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A Framework for Real-Time Sentiment Analysis of On-line Micro-texts with Sentiment Drift Detection Method
2017
International Journal of Software Engineering and Its Applications
Nowadays, the Twitter data streams have become most trusted on-line micro-texts (tweets) for sensing and monitoring the public opinion for any entity (event, topic or product). The real-time monitoring of Twitter data can be done by performing the realtime sentiment analysis of the tweets. However, unlike to the sentiment analysis of static textual data in which the aggregated sentiment score remains static, the aggregated sentiment score of Twitter data changes very frequently with the time.
doi:10.14257/ijseia.2017.11.1.07
fatcat:diyjokzwvvd4hdiooca64yepqq