Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams

Khantil Patel; Orland Hoeber; Howard J. Hamilton

doi:10.1007/978-3-319-18356-5_17

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Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams

Khantil Patel Orland Hoeber Howard J. Hamilton

Year: 2015 Lecture notes in computer science Pages: 196-203 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-18356-5_17

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Keywords:

Computer science Sliding window protocol Anomaly detection Data stream mining Anomaly (physics) STREAMS Probabilistic logic Sentiment analysis Data mining Sensitivity (control systems) Window (computing) Artificial intelligence

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Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Spam and Phishing Detection

Physical Sciences → Computer Science → Information Systems

Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams

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