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Journal: International Journal of Civil Engineering and Technology (IJCIET) (Vol.8, No. 2)

Publication Date:

Authors : ; ; ;

Page : 218-225

Keywords : Sentiment Analysis; Opinion Mining; Web mining; Text mining; Traffic Analysis.;

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In this paper, we have described system for mining opinions from traffic status tweets. The opinions are categorized as positive (p) and negative (n). We collected a corpus of around 5000 traffic related tweets using twitter API. These tweets were then cleansed from unwanted contents and processed. The processed tweets were converted into a bag of words and manually labeled as “p” or “n” appropriately. This labeled dataset was then split into training and test set in the ratio of 80:20. Various classifier algorithms were trained on this set and validated. Based on the performance of the algorithms the top 7 among them were chosen to form an ensemble model. This ensemble model was then used to classify the test set. We obtained an F-measure of 87.15 which indicates that our system is quite competitive in mining opinions about traffic status from tweets.

Last modified: 2017-05-19 18:12:32