Portland, OR -- (SBWire) -- 11/02/2017 --Customer satisfaction plays a decisive role in the success of a company. Recent years have witnessed a steady growth in the adoption of tools to analyze consumer's opinions, sentiments, emotions, and evaluations about products, organizations, services, and other aspects and attributes. Sentiment analysis, also called opinion mining, is gaining traction as it aids in extracting vital information and acts as a powerful tool for competitive and market analysis. Sentiment analytic tools use advanced technologies such as Natural Language Processing (NLP) along with data mining and text mining to determine the meaning and context of the words used. The tools then analyze the nature, i.e. positive, negative, or neutral.
Social media greatly influences consumer's choice, preferences, and their decision-making. Product reviews, feedbacks, and complaints posted on the web, assist the buyers while investing their money in the best available products. Every negative comment adversely affects the organization's popularity and its brand value. Every company, irrespective of the type of products or services they offer and the size of the organization, benefits from the adoption of sentiment analytics. These tools help the organization to cater to the demands of the consumers by taking into account their evaluations and responses. In the media and entertainment industry, huge sums are invested to study the patterns of viewers, based on historical data as well as real-time data. On microblogging sites, these tools help to categorize the large volumes of data, structured and unstructured, block redundant data, and analyze the latest trends. Research Beam added a detailed report titled, "Global Sentiment Analytics Market Size, Status, and Forecast 2022", that provides a comprehensive analysis of the key market trends, top impacting factors, and market segmentation. The leading players in the global sentiment analytics market include Angoss Sentiment Corporation, Clarabridge, IBM, SAS Institute, Aylien, Bottlenose.com, Crowdflower, Brandwatch, Twizoo, and Adoreboard among others.
Google Cloud's Natural Language API gets Sentiment Analysis upgrade
In September 2017, Google Cloud released two crucial updates for its Natural Language API. The latest updates include content classification and entity sentiment analysis. The content classification feature enables organizations to sort the wide array of content into different categories, such as healthcare, law, entertainment, and others, based on their common attributes. A total of 700 categories are made available for document classification. Unlike the conventional sentiment analysis performed on sentences or paragraphs, the latest upgrade enables a deeper granular analysis and assists in identifying the sentiment and emotional connect related to specific words. These updates are beneficial for brands and media companies, as they capture and extract useful feedback and opinions regarding their products and services.
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Box launches AI-based Box Skills powered by IBM Watson
Box, leading cloud storage company, recently launched Box Skills and "Box Skills Kit" for developers. The new product is powered by IBM Watson, Google Cloud, and Microsoft Azure. The framework allows users to apply features such as sentiment analysis and natural language processing to the content stored in The Box platform. The sentiment analysis services will be used to tag conversations and texts, thus aiding in the identification of various types of emotions such as anger, agreeableness, and frustration.
Novel Tools and Features Drive the Growth of Global Sentiment Analytics Market
The research offers introduction of the global Sentiment Analytics market in terms of its scope. It incorporates research methodology to analyze competitive spirit among manufacturers.