160 research outputs found
Potentially preventable readmissions - narrowing identification of patients at risk of unplanned readmission
Interplay between telecommunications and face-to-face interactions - a study using mobile phone data
In this study we analyze one year of anonymized telecommunications data for
over one million customers from a large European cellphone operator, and we
investigate the relationship between people's calls and their physical
location. We discover that more than 90% of users who have called each other
have also shared the same space (cell tower), even if they live far apart.
Moreover, we find that close to 70% of users who call each other frequently (at
least once per month on average) have shared the same space at the same time -
an instance that we call co-location. Co-locations appear indicative of
coordination calls, which occur just before face-to-face meetings. Their number
is highly predictable based on the amount of calls between two users and the
distance between their home locations - suggesting a new way to quantify the
interplay between telecommunications and face-to-face interactions
Analyzing Users' Activity in On-line Social Networks over Time through a Multi-Agent Framework
[EN] The number of people and organizations using online social networks as a new way of communication is continually increasing. Messages that users write in networks and their interactions with other users leave a digital trace that is recorded. In order to understand what is going on in these virtual environments, it is necessary systems that collect, process, and analyze the information generated. The majority of existing tools analyze information related to an online event once it has finished or in a specific point of time (i.e., without considering an in-depth analysis of the evolution of users activity during the event). They focus on an analysis based on statistics about the quantity of information generated in an event. In this article, we present a multi-agent system that automates the process of gathering data from users activity in social networks and performs an in-depth analysis of the evolution of social behavior at different levels of granularity in online events based on network theory metrics. We evaluated its functionality analyzing users activity in events on Twitter.This work is partially supported by the PROME-TEOII/2013/019, TIN2014-55206-R, TIN2015-65515-C4-1-R, H2020-ICT-2015-688095.Del Val Noguera, E.; Martínez, C.; Botti, V. (2016). Analyzing Users' Activity in On-line Social Networks over Time through a Multi-Agent Framework. Soft Computing. 20(11):4331-4345. https://doi.org/10.1007/s00500-016-2301-0S433143452011Ahn Y-Y, Han S, Kwak H, Moon S, Jeong H (2007) Analysis of topological characteristics of huge online social networking services. In: Proceedings of the 16th WWW, pp 835–844Bastiaensens S, Vandebosch H, Poels K, Cleemput KV, DeSmet A, Bourdeaudhuij ID (2014) Cyberbullying on social network sites. an experimental study into behavioural intentions to help the victim or reinforce the bully. Comput Hum Behav 31:259–271Benevenuto F, Rodrigues T, Cha M, Almeida V (2009) Characterizing user behavior in online social networks. In: Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference. ACM, pp 49–62Borge-Holthoefer J, Rivero A, García I, Cauhé E, Ferrer A, Ferrer D, Francos D, Iñiguez D, Pérez MP, Ruiz G et al (2011) Structural and dynamical patterns on online social networks: the Spanish may 15th movement as a case study. PLoS One 6(8):e23883Borondo J, Morales AJ, Losada JC, Benito RM (2013) Characterizing and modeling an electoral campaign in the context of Twitter: 2011 Spanish presidential election as a case studyCatanese SA, De Meo P, Ferrara E, Fiumara G, Provetti A (2011) Crawling facebook for social network analysis purposes. In: Proceedings of the international conference on web intelligence, mining and semantics. ACM, p 52Cha M, Mislove A, Gummadi KP (2009) A measurement-driven analysis of information propagation in the flickr social network. In: Proceedings of the 18th international conference on World Wide Web. ACM, pp 721–730del Val E, Martínez C, Botti V (2015a) A multi-agent framework for the analysis of users behavior over time in on-line social networks. In: 10th International conference on soft computing models in industrial and environmental applications. Springer, Berlin, pp 191–201del Val E, Rebollo M, Botti V (2015b) Does the type of event influence how user interactions evolve on twitter? PLOS One 10(5):e0124049Eurostat (2016a) Internet use statistics—individuals. http://ec.europa.eu/eurostat/statistics-explained/index.php/Internet_use_statistics_-_individuals . Accessed 29 April 2016Eurostat (2016b) Social media—statistics on the use by enterprises. http://ec.europa.eu/eurostat/statistics-explained/index.php/Social_media_-_statistics_on_the_use_by_enterprises#Further_Eurostat_information . Accessed 29 April 2016García Fornes AM, Rodrigo Solaz M, Terrasa Barrena AM, Inglada J, Javier V, Jorge Cano J, Mulet Mengual L, Palomares Chust A, Búrdalo Rapa LA, Giret Boggino AS et al (2015) Magentix 2 user’s manualGolbeck J, Robles C, Turner K (2011) Predicting personality with social media. In: CHI’11, pp 253–262Guimerà R, Llorente A, Moro E, Sales-Pardo M (2012) Predicting human preferences using the block structure of complex social networks. PloS One 7(9):e44620Huberman BA, Romero DM, Wu F (2008) Social networks that matter: Twitter under the microscope. arXiv preprint arXiv:0812.1045Jamali M, Abolhassani H (2006) Different aspects of social network analysis. In: 2006 IEEE/WIC/ACM international conference on web intelligence (WI 2006 main conference proceedings)(WI’06). IEEE, pp 66–72Jiang Y, Jiang J (2014) Understanding social networks from a multiagent perspective. Parallel Distrib Syst IEEE Trans 25(10):2743–2759Kossinets G, Watts D (2006) Empirical analysis of an evolving social network. Science 311(5757):88–90Kumar R, Novak J, Tomkins A (2010) Structure and evolution of online social networks. In: Yu PS, Han J, Faloutsos C (eds) Link mining: models, algorithms, and applications. Springer, New York, pp 337–357Lazer D (2009) Life in the network: the coming age of computational social science. Science 323(5915):721–723Leskovec J, Adamic LA, Huberman BA (2007) The dynamics of viral marketing. ACM Trans Web 1(1):5Licoppe C, Smoreda Z (2005) Are social networks technologically embedded? How networks are changing today with changes in communication technology. Soc Netw 27(4):317–335Lotan G, Graeff E, Ananny M, Gaffney D, Pearce I, Boyd D (2011) The revolutions were tweeted: information flows during the 2011 tunisian and egyptian revolutions. Int J Commun 5:1375–1405Peña-López I, Congosto M, Aragón P (2013) Spanish indignados and the evolution of 15M: towards networked para-institutions. Big data: challenges and opportunities, pp 25–26Perliger A, Pedahzur A (2011) Social network analysis in the study of terrorism and political violence. PS Polit Sci Polit 44:45–50Romero DM, Galuba W, Asur S, Huberman BA (2011a) Influence and passivity in social media. In: Proceedings of the 20th WWW, pp 113–114Romero DM, Meeder B, Kleinberg J (2011b) Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on Twitter. In: Proceedings of the 20th WWW, pp 695–704Stockman FN, Doreian P, (1997) Evolution of social networks: processes and principles. In: Doreian P, Stokman FN (eds) Evolution of social networks. Routledge, London, pp 233–250Traud AL, Mucha PJ, Porter MA (2012) Social structure of facebook networks. Phys A Stat Mech Its Appl 391(16):4165–4180Ugander J, Karrer B, Backstrom L, Marlow C (2011) The anatomy of the Facebook social graph. arXiv preprint arXiv:1111.4503Valero S, del Val E, Alemany J, Botti V (2015) Using magentix2 in smart-home environments. In: 10th International conference on soft computing models in industrial and environmental applications. Springer, Berlin, pp 27–37Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, CambridgeWersm (2015) How much data is generated every minute on social media? http://wersm.com/how-much-data-is-generated-every-minute-on-social-media/ . Accessed 29 April 201
Correlated dynamics in egocentric communication networks
We investigate the communication sequences of millions of people through two
different channels and analyze the fine grained temporal structure of
correlated event trains induced by single individuals. By focusing on
correlations between the heterogeneous dynamics and the topology of egocentric
networks we find that the bursty trains usually evolve for pairs of individuals
rather than for the ego and his/her several neighbors thus burstiness is a
property of the links rather than of the nodes. We compare the directional
balance of calls and short messages within bursty trains to the average on the
actual link and show that for the trains of voice calls the imbalance is
significantly enhanced, while for short messages the balance within the trains
increases. These effects can be partly traced back to the technological
constrains (for short messages) and partly to the human behavioral features
(voice calls). We define a model that is able to reproduce the empirical
results and may help us to understand better the mechanisms driving technology
mediated human communication dynamics.Comment: 7 pages, 6 figure
Mapping the beach beneath the street:digital cartography for the playable city
