Large-Scale Sentiment Analysis for News and Blogs

A method for determining a sentiment associated with an entity Background: Sentiment analysis of natural language texts is a large and growing field. Some methods for generating sentiment lexicons assume positive and negative sentiment using synonyms and antonyms. Such methods may not accurately capture the sentiment of a word. Other methods use semantics, such as "and" and "but", or tone/orientation to determine a sentiment of a word, but such methods may have low accuracy. Current methods for analyzing sentiment treat only single complete documents, for example, to determine if a movie review is good or bad or quantify opinion from a product review. Therefore, there is a need for a method of generating a more accurate sentiment lexicon and for determining a sentiment over a plurality of texts. Technology Overview: This technology uses statistical analysis of text streams to simultaneously monitor changes in reputation to thousands of distinct news entries. Commercial applications of this technology include 1) market research - the technology can analyze the reputation of people, products, and companies without the need for expensive surveys or polling, 2) financial analysis - the conversion of news data to time-series facilitates automated investment analysis, e.g. strengthening pair trading investment strategies by identifying companies without the need for expensive surveys/polling, 2) internet search engines - augmenting results by providing sentiment data on articles. Advantages: Gives the ability to monitor entity sentiment as a time-series in any text stream, such as news or blogs, even if written in different languages and from different news sources. Applications: Commercial applications include:

- Market Research- This technology can analyze the reputation of people, products, and companies without the need for expensive surveys or polling

- Financial Analysis- The conversion of news data to time-series facilitates automated investment analysis

- Internet Search Engines- augmenting results by providing sentiment data on articles Intellectual Property Summary: Patented Stage of Development: 7,996,210 8,515,739 Licensing Potential: Licensing Licensing Status: Available for License. 7947 Additional Information: lexicon,quantify,market research,search engine,statistical,analysis tool,document analysis,market analysis,analysis software,data analysis,mathematical analysis,analytics system,analytics platform,analytics,analytics technology,online analytics,data analytics,analyze text,text analysis,natural language processing,language processing,document processing,electronic document,statistical analysis package,technical market research,methods,movie https://stonybrook.technologypublisher.com/files/sites/apoalnkqcczdegzwd345_network_visualisation_incorporating_sentiment_analysis_of_the_subreddit_'skeptic'_from_reddit.png Please note, header image is purely illustrative. Source: Siobhán Grayson, Wikimedia Commons, CC BY-SA 4.0.

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