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Lecturer(s)
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Matlach Vladimír, Mgr. Ph.D.
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Andres Jan, prof. RNDr. dr hab. DSc.
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Course content
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Multivariate analysis - Utilizing multiple quantified properties, pitfalls - Distances and similarities between objects - Visualizing and interpreting multivariate data, relationships between properties - Clustering methods, finding patterns and groups, describing and interpreting data - Application of methods in practice Data acquisition issues - Corpora, online databases, open datasets - Data retrieval from web resources: API access, REST, JSON, XML formats - Web-Scraping Text and multidimensional data - Application of quantitative linguistics to text description, edit distances, latent semantics - Classical methods of text modelling, their pitfalls and solutions - Applications of explicated multidimensional methods from clustering to visualizations - Application of methods in practice to authorship, language, similarity of works, use in sociology, anthropology, etc. Graph theory and social networks - Graph theory and applications to social and other networks, social network analysis (SNA) - Ways of extracting relationships from text: letters, books, manuscripts, ? - Social networks on the internet: discussion forums and others - data and relationship mining - Timeline and evolution of relationships - Gephi and Cytoscape tools - Applications in historiography, sociology, political science Introduction to geoinformation systems - Analysis of data related to areas - Methods of data visualisation
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Learning activities and teaching methods
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Lecture
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Learning outcomes
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The aim of the course is to develop the knowledge from the first two courses and to build on the R programming language to solve practical tasks, especially multidimensional data analysis. This course addresses how to compare the similarity of objects described by more than one property, clustering them by similarity, understanding the relationships of individual properties to each other, and their influence on group formation. Further, consideration is given to the meaningful visualization of such data and their interpretation using classical methods up to the state-of-the-art. This knowledge is further extended to graph theory, its visualization, applications to social networks and their extraction from various sources. This course provides deeper practical and theoretical skills.
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Prerequisites
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The lecture is just for PhD students.
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Assessment methods and criteria
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Oral exam
Completion of own and previously consulted project
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Recommended literature
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Hajičová, Panevová, Sgall. (2003). Úvod do teoretické a počítačové lingvistiky. Praha.
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Sells, P. (1985). Lectures on Contemporary Syntactic Theories. Stanford.
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Stockwell, R. M. (1977). Fundations of Syntactic Theory. New Persey.
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