scholarly journals Il progetto VVV: lessicografia, informatica e social network al servizio della promozione linguistica

2020 ◽  
Vol 26 ◽  
pp. 136-149
Author(s):  
Fabio Scetti ◽  
Federica Salamino
Keyword(s):  

Questo contributo si basa su un progetto lessicografico e fornisce informazioni importanti sulla promozione del Valoc ’, un dialetto a rischio di estinzione parlato in Val Masino (Lombardia, Italia). Lo scopo del progetto VVV è sviluppare il nuovo dizionario, basato sulla ricerca antropologica e dialettologica. Grazie al nostro approccio metodologico ci proponiamo di osservare le pratiche del Valoc ', la sua trasmissione da una generazione all'altra e discorsi che sostengono principalmente le ideologie in relazione alle pratiche linguistiche e all'identità. In questo lavoro, vorremmo presentare il contesto, descritto da un punto di vista linguistico e sociolinguistico, concentrandoci sull'importanza di promuovere il Valoc ’attraverso lezioni, conferenze, il dizionario e i social network. Infatti, grazie alla nostra pagina sui social network, è stato possibile osservare l'evoluzione del linguaggio e analizzare il modo in cui i parlanti affrontano l'esercizio della scrittura.

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.


Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.


2010 ◽  
Vol 9 (4) ◽  
pp. 181-194 ◽  
Author(s):  
Jürgen Weibler ◽  
Sigrid Rohn-Endres

This paper develops an understanding of how shared leadership emerges in social network interactions. On the basis of a qualitative research design (grounded theory methodology – GTM) our study in two interorganizational networks offers insights into the interplay between structures, individuals, and the collective for the emergence of shared network leadership (SNL). The network-specific Gestalt of SNL appears as a pattern of collective and individual leadership activities unified under the roof of a highly developed learning conversation. More importantly, our findings support the idea that individual network leadership would not emerge without embeddedness in certain high-quality collective processes of relating and dialogue. Both theoretical and practical implications of this original network leadership perspective are discussed.


1986 ◽  
Vol 22 (3) ◽  
pp. 310-316 ◽  
Author(s):  
Mary J. Levitt ◽  
Ruth A. Weber ◽  
M. Cherie Clark

Sign in / Sign up

Export Citation Format

Share Document