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Topic Detection and Classification in Social Networks: The Twitter Case de Dimitrios Milioris

Topic Detection and Classification in Social Networks: The Twitter Case

Autor Dimitrios Milioris
en Limba Engleză Hardback – 13 oct 2017
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.
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Specificații

ISBN-13: 9783319664132
ISBN-10: 3319664131
Pagini: 105
Ilustrații: XVI, 105 p. 38 illus., 25 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.35 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Cuprins

Introduction.- Background and Related Work.- Joint Sequence Complexity.- Text Classification via Compressive Sensing.- Extension of Joint Complexity and Compressive Sensing.- Conclusion.

Notă biografică

Dr. Dimitrios Milioris is a research associate and lecturer at the Massachusetts Institute of Technology (MIT). He received his Ph.D. from École Polytechnique Paris (2015, honors) while a scholar at Columbia University, New York, USA, as an Alliance Program awardee (2013 – 2014). He received his double M.Sc. degree (2011, first in class, honors) in computer science & applied mathematics from Paris XI University and the École Polytechnique, and his B.Sc. degree (2009, honors) in computer science from the University of Crete, Greece. Prior to joining MIT, he was a researcher at Bell Labs, Alcatel-Lucent in Paris, France, and a member of the Mathematics of Dynamic & Complex Networks Department. Prior to joining Bell Labs, he served as a research assistant at the Institute of Computer Science (ICS) of the Foundation for Research and Technology Hellas (FO.R.T.H.), and as a research engineer with the Hipercom Team at the National Institute for Research in Computer Science and Automatic Control (I.N.R.I.A.), followed by a compulsory military service in Telecommunications Division.

Textul de pe ultima copertă

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.

Caracteristici

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