News articles have always been a prominent force in the formation of a company's financial image in the minds of the general public, especially the investors. Given the large amount of news being generated these days through various websites, it is possible to mine the general sentiment of a particular company being portrayed by media agencies over a period of time, which can be utilized to gauge the long term impact on the investment potential of the company. However, given such a vast amount of news data, we need to first separate corporate news from other kinds namely, sports, entertainment, science & technology, etc. We propose a system which takes news as, checks whether it is of corporate nature, and then identifies the polarity of the sentiment expressed in the news. The system is also capable of distinguishing the company/organization which is the subject of the news from other organizations which find mention, and this is used to pair the sentiment polarity with the identified company.
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