Topic Detection and Classification in Social Networks

Beschreibung

This book provides a novel method for topic detection and classification in social networks. The book addresses several research and technical challenges that are currently being investigated by the research community, from the analysis of relations and communications between members of a community, to quality, authority, relevance and timeliness of the content, traffic prediction based on media consumption, spam detection, to security, privacy and protection of personal information. Furthermore, the book discusses innovative techniques to address those challenges and provides novel solutions based on information theory, sequence analysis and combinatorics, which are applied on real data obtained from Twitter.

Provides a language-agnostic method for social media text analysis, which is not based on a specific grammar, semantics or machine learning techniques

Detects topics from large text documents and extracts the main opinion without any human intervention

Compares a variety of techniques and provides a smooth transition from theory to practice with multiple experiments and results

Autor*in

Dimitrios Milioris

Themen in »Topic Detection and Classification in Social Networks«

Dynamic Social Networks Joint Sequence Complexity Joint Complexity Analytic Combinatorics Analytic Combinatorics Application in Social Networks Compressive Sensing Sparse Representation Kalman Filter Privacy in Social Networks Topic Detection Topic Detection in Social Networks Classification in Social Networks Automatic Classification of Topics Trend Sensing Analysis in Twitter

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