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

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

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

Semi-abelian condition for color Hopf algebras

Recently, in [22], it was shown that the category of cocommutative Hopf algebras over an arbitrary field k is semi-abelian. We extend this result to the category of cocommutative color Hopf algebras, i.e. of cocommutative Hopf monoids in the symmetric monoidal category of G-graded vector spaces with G an abelian group, given an arbitrary skew-symmetric bicharacter on G, when G is finitely generated and the characteristic of k is different from 2 (not needed if G is finite of odd cardinality). We also prove that this category is action representable and locally algebraically cartesian closed, then algebraically coherent. In particular, these results hold for the category of cocommutative super Hopf algebras by taking G = Z_{2}. Furthermore, we prove that, under the same assumptions on G and k, the abelian category of abelian objects in the category of cocommutative color Hopf algebras is given by those cocommutative color Hopf algebras which are also commutative

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

Dynamic coupling of photoacclimation and photoinhibition in a model of microalgae growth.

International audienceThe development of mathematical models that can predict photosynthetic productivity of microalgae under transient conditions is crucial for enhancing large-scale industrial culturing systems. Particularly important in outdoor culture systems, where the light irradiance varies greatly, are the processes of photoinhibition and photoacclimation, which can affect photoproduction significantly. The former is caused by an excess of light and occurs on a fast time scale of minutes, whereas the latter results from the adjustment of the light harvesting capacity to the incoming irradiance and takes place on a slow time scale of days. In this paper, we develop a dynamic model of microalgae growth that simultaneously accounts for the processes of photoinhibition and photoacclimation, thereby spanning multiple time scales. The properties of the model are analyzed in connection to PI-response curves, under a quasi steady-state assumption for the slow processes and by neglecting the fast dynamics. For validation purposes, the model is calibrated and compared against multiple experimental data sets from the literature for several species. The results show that the model can describe the difference in photosynthetic unit acclimation strategies between Dunaliella tertiolecta (n-strategy) and Skeletonema costatum (s-strategy)

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