Статья

Twitter sentiment analysis on coronavirus: Machine learning approach

C. Machuca, C. Gallardo, R. Toasa,
2021

In machine learning, a fundamental challenge is the analysis of data to identify feelings using algorithms that allow us to determine the positive or negative emotions that people have regarding a topic. Social networks and microblogging are a valuable source of information, being mostly used to express personal points of view and thoughts. Based on this knowledge we propose a sentiment analysis of English tweets during the pandemic COVID-19 in 2020. The tweets were classified as positive or negative by applying the Logistic Regression algorithm, using this method we got a classification accuracy of 78.5%.

Цитирование

Похожие публикации

Документы

Источник

Версии

  • 1. Version of Record от 2021-03-04

Метаданные

Об авторах
  • C. Machuca
    Tomsk Polytechnic University
  • C. Gallardo
    Tomsk Polytechnic University
  • R. Toasa
    Universidad Israel
Название журнала
  • Journal of Physics: Conference Series
Том
  • 1828
Выпуск
  • 1
Номер гранта
  • undefined
Тип документа
  • journal article
Тип лицензии Creative Commons
  • CC BY
Правовой статус документа
  • Свободная лицензия
Источник
  • scopus