to selective exposure to information. The study applies this design in a laboratory experiment with a diverse group of participants using the example of issue voting and European integration in the context of the 2014 European Parliament elections

Italian Political Communication and Gender Bias: Press Representations of Men/Women Presidents of the Houses of Parliament (1979, 1994, and 2013)

The study considers mass media communication as intertwined with social norms, as assumed by the perspective of social representations. It explores the Italian press communication by focusing on three pairs of men and women politicians with different political orientations and all serving as presidents of the Houses of Parliament in three legislatures. The article concentrates on five newspapers in order to sound out the presence of a possible gender bias in favor of men in the coverage. It explores the strategic use of language to enhance or penalize the role of women politicians. In order to scrutinize the role of gender visibility and discrimination, the study compares how women and men presidents are named and examines the linguistic sexism/nonsexism used for women politicians also in relation to the ideological/cultural orientations of newspapers. Thereby, 591 headlines were collected and analyzed with SPAD-T statistical package. The results, for some cases, confirm the trends revealed in the international literature, in other cases, disprove expectations

Hybrid RF-Energy Harvester for IoT Smart Device Applications Low Power Consumption

Energy independence and long battery lifetime, the vision of 5G technology is one of them for IoT smart devices. Focusing on the challenges in this technological vision, the solution for this system is to harvest the energy sources around it as a backup or eliminate the use of batteries. The output of the hybrid energy harvester method as a solution to energy independence using radio frequency (RF) waves has been optimized in this study. The double-T patch microstrip antenna based on CSRR metamaterial as an RF energy harvester works at the ISM band frequency of 2.45 GHz and has return loss, gain and bandwidth values that are in accordance with the concept of the RF-Energy harvester system. This antenna is capable of absorbing energy using a DC converter circuit at a maximum distance of 6.79 V using 2 access points at the position of the transmitting antenna facing each other with a conversion efficiency of 6.68%. One method to maximize the output of the energy harvester is also carried out in this study by doing a hybrid with a mini solar cell, which is able to carry out constant voltage and can charge the load in the form of a cellphone. The hybrid RF-Energy harvester system designed in this research can be used as a source of energy in smart devices with small power requirements

Linguaggio, ideologia e categorizzazione sociale : un’analisi psicologico sociale del documento di rivendicazione dell’attentato a Marco Biagi

Louvain-la-Neuv

Hybrid Deep Learning Approach For Stress Detection Model Through Speech Signal

Stress is a psychological condition that requires proper treatment due to its potential long-term effects on health and cognitive faculties. This is particularly pertinent when considering pre- and early-school-age children, where stress can yield a range of adverse effects. Furthermore, detection in children requires a particular approach different from adults because of their physical and cognitive limitations. Traditional approaches, such as psychological assessments or the measurement of biosignal parameters prove ineffective in this context. Speech is also one of the approaches used to detect stress without causing discomfort to the subject and does not require prerequisites for a certain level of cognitive ability. Therefore, this study introduced a hybrid deep learning approach using supervised and unsupervised learning in a stress detection model. The model predicted the stress state of the subject and provided positional data point analysis in the form of a cluster map to obtain information on the degree using CNN and GSOM algorithms. The results showed an average accuracy and F1 score of 94.7% and 95%, using the children's voice dataset. To compare with the state-of-the-art, model were tested with the open-source DAIC Woz dataset and obtained average accuracy and F1 scores of 89% and 88%. The cluster map generated by GSOM further underscored the discerning capability in identifying stress and quantifying the degree experienced by the subjects, based on their speech pattern