Cantitate/Preț
Produs

Applications of Social Media and Social Network Analysis: Lecture Notes in Social Networks

Editat de Przemysław Kazienko, Nitesh Chawla
en Limba Engleză Hardback – 10 iun 2015
This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to communities of open source software developers, biometric template generation as well as analysis of user behavior within heterogeneous environments of cultural educational centers. Addressing these challenging applications is what makes this edited volume of interest to researchers and students focused on social media and social network analysis.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 64350 lei  6-8 săpt.
  Springer International Publishing – 13 oct 2016 64350 lei  6-8 săpt.
Hardback (1) 64975 lei  6-8 săpt.
  Springer International Publishing – 10 iun 2015 64975 lei  6-8 săpt.

Din seria Lecture Notes in Social Networks

Preț: 64975 lei

Preț vechi: 81219 lei
-20% Nou

Puncte Express: 975

Preț estimativ în valută:
12439 12979$ 10427£

Carte tipărită la comandă

Livrare economică 13-27 martie

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319190020
ISBN-10: 3319190024
Pagini: 240
Ilustrații: XIII, 240 p. 123 illus., 37 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.54 kg
Ediția:2015
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes in Social Networks

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

A Node-Centric Reputation Computation Algorithm on Online Social Networks.- Measuring Centralities for Transportation Networks Beyond Structures.- Indifferent Attachment: The Role of Degree in Ranking Friends.- Analyzing the Social Networks of Contributors in Open Source Software Community.- Precise Modeling Rumor Propagation and Control Strategy on Social Networks.- Studying Graph Dynamics Through Intrinsic Time Based Diffusion Analysis.- A Learning Based Approach for Real-time Emotion Classification of Tweets.- A New Linguistic Approach to Assess the Opinion of Users in Social Network Environments.- Visual Analysis of Topical Evolution in Unstructured Text: Design and Evaluation of TopicFlow.- Explaining Scientic and Technical Emergence Forecasting.- Combining Social, Audiovisual and Experiment Content for Enhanced Cultural Experiences.- Social Network Analysis for Biometric Template Protection.

Textul de pe ultima copertă

This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to communities of open source software developers, biometric template generation as well as analysis of user behavior within heterogeneous environments of cultural educational centers. Addressing these challenging applications is what makes this edited volume of interest to researchers and students focused on social media and social network analysis.

Caracteristici

Includes a number of real-world application of methodologies developed for social network analysis Covers application of various analytical methods to social media data Demonstrates applicability of static, dynamic and real time approaches Includes supplementary material: sn.pub/extras