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Methods and applications in social networks analysis : Evidence from Collaborative, Governance, Historical and Mobility Networks
| Methods and applications in social networks analysis : Evidence from Collaborative, Governance, Historical and Mobility Networks |
| Autore | Giordano Giuseppe |
| Pubbl/distr/stampa | Milan, : FrancoAngeli, 2021 |
| Descrizione fisica | 1 online resource (240 p.) |
| Collana | Computational Social Science |
| Soggetto topico | Social media / social networking |
| Soggetto non controllato | Network Analysis, social networks, computational social science, social interaction, information technologies |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Methods and applications in social networks analysis |
| Record Nr. | UNINA-9910548268903321 |
Giordano Giuseppe
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| Milan, : FrancoAngeli, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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New Frontiers in Textual Data Analysis / / edited by Giuseppe Giordano, Michelangelo Misuraca
| New Frontiers in Textual Data Analysis / / edited by Giuseppe Giordano, Michelangelo Misuraca |
| Autore | Giordano Giuseppe |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (385 pages) |
| Disciplina | 300.727 |
| Altri autori (Persone) | MisuracaMichelangelo |
| Collana | Studies in Classification, Data Analysis, and Knowledge Organization |
| Soggetto topico |
Social sciences - Statistical methods
Data mining Natural language processing (Computer science) Statistics Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Data Mining and Knowledge Discovery Natural Language Processing (NLP) Statistical Theory and Methods Statistics in Business, Management, Economics, Finance, Insurance |
| ISBN |
9783031559174
3031559177 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Statistical methods for Textual Data Analysis -- Statistical and deep learning methods for a linguistic and literary analysis -- Statistical profiling of Hybrid CNN-SVM effectiveness -- EMOtivo: a classifier for emotion detection of Italian texts trained on a self-labelled corpus -- Community detection and semantic analysis on Twitter. The case of No greenpass and No vax movement in Italy -- Evaluating customer satisfaction through Amazon reviews analysis: the Bluetooth earphones example -- Symmetric Non-Negative Matrix Factorization for analysing the scientific production on day surgery -- Social Media Effects on Sales: consumer sentiment in a state-space model -- Part II Advances in language processing -- Quality enhancements in experimental statistics: the Italian Social Mood on Economy Index -- A Strategy to Identify the Peculiarity of a Lexicon in the Analysis of a Corpus -- Neologisms and estrangement in a corpus of science-fiction -- Automatic retrieving ofderived Quechua verbs -- A Stylometric profile of Carmen Mola in the gender of ‘her’ authorial persona and the contribution of each author behind the pseudonym -- Automatic Genre Classification of Czech Texts Based on Syntactic Functions -- Deep learning as an aid to text mining in the choice of texts to lemmatise for a comparison corpus: a stylistic study of Peter Damian’s letters -- Dialogic Process Analysis in Natural Language Processing: an attempt to describe sense of reality and meaning of textdata -- Multi-channel Convolutional Transformer and intertextuality: a Latin case study -- Part III Emotional and Sentiment Analyses -- Opinion Mining Hybrid Approach. An application to investigate the users’ political positions in disinformative echo chambers -- Prediction of Italians’ sentiment during the first COVID-19 lockdown through a weighted random forest balanced with SMOTE algorithm -- Sentiment analysis on social network data: the Regional Index RETI -- Integrating text mining and hermeneutic analysis: the case of international volunteering biographies -- Emotional text mining and multilingual corpora: The analysis of #Covid-19 on Twitter -- Emotional Markers as Indicators of Investor Attitudes: EDA Sub - Process Proposal -- “The Spanish Model”: an analysis of Spanish culture in Organ Donation through the Emotional Text Mining -- Part IV Textual Data Analysis in action -- Comparative analysis of national reports: the case of the Erasmus+ ECOLHE Project -- Action Research in Psychology: the case of adoptive family -- Uncovering Uncertainty in Narrative Economics: A Semantic Search Approach -- Italian Institutional communication in pandemic period: a chronological analysis of Prime Minister speeches -- What about corruption? A text analytics method for a scoping literature review -- The stability of the discursive framework of the Ministry of Foreign Affairs tested by textometry -- Statistical analysis of textual data for longitudinal analysis. A studyon postgraduate course participants' reflections -- Third Mission & VQR 2015-2019: A Bigram’s Story. |
| Record Nr. | UNINA-9910887804103321 |
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Giordano Giuseppe
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical Models and Learning Methods for Complex Data / / edited by Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi
| Statistical Models and Learning Methods for Complex Data / / edited by Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi |
| Autore | Giordano Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (312 pages) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
La RoccaMichele
NiglioMarcella RestainoMarialuisa VichiMaurizio |
| Collana | Studies in Classification, Data Analysis, and Knowledge Organization |
| Soggetto topico |
Mathematical statistics - Data processing
Statistics Data mining Quantitative research Statistics and Computing Statistical Theory and Methods Applied Statistics Data Mining and Knowledge Discovery Data Analysis and Big Data |
| ISBN | 3-031-84702-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | - Exploring latent evolving ability in test equating and its effects on final rankings -- Hidden Markov and related discrete latent variable models An application to compositional data -- An application of Natural Language Processing Analysis on TripAdvisor Reviews -- Modelling football players field position via mixture of Gaussians with flexible weights -- Estimation Issues in Multivariate Panel Data -- Testing linearity in the single functional index model for dependent data -- A multi-step approach for streamflow classification -- Identification of misogynistic accounts on Twitter through Graph Convolutional Networks -- Topic modeling of publication activity in Hungary and Poland in the fields of economics, finance, and business -- Circular kernel classification with errors-in-variables -- Classification Trees Applied to Time Lagged Data to Improve Quality in Official Statistics -- Trimmed factorial k-means a clustering application to a cookies dataset_Farné and Camillo -- Visualization of Proximity and Role-based Embeddings in a Regional Labour Flow Network -- Bridging the Gap Investigating Correlation Clustering and Manifold Learning Connections -- Improving Performance in Neural Networks by Dendrite-Activated Connection -- Regression models with compositional regressors in case of structural zeros -- Multi-Dimensional Robinson Dissimilarities -- Composite selection criteria for the number of components of a finite mixture for ordinal data -- Clustering of Italian higher education institutions based on a destination–specific approach -- Analyzing Italian crime data using matrix-variate hidden Markov models. |
| Record Nr. | UNINA-9911031662903321 |
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Giordano Giuseppe
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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