Maps are an important component within many of the playful and gameful experiences designed to turn cities into a playable infrastructures. They take advantage of the fact that the technology used for obtaining accurate spatial information, such as GPS receivers and magnetometers (digital compasses), are now so wide-spread that they are considered as ‘standard’ sensors on mobile phones, which are themselves ubiquitous. Interactive digital maps, therefore, are are widely used by the general public for a variety of purposes. However, despite the rich design history of cartography digital maps typically exhibit a dominant aesthetic that has been de-signed to serve the usability and utility requirements of turn-by-turn urban navigation, which is itself driven by the proliferation of in-car and personal navigation services. The navigation aesthetic is now widespread across almost all spatial applications, even where a be-spoke cartographic product would be better suited. In this chapter we seek to challenge this by exploring novel neo-cartographic ap-proaches to making maps for use within playful and gameful experi-ences designed for the cities. We will examine the potential of de-sign approaches that can producte not only more aesthetically pleasing maps, but also offer the potential for influencing user be-haviour, which can be used to promote emotional engagement and exploration in playable city experiences
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Locative Media and Sociability:Using Location-Based Social Networks to Coordinate Everyday Life
Foursquare was a mobile social networking application that enabled people to share location with friends in the form of “check-ins.” The visualization of surrounding known social connections as well as unknown others has the potential to impact how people coordinate social encounters and forge new social ties. While many studies have explored mobile phones and sociability, there is a lack of empirical research examining location-based social network’s (LSBNs) from a sociability perspective. Drawing on a dataset of original qualitative research with a range of Foursquare users, the paper examines the application in the context of social coordination and sociability in three ways. First, the paper explores if Foursquare is used to organize certain social encounters, and if so, why. Second, the paper examines the visualization of surrounding social connections and whether this leads to “serendipitous encounters.” Lastly, the paper examines whether the use of Foursquare
can produce new social relationships
Toward an Identification of Resources Influencing Habitat Use in a Multi-Specific Context
Interactions between animal behaviour and the environment are both shaping observed habitat use. Despite the importance of inter-specific interactions on the habitat use performed by individuals, most previous analyses have focused on case studies of single species. By focusing on two sympatric populations of large herbivores with contrasting body size, we went one step beyond by studying variation in home range size and identifying the factors involved in such variation, to define how habitat features such as resource heterogeneity, resource quality, and openness created by hurricane or forest managers, and constraints may influence habitat use at the individual level. We found a large variability among individual's home range size in both species, particularly in summer. Season appeared as the most important factor accounting for observed variation in home range size. Regarding habitat features, we found that (i) the proportion of area damaged by the hurricane was the only habitat component that inversely influenced roe deer home range size, (ii) this habitat type also influenced both diurnal and nocturnal red deer home range sizes, (iii) home range size of red deer during the day was inversely influenced by the biomass of their preferred plants, as were both diurnal and nocturnal core areas of the red deer home range, and (iv) we do not find any effect of resource heterogeneity on home range size in any case. Our results suggest that a particular habitat type (i.e. areas damaged by hurricane) can be used by individuals of sympatric species because it brings both protected and dietary resources. Thus, it is necessary to maintain the openness of these areas and to keep animal density quite low as observed in these hunted populations to limit competition between these sympatric populations of herbivores
Mobile Phones and Social Signal Processing for Analysis and Understanding of Dyadic Conversations
