Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams
- 29 April 2015
- book chapter
- Published by Springer Science and Business Media LLC
Abstract
No abstract availableKeywords
This publication has 8 references indexed in Scilit:
- Research issues in outlier detection for data streamsACM SIGKDD Explorations Newsletter, 2014
- Outlier Detection for Temporal Data: A SurveyIEEE Transactions on Knowledge and Data Engineering, 2013
- On-line relevant anomaly detection in the Twitter streamPublished by Association for Computing Machinery (ACM) ,2013
- Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the medianJournal of Experimental Social Psychology, 2013
- Probabilistic reasoning for streaming anomaly detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- TwitinfoPublished by Association for Computing Machinery (ACM) ,2011
- Online outlier detection for data streamsPublished by Association for Computing Machinery (ACM) ,2011
- Sentiment Knowledge Discovery in Twitter Streaming DataLecture Notes in Computer Science, 2010