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On Addressing the Challenges of Complex Stochastic Games Using “Representative” Moves Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Sub-event Detection on Twitter Network

verfasst von : Chao Chen, Gabriel Terejanu

Erschienen in: Artificial Intelligence Applications and Innovations

Verlag: Springer International Publishing

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Abstract

This work addresses the online detection of sub-events using Twitter stream data. We formulate the process of sub-event identification as an outlier detection problem using three statistical methods: Kalman Filter, Gaussian Process, and Probabilistic Principal Component Analysis. These methods are used to construct the probability distribution of percentage change in the number of tweets. Outliers are identified as future observations that do not fit these predicted probability distributions. Five real-world case studies are investigated to test the effectiveness of the methods. Finally, we discuss the limitations of the proposed frame-work and provide future directions for improvement.

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Vorheriges Kapitel Spam Filtering in Social Networks Using Regularized Deep Neural Networks with Ensemble Learning
Nächstes Kapitel Ontology-Based Spatial Pattern Recognition in Diagrams
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Metadaten
Titel
Sub-event Detection on Twitter Network
verfasst von
Chao Chen
Gabriel Terejanu
Copyright-Jahr
2018
Buch
Artificial Intelligence Applications and Innovations

Print ISBN: 978-3-319-92006-1

Electronic ISBN: 978-3-319-92007-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-92007-8_5