Item weighted Kemeny distance for preference data

Preference data represent a particular type of ranking data where a group of people gives their preferences over a set of alternatives. The traditional metrics between rankings don’t take into account that the importance of elements can be not uniform. In this paper the item weighted Kemeny distance is introduced and its properties demonstrated

Social capital and social network sites: an empirical analysis of European high school students

This paper shows the results of part of an empirical study which was developed in the sphere of the PACT EU project (Pathways for Carbon Transitions). The performed analysis concerns the social capital of young Europeans in terms of trust, size of personal networks, volunteering activities and usage of social network sites (SNS). The purpose of the work is, on one hand, exploratory, especially in aspects related to the comparison between relational context of social networks and virtual networks. At the same time, the research aims to confirm on this particular population some of the hypothesis coming from the literature on social capital, and to verify the existence of differences between European countries regarding relational characteristics

Dimensionality Reduction of Unstructured and Network Data for Stance Detection

The idea behind this work stems from the participation in some shared tasks concerning stance detection in NLP conferences. In these competitions, participants tried to develop the best stance prediction system for 'favor', 'against', and 'none' categories on selected topics, according to messages and relationships among users of a social networking site. Thus, the data available consisted of textual and network data. The teams we collaborated with used dimensionality reduction methods for network data, through a Multidimensional Scaling. On the other hand, the approach towards textual data involved different methods of feature extraction, without paying particular attention to dimensionality reduction for unstructured data. In this paper we show the empirical results of a two-step strategy to obtain lower-dimensional textual data relying on text mining techniques and principal component analysis. The results show levels of accuracy comparable to classical feature extraction techniques and to the best task models, despite using a much smaller number of predictors

Evidence for the production of three massive vector bosons in pp collisions with the ATLAS detector

A search for the production of three massive vector bosons in proton--proton collisions is performed using data at s√=13TeV recorded with the ATLAS detector at the Large Hadron Collider in the years 2015--2017, corresponding to an integrated luminosity of 79.8fb−1. Events with two same-sign leptons ℓ (electrons or muons) and at least two reconstructed jets are selected to search for WWW→ℓνℓνqq. Events with three leptons without any same-flavour opposite-sign lepton pairs are used to search for WWW→ℓνℓνℓν, while events with three leptons and at least one same-flavour opposite-sign lepton pair and one or more reconstructed jets are used to search for WWZ→ℓνqqℓℓ. Finally, events with four leptons are analysed to search for WWZ→ℓνℓνℓℓ and WZZ→qqℓℓℓℓ. Evidence for the joint production of three massive vector bosons is observed with a significance of 4.0 standard deviations, where the expectation is 3.1 standard deviations

COVID-19 Outbreak through Tweeters\u2019 Words: Monitoring Italian Social Media Communication about COVID-19 with Text Mining and Word Embeddings

In this paper we aim to analyze the Italian social media communication about COVID-19 through a Twitter dataset collected in two months. The text corpus had been studied in terms of sensitivity to the social changes that are affecting people's lives in this crisis. In addition, the results of a sentiment analysis performed by two lexicons were compared and word embedding vectors were created from the available plain texts. Following we tested the informative effectiveness of word embeddings and compared them to a bag-of-words approach in terms of text classification accuracy. First results showed a certain potential of these textual data in the description of the different phases of the outbreak. However, a different strategy is needed for a more reliable sentiment labeling, as the results proposed by the two lexicons were discordant. Finally, although presenting interesting results in terms of semantic similarity, word embeddings did not show a predictive ability higher than the frequency vectors of the terms

Commutators and crossed modules of color Hopf algebras

In a previous paper we showed that the category of cocommutative color Hopf algebras is semi-abelian in case the group $G$ is abelian and finitely generated and the characteristic of the base field is different from 2 (not needed if $G$ is finite of odd cardinality). Here we describe the commutator of cocommutative color Hopf algebras and we explain the Hall's criterion for nilpotence and the Zassenhaus Lemma. Furthermore, we introduce the category of color Hopf crossed modules and we explicitly show that this is equivalent to the category of internal crossed modules in the category of cocommutative color Hopf algebras and to the category of simplicial cocommutative color Hopf algebras with Moore complex of length 1.Comment: 25 page

