Abstract
The news article manifests different issues of public domain. The news article are organized in different sections like local, national, international, sports, politics, editorial, readers view, sports etc. This paper purposes to categorize positive, negative and neutral local news and later on prediction of sensitivity from negative local news articles. The purpose of sensitivity analysis of negative local news articles is to set priority of action to be taken by the local administration. The sensitive news discusses the issues or event of urgent in nature, which need sudden intervention. The experiment is carried out basing on odia Syntactosemantic knowledge for categorization of 1000 local Odia news article and for sensitivity analysis tf and tf-idf score is calculated using unigram and bigram representation of data at document level, tf and tf-idf vector is passed to SVM for result and the results are analyzed by calculating the accuracy and F1 score.
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