Analysis processes treatment study information in sentiment analysis using technology Google

被引:0
|
作者
Quintana Gomez, Angel [1 ]
机构
[1] Univ Atlantic Medio, Grad Comunicac, Gran Canaria, Spain
来源
VIVAT ACADEMIA | 2021年 / 154期
关键词
API Natural Language; Big Query; Crawler; Google Cloud Platform; Google Data Prep; Google Data Studio; Sentiment Analyses; Twitter;
D O I
10.15178/va.2021.154.e1336
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
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.
引用
收藏
页数:15
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