For One or Many? Recommendation Targeting and Consumer Advice Integration

As consumers, many of our most important decisions are not made in isolation. Rather, it is common for individuals to pursue, evaluate, and rely on advice from other individuals. While research on advice usage from multiple or individual advisors has been investigated, no research has looked at advice integration when the advice is offered to an individual or group. This is an important consideration of advice as online review sites (e.g. Yelp, Expedia, and Foursquare) and social media platforms (e.g. Twitter and Facebook) now make it easy for consumers to make general recommendations targeted at a large number of individuals. To help fill this knowledge gap, the current research addresses the impact of advice targeting on consumers’ likelihood of integrating recommendations into their decisions. Across two experiments, we demonstrate that the acceptance of advice that is targeted at a group or an individual is dependent upon tie-strength between the advisor and the advisee. In particular, we show that when a strong tie exists, consumers are more likely to take individually targeted advice when compared to group targeted advice. Conversely, when a weak tie exists, consumers are more likely to utilize group targeted advice rather than individually targeted advice. In addition, we find that psychological reactance to the proffered advice drives this demonstrated effect. These results offer insight into consumers’ advice usage and suggest that personalized advice might not always be the most effective means to influence consumer decision making

Generic analysis of the response of calcifying microalgae to an elevation of pCO2 : qualitative vs quantitative analysis

International audienceCalcifying microalgae can play a key role in atmospheric CO2 trapping through large scale precipitation of calcium carbonate in the oceans. However, recent experiments revealed that the associated fluxes may be slow down by an increase in atmospheric CO2 concentration. In this paper we design models to account for the decrease in calcification and photosynthesis rates observed after an increase of pCO2 in Emiliania huxleyi chemostat cultures. Since the involved mechanisms are still not completely understood, we consider various models, each of them being based on a different hypothesis. These models are kept at a very general level, by maintaining the growth and calcification functions in a generic form, i.e. independent on the exact shape of these functions and on parameter values. The analysis is thus performed using these generic functions where the only hypothesis is an increase of these rates with respect to the regulating carbon species. As a result, each model responds differently to a pCO2 elevation. Surprisingly, the only models whose behaviour are in agreement with the experimental results correspond to carbonate as the regulating species for photosynthesis. Finally we show that the models whose qualitative behaviour are wrong could be considered as acceptable on the basis of a quantitative prediction error criterion.Les microalgues calcifiantes jouent un rôle clé dans le piégeage du CO2 atmosphérique d’origine anthropique en précipitant du carbonate de calcium qui sédimente au fond des océans. Toutefois, des expériences en laboratoire ont suggéré que cette activité biologique pourrait être diminuée par l’augmentation de la pression partielle de CO2 (pCO2) dans les océans qui a tendance à s’ équilibrer avec celle de l’atmosphère. Dans ce papier, nous concevons des modèles dynamiques pour essayer de simuler la diminution des taux de calcification et de photosynthèse observés chez Emiliania huxleyi après une hausse de la pCO2 reproduite en chémostat. Comme les mécanismes physiologiques impliqués sont encore loin d’ être complètement élucidés, nous considérons différents modèles, chacun d’eux étant basé sur une hypothèse biologique différente. Ces modèles, construits en utilisant des fonctions génériques pour caractériser les processus de croissance et de calcification, peuvent être analysés indépendamment de la forme exacte de ces fonctions et de la valeur des paramètres. L’ étude s’appuie donc sur ces fonctions génériques où la seule hypothèse est une régulation de ces taux par une des trois formes qui composent la totalité du carbone inorganique dissous : le CO2, les carbonates et les bicarbonates. Il s’en suit que chaque modèle réagit différemment à une élévation de la pCO2. Contrairement aux hypothèses classiquement admises, notre étude montre que les seuls modèles dont le comportement est en accord avec les résultats expérimentaux sont ceux pour lesquels une régulation de la photosynthèse par les carbonates a été supposée, ce qui corrobore les conclusions de travaux récents. Enfin, nous montrons que les modèles dont le comportement qualitatif est mauvais ne seraient pas rejetés sur la base d’un critère quantitatif d’erreur de prédiction

Pixel vs. Font. Facebook and Young People’s Self-Presentation

This paper explores various strategies for self-presentation used on Facebook, among a sample of 1330 Italian students aged 14-19 years. Based on two social network site practices, the production of text material and the publication of personal photos, we have constructed a model embracing four types of categories and behaviors. We examined the categories according to structural variables, variables regarding self-narration, and two psychological scales. The results show the validity of the four categories in distinguishing different styles of Facebook use and allowing us to define those styles in greater depth. In particular, the publication of photos by those who do not contribute written text seems to indicate the need to maintain one’s real-life social network; the production of text alone seems to reflect the need to deepen one’s most passionate interests; while the combination of the two communicative modes tends to reveal a greater capacity in planning for the future