Social Signal Processing is the domain aimed at bridging the social intelligence gap between humans and machines via modeling, analysis and synthesis of nonverbal behavior in social interactions. One of the main challenges of the domain is to sense unobtrusively the behavior of social interaction participants, one of the key conditions to preserve the spontaneity and naturalness of the interactions under exam. In this respect, mobile devices offer a major opportunity because they are equipped with a wide array of sensors that, while capturing the behavior of their users with an unprecedented depth, are still invisible. This is particularly important because mobile devices are part of the everyday life of a large number of individuals and, hence, they can be used to investigate and sense natural and spontaneous scenarios
Efeitos da terapia ultrassônica de baixa intensidade sobre o infarto agudo do miocárdio em ratos
Introdução. O infarto agudo do miocárdio (IAM) é considerado importante causa de morbidade e mortalidade no mundo e no Brasil. Novas intervenções terapêuticas estão sendo testadas isoladas ou em associação com as já existentes com o intuito de impedir a progressão ou atenuar o remodelamento no coração infartado. Dentre elas destaca-se a aplicação do Ultra-som (US) conjunto com agentes trombolíticos. Entretanto, na aplicação da energia ultrassônica como terapêutica pós-infarto é avaliado somente o seu possível efeito como agente trombolítico, não sendo investigado a sua possível implicação no processo de cicatrização da área infartada e parâmetros funcionais cardíacos. Objetivos. Diante dessas informações, nós objetivamos avaliar os efeitos da terapia ultrassônica transtorácica não-invasiva de baixa intensidade (NITUS) sobre a morfologia e função do músculo cardíaco de ratos infartados cirurgicamente após o 5° e 30° dia. Metodologia. Ratos machos Wistar (200-250g) foram pesados e divididos aleatoriamente em oito grupos com oito animais em cada grupo. Quatro grupos de animais foram submetidos à indução do IAM através da oclusão permanente da artéria coronária descendente anterior esquerda, sendo que dois destes grupos foram sacrificados no 5° dia após o IAM e as cinco aplicações da terapia ultrassônica e os outros dois grupos foram sacrificados no 30° dia após o IAM e as 5 aplicações da terapia ultrassônica. Quatro grupos de animais foram submetidos à cirurgia fictícia (Sham), sendo que dois destes grupos foram sacrificados no 5° dia após a cirurgia fictícia e as 5 aplicações da terapia ultrassônica e os outros dois grupos foram sacrificados no 30° dia após a cirurgia fictícia e as 5 aplicações da terapia ultrassônica. Os parâmetros da terapia ultrassônica foram freqüência de 1MHz, potência de 1W/cm2, modo pulsado e tempo de aplicação de 5 minutos. Para avaliação dos parâmetros funcionais foi realizado registros hemodinâmicos de todos os grupos e após a coleta dos registros os corações foram retirados para análise morfométrica a fim de avaliar a área da cicatriz do infarto. Os corações foram cortados em 4 fatias sendo retirados 3 cortes com espessura de 8 micrômetros da terceira fatia do ápice para a base, e estes foram corados com picrosírius. Foi utilizada uma câmera de vídeo para capturar uma área que contivesse todo o corte. A imagem era capturada com a utilização do programa AMCap e após a captura, esta era arquivada. A imagem arquivada era transferida para o programa ImageJ 1.42q/java no qual era marcada a área da cicatriz. De modo semelhante, era marcada toda a área da parede ventricular, para se obter a relação entre a área da cicatriz e a área total da parede ventricular. Resultados. No que concerne aos parâmetros hemodinâmicos, observamos que 30 dias após o IAM houve redução na pressão diastólica final (PDF) (mmHg) do grupo IAM+US quando comparado com grupo IAM (15±1.9 e 26±1.4; p<0.01 respectivamente). Não houve diferença significativa na área da cicatriz do infarto entre os grupos IAM e IAM+US no 5º. dia após infarto (31.6%±3.1% e 34.5%±1.6, respectivamente). Houve redução da área da cicatriz do infarto no grupo IAM+US quando comparado ao grupo IAM (21.5%±1.4% e 26.2%±1.7%; p<0.05, respectivamente) no 30º dia após IAM. Conclusão. A terapia com US dentro dos parâmetros estabelecidos, reduziu a área da cicatriz do infarto no grupo IAM+US (30 dias) bem como manteve a PDF dentro de valores fisiológicos, provavelmente por exercer influência nas fases inflamatória, proliferativa e de remodelamento, o que favorece um aumento na velocidade da resposta inflamatória por meio da mobilização de células inflamatórias como neutrófilos, macrófagos, ao mesmo tempo em que estimulou à degranulação dos mastócitos, bem como interferiu na mobilização leucocitária
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