Analysis processes treatment study information in sentiment analysis using technology Google
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Abstract
In recent years, Big Data has made its way amongst the main market analysis tools, linking itself to machine learning techniques in order to learn about the data owned. One of the fastest growing areas is natural language processing, which provides the researcher with data on text structures and meanings. In order to deep in into this area, Google has created the natural language API, allowing researchers to work with different aspects of language functions, including sentiment analysis, providing information on the predominant emotional response to a previously selected content, and allowing it to obtain a score that analyzes the valence of emotions with dichotomous values. The object of this study is to analyze the different processes that a researcher has to use to obtain useful information for their research. From the extraction of information to obtaining data that helps the researcher to draw conclusions, a long process of information processing is developed. The study will show us how the various tools available to Google on its own Google Cloud Platform provide a researcher with the necessary support for the development of their work, once the information to be analyzed is already available. In addition, it will be complemented with tracking tools to extract the desired text, depending on where it is.
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