867 resultados para SOCIAL NETWORK ANALYSIS


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Dopo un’introduzione sull’economia nel mondo antico e nella Galilea, la tesi affronta una rappresentazione storica de “Il Mare di Galilea tra l’antichità e oggi” (cap. 3). Seguono i capitoli sulle “Tecniche e le attrezzature di pesca” (cap.4) e su “Città, villaggi e aree di pesca” (Cap. 5). Due capitoli riguardano più particolarmente l’attività economica in senso stretto: “L’organizzazione dell’attività” (cap. 6) e “Commercio ed esportazione” (cap. 7). Chiudono la tesi due capitoli di carattere più metodologico: una rappresentazione degli agenti sociali della pesca (“i pescatori”) condotta ispirandosi alla network Analysis e un’analisi antropologica del loro sistema di vita (capitolo finale).La tesi è basata essenzialmente su tre corpi di documentazione: papiri documentari, dati archeologici, fonti storiche e letterarie. Molti dei documenti reperiti, in lingua greca, non erano mai stati tradotti in lingue moderne.La tesi consta – oltre ai diversi capitoli – anche di un’appendice documentaria molto estesa

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Con l’evoluzione dei social network e degli strumenti del 2.0 (blog, wiki, forum), internet si avvia verso nuove forme di business cui artigiani e pmi possono sfruttare per nuove opportunità, unendo social network e e-commerce e capire come si è evoluto il processo di creazione e finanziamento di un prodotto. La tesi è un viaggio per scoprire quali sono queste nuove opportunità per chi pratica artigianato a livello locale, e come è cambiata la figura stessa dell’artigiano, tra questi un nuovo movimento chiamato makers, che sfruttano i nuovi strumenti, tra cui anche mezzi rivoluzionari come la stampante 3D ora accessibile a tutti per creare oggetti e nuove idee. Sarà necessario capire quali sono le vetrine online dove e come poter vendere i nostri prodotti e profilare attraverso una segmentazione l’utente medio che già utilizza il social-commerce. In seguito si tratta il caso empirico di una start-up italiana, Blomming, una dei primi a differenziarsi dagli altri marketplace più famosi come contenitore adatto ad artigiani, ma non solo. Si seguiranno le varie fasi di crescita da un’idea, introduzione nel mercato fino alla direzione a cui si sta avviando con le ultime novità effettuando un’analisi dei rischi. Infine per capire tendenze e storie di chi sta già usando queste piattaforme è stato necessario fare un profilo dell’artigiano fai-da-te medio intervistando, e successivamente creando grafici, 100 artigiani che già vendono online.

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Il presente progetto di tesi è stato sviluppato per presentare un esempio concreto di come sia possibile sfruttare le potenzialità ottenibili inserendo, all'interno di un sito web, il markup Open Graph Protocol per la definizione, tramite l’utilizzo di metadati, di concetti semanticamente ricchi e interpretabili dai principali Social Network ed integrando le Graph API Facebook per interrogare questi dati e sfruttarli per il funzionamento stesso del sito.

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La prima parte del documento contiene una breve introduzione al mondo mobile, cloud computing e social network. La seconda parte si concentra sulla progettazione di un'applicazione per i dispositivi mobili usando le tecnologie Facebook e Parse. Infine, viene implementata un'applicazione Android usando le techiche descritte in precedenza.

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Studio ed analisi delle principali tecniche in ambito di Social Data Analysis. Progettazione e Realizzazione di una soluzione software implementata con linguaggio Java in ambiente Eclipse. Il software realizzato permette di integrare differenti servizi di API REST, per l'estrazione di dati sociali da Twitter, la loro memorizzazione in un database non-relazionale (realizzato con MongoDB), e la loro gestione. Inoltre permette di effettuare operazioni di classificazione di topic, e di analizzare dati complessivi sulle collection di dati estratti. Infine permette di visualizzare un albero delle "ricondivisioni", partendo da singoli tweet selezionati, ed una mappa geo-localizzata, contenente gli utenti coinvolti nella catena di ricondivisioni, e i relativi archi di "retweet".

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Il progetto ArtMap! mette a disposizione un applicativo user, destinato agli utenti, che tramite una struttura a social network, propone una mappatura globale di street art. Viene messo a disposizione un archivio di informazioni, aggiornate direttamente dagli utenti, relative a opere ed artisti e la possibilità di creare itinerari personali. Inoltre, è stato sviluppato un applicativo di supporto per la convalidazione delle informazioni inserite dagli utenti, destinato ai gestori del database di informazioni.

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La Sentiment analysis, nata nell'ambito dell’informatica, è una delle aree di ricerca più attive nel campo dell’analisi del linguaggio naturale e si è diffusa ampiamente anche in altri rami scientifici come ad esempio le scienze sociali, l’economia e il marketing. L’enorme diffusione della sentiment analysis coincide con la crescita dei cosiddetti social media: siti di commercio e recensioni di prodotti, forum di discussione, blog, micro-blog e di vari social network. L'obiettivo del presente lavoro di tesi è stato quello di progettare un sistema di sentiment analysis in grado di rilevare e classificare le opinioni e i sentimenti espressi tramite chat dagli utenti della piattaforma di video streaming Twitch.tv. Per impostare ed organizzare il lavoro, giungendo quindi alla definizione del sistema che ci si è proposti di realizzare, sono stati utilizzati vari modelli di analisi in particolare le recurrent neural networks (RNNLM) e sistemi di word embedding (word2vec),nello specifico i Paragraph Vectors, applicandoli, dapprima, su dati etichettati in maniera automatica attraverso l'uso di emoticon e, successivamente, su dati etichettati a mano.

