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

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

The weight of words: textual data versus sentiment analysis in stock returns prediction

The focus of this paper is to understand whether the words contained in a text corpus improves the explained variance of stock returns better than the use of the polarity of the same texts, obtained through a sentiment analysis using a generic ontological dictionary. The empirical analysis is based on the content of a weekly column in the most important Italian financial newspaper, which published past information and analysts’ recommendations on listed companies. The use of textual data clearly increases the explained variance of stock returns but, through comparisons between data mining techniques, we observed minor differences in terms of MSE, by adding a selection of specific terms as features. In this context, the text mining approach proved to be very useful to improve the explanatory power of forecasting models, while it emerged the limited explanatory power of an automatic sentiment analysis based on a generic lexicon

Introduction to the special section bio-optical and biogeochemical conditions in the South East Pacific in late 2004: the BIOSOPE program

International audienceThe objectives of the BIOSOPE (BIogeochemistry and Optics SOuth Pacific Experiment) project was to study, during the austral summer, the biological, biogeochemical and bio-optical properties of different trophic regimes in the South East Pacific: the eutrophic zone associated with the upwelling regime off the Chilean coast, the mesotrophic area associated with the plume of the Marquises Islands in the HNLC (High Nutrient Low Chlorophyll) waters of this subequatorial area, and the extremely oligotrophic area associated with the central part of the South Pacific Gyre (SPG). At the end of 2004, a 55-day international cruise with 32 scientists on board took place between Tahiti and Chile, crossing the SPG along a North-West South-East transect. This paper describes in detail the objectives of the BIOSOPE project, the implementation plan of the cruise, the main hydrological entities encountered along the ~8000 km South East Pacific transect, and ends with a general overview of the 32 other papers published in this special issue

Infinitesimal braidings and pre-Cartier bialgebras

We propose an infinitesimal counterpart to the notion of braided category. The corresponding infinitesimal braidings are natural transformations which are compatible with an underlying braided monoidal structure in the sense that they constitute a first-order deformation of the braiding. This extends previously considered infinitesimal symmetric or Cartier categories, where involutivity of the braiding and an additional commutativity of the infinitesimal braiding with the symmetry are required. The generalized pre-Cartier framework is then elaborated in detail for the categories of (co)quasitriangular bialgebra (co)modules and we characterize the resulting infinitesimal $\mathcal{R}$-matrices (resp. $\mathcal{R}$-forms) on the bialgebra. It is proven that the latter are Hochschild $2$-cocycles and that they satisfy an infinitesimal quantum Yang-Baxter equation, while they are Hochschild $2$-coboundaries under the Cartier (co)triangular assumption in the presence of an antipode. We provide explicit examples of infinitesimal braidings, particularly on quantum $2\times 2$-matrices, $\mathrm{GL}_q(2)$, Sweedler's Hopf algebra and via Drinfel'd twist deformation. As conceptual tools to produce examples of infinitesimal braidings we prove an infinitesimal version of the FRT construction and we provide a Tannaka-Krein reconstruction theorem for pre-Cartier coquasitriangular bialgebras. We comment on the deformation of infinitesimal braidings and construct a quasitriangular structure on formal power series of Sweedler's Hopf algebra.Comment: 38 page

New concepts in password management

Passwords have been used for many years in the security of computer systems. The password mechanism has not changed in recent years and has several inherent security problems. This paper examines several password problems including sniffers, dictionary and brute force attacks. A specific Department of Defense incident is cited to illustrate a method to thwart sniffers followed by several suggestions intended to increase the security of the password process