The use of machine learning for correlation analysis of sentiment and weather data

Hu Li, Zahra Jadidi, Jinyan Chen, Jun Jo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The development of the Internet of Things (IoT) drives us to confront, manage and analyse massive and complicated data generated from various sensors. Also, social media have rapidly become very popular and can be considered as important source of data. Twitter on average generates about 6,000 tweets every second, which total to over 500 million tweets per day. Facebook has over 2 billion monthly active users. The individual posts may be trivial, however, the accumulated big data can provide diverse valuable information, which can be also correlated with IoT and enable human sentiment identification of the environment changes. This work proposes a machine learning model for correlation analysis and prediction of weather conditions and social media posts. In experimental evaluation we demonstrate that the Big Data analysis approach and machine learning techniques can be used to analyse and predict sentiment of different weather conditions.

Original languageEnglish
Title of host publicationRobot Intelligence Technology and Applications 5 - Results from the 5th International Conference on Robot Intelligence Technology and Applications
EditorsHyun Myung, Weiliang Xu, Jin-Woo Jung, Han-Lim Choi, Jong-Hwan Kim, Junmo Kim, Eric T Matson
PublisherSpringer-Verlag
Pages291-298
Number of pages8
ISBN (Print)9783319784519
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event5th International Conference on Robot Intelligence Technology and Applications, RiTA 2017 - Daejeon, Korea, Republic of
Duration: 13 Dec 201715 Dec 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume751
ISSN (Print)2194-5357

Conference

Conference5th International Conference on Robot Intelligence Technology and Applications, RiTA 2017
Country/TerritoryKorea, Republic of
CityDaejeon