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This project is the third stage of a comparative research project, The New Baltic Barometer, which was carried out simultaneously with the "New Democracies Barometer" of the Paul Lazerfeld Society (Vienna) and The Russian Barometer. It studied the opinion and behaviour of the largest Baltic ethnic groups (Estonians, Latvians, Lithuanians). The main focus was on the attitudes of Baltic residents towards the changes in the economic and political system, attitudes towards political values, political trust, and attitudes to the Baltic countries joining the European Union. An analysis of macroeconomic indicators of the Baltic states made it possible to deduce the link between the country's economic development, and satisfaction with the political regime and attitudes towards democratic values. The study analysed the conditions for the democratisation of society, i.e. the development of culture and public opinion in the Baltic states. Attention was also paid to the development of a social network of individuals, showing the transition from informal networks to impersonal institutions. The group concluded that the participation of residents in formal organisations, NGOs in particular, considerably fosters political trust and also increases political efficacy. Participation in formal organisations also reduces the importance of esteem for an authoritarian leader.

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BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

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BACKGROUND: Pain is a common experience in later life. There is conflicting evidence of the prevalence, impact, and context of pain in older people. GPs are criticised for underestimating and under-treating pain. AIM: To assess the extent to which older people experience pain, and to explore relationships between self-reported pain and functional ability and depression. DESIGN OF STUDY: Secondary analysis of baseline data from a randomised controlled trial of health risk appraisal. SETTING: A total of 1090 community-dwelling non-disabled people aged 65 years and over were included in the study from three group practices in suburban London. METHOD: Main outcome measures were pain in the last 4 weeks and the impact of pain, measured using the 24-item Geriatric Pain Measure; depression symptoms captured using the 5-item Mental Health Inventory; social relationships measured using the 6-item Lubben Social Network Scale; Basic and Instrumental Activities of Daily Living and self-reported symptoms. RESULTS: Forty-five per cent of women and 34% of men reported pain in the previous 4 weeks. Pain experience appeared to be less in the 'oldest old': 27.5% of those aged 85 years and over reported pain compared with 38-53% of the 'younger old'. Those with arthritis were four times more likely to report pain. Pain had a profound impact on activities of daily living, but most of those reporting pain described their health as good or excellent. Although there was a significant association between the experience of pain and depressed mood, the majority of those reporting pain did not have depressed mood. CONCLUSION: A multidimensional approach to assessing pain is appropriate. Primary care practitioners should also assess the impact of pain on activities of daily living.

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Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

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BACKGROUND: Pain and depression are known to be associated in later life, and both have a negative effect on physical performance both separately and in combination. The nature of the relationships between pain intensity and depression in elderly persons experiencing pain is less clear. The objectives of this study were to explore which factors are associated with depressed mood in older people experiencing pain, and to test the hypothesis that older people experiencing pain are at risk of depressed mood according to the severity or frequency of their pain. In addition we explored whether other potentially modifiable factors might increase the risk of depressed mood in these persons. METHODS: The study is a secondary analysis of baseline data for four hundred and six community-dwelling non-disabled people aged 65 and over registered with three group practices in suburban London who had experienced pain in the past 4 weeks. Intensity and frequency of pain was measured using 24 item Geriatric Pain Measure (GPM) and the presence of depressive symptoms using the 5 item Mental Health Inventory. Risk for social isolation was measured using the 6 item Lubben Social Network scale and instrumental activities of daily living (IADL) were also measured. RESULTS: Overall 76 (19%) had depressed mood. Pain frequency and severity were not statistically significantly associated with depressed mood in this population. In multivariate analyses, significant predictors of the presence of depressive symptoms were difficulties with basic ADLs (OR 2.8, 95% CI 1.1.7.8), risk for social isolation (OR 4.1, 95% CI 1.8-9.3), and basic education only (OR 2.2, 95% CI 1.1-4.4). CONCLUSION: Older people experiencing pain are also likely to experience depression. Among those experiencing pain, social network and functional status seem to be more important predictors of depressive symptoms than the severity of pain. Further studies should evaluate whether improvement of social network and functional status might reduce depressive symptoms in older patients.

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Following the end of a half-century of Soviet occupation, Lithuania, like other former Soviet republics, has been in socio-economic disorder. Now that Lithuania is free, the system of social welfare is characterized by under-funded health services and pensions, and a large number of institutions. Semi-structured interviews were conducted with students and practitioners focusing on community development, using Lofland’s model of social setting analysis.Results indicate that the collaborative efforts successfully produced a revolutionary and successful social service program, a multi-generational living facility offering full-time social services to unwed mothers, infants, and elderly residents.This article is based upon the qualitative study of social work practitioners and social work students and chronicles the successes and difficulties encountered within the process of community development.