MOA-TweetReader: Real-time analysis in twitter streaming data

Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Twitter is a micro-blogging service built to discover what is happening at any moment in time, anywhere in the world. Twitter messages are short, generated constantly, and well suited for knowledge discovery using data stream mining. We introduce MOA-TweetReader, a system for processing tweets in real time. We show two main applications of the new system for studying Twitter data: detecting changes in term frequencies and performing real-time sentiment analysis.

Original languageEnglish
Title of host publicationDiscovery Science - 14th International Conference, DS 2011, Proceedings
Pages46-60
Number of pages15
DOIs
Publication statusPublished - 17 Oct 2011
Externally publishedYes
Event14th International Conference on Discovery Science, DS 2011, Co-located with the 22nd International Conference on Algorithmic Learning Theory, ALT 2011 - Espoo, Finland
Duration: 5 Oct 20117 Oct 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6926 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Discovery Science, DS 2011, Co-located with the 22nd International Conference on Algorithmic Learning Theory, ALT 2011
Country/TerritoryFinland
CityEspoo
Period5/10/117/10/11

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