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
相关论文
共 50 条
  • [41] Social Sensing and Sentiment Analysis: Using Social Media as Useful Information Source
    Ducange, Pietro
    Fazzolari, Michela
    PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON SMART SYSTEMS AND TECHNOLOGIES (SST), 2017, : 301 - 306
  • [42] Sentiment analysis of vegan related tweets using mutual information for feature selection
    Shamoi, Elvina
    Turdybay, Akniyet
    Shamoi, Pakizar
    Akhmetov, Iskander
    Jaxylykova, Assel
    Pak, Alexandr
    PEERJ COMPUTER SCIENCE, 2022, 8
  • [43] Sentiment analysis based on probabilistic models using inter-sentence information
    Sadamitsu, Kugatsu
    Sekine, Satoshi
    Yamamoto, Mikio
    SIXTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, LREC 2008, 2008, : 2892 - 2896
  • [44] Optimized Sentiment Analysis Tool A sentiment analysis tool to study cognitive inclinations
    Sharma, Nayonika
    Sharma, Chetna
    Indu, S.
    Chugh, Priyanka
    PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT, 2016, : 2589 - 2592
  • [45] Sentiment Analysis Using Naive Bayes Algorithm With Case Study
    Akella, Jishnusri Ojaswy
    Akella, L. N. Yashaswy
    PROCEEDINGS OF THE 2018 3RD INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2018), 2018,
  • [46] Hydrogeochemical analysis of processes affecting HCH removal using ZVI-based treatment technology
    Nemecek, Jan
    Zeman, Josef
    Brucek, Petr
    Hrabak, Pavel
    Cernik, Miroslav
    APPLIED GEOCHEMISTRY, 2024, 175
  • [47] Numeric Rating of Apps on Google Play Store by Sentiment Analysis on User Reviews
    Islam, Mir Riyanul
    2014 1ST INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATION & COMMUNICATION TECHNOLOGY (ICEEICT 2014), 2014,
  • [48] AN ONLINE ADAPTIVE CLASSIFICATION OF GOOGLE TRENDS DATA ANOMALIES FOR INVESTOR SENTIMENT ANALYSIS
    Dere, Duygu
    Ergeneci, Mert
    Gokcesu, Kaan
    ECONOMICS, FINANCE AND STATISTICS, VOL 2, ISSUE 1, 2018, : 79 - 81
  • [49] ANALYSIS OF INFORMATION TECHNOLOGY AND COMMUNICATION IN THE CLASSROOM: A STUDY CASE
    Odete de Mattos, Maria
    Slowinska Milena, Ewelina
    Santos Gomez, Melody
    Martinez Romero, Natalia
    REVISTA IBERO-AMERICANA DE ESTUDOS EM EDUCACAO, 2012, 7 (02): : 43 - 57
  • [50] 360-MAM-Affect: Sentiment Analysis with the Google Prediction API and EmoSenticNet
    Mulholland, Eleanor
    Mc Kevitt, Paul
    Lunney, Tom
    Farren, John
    Wilson, Judy
    PROCEEDINGS OF THE 2015 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNOLOGIES FOR INTERACTIVE ENTERTAINMENT, 2015, : 217 - 221