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Journal Article
Real Time Text AnalysisPublished in IOP Publishing
2017
Volume: 263
This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language
Topics: Sentiment analysis (54)%54% related to the paper, WordNet (52)%52% related to the paper and Data model (50)%50% related to the paper
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Content may be subject to copyright.This is an author-created, un-copyedited version of an article accepted for publication/published in IOP Conference Seri... ...This is an author-created, un-copyedited version of an article accepted for publication/published in IOP Conference Series: Materials Science and Engineering. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/1757-899X/263/4/042005
About the journal
| Journal | Data powered by TypesetIOP Conference Series: Materials Science and Engineering |
|---|---|
| Publisher | Data powered by TypesetIOP Publishing |
| ISSN | 1757-8981 |
| Open Access | 0 |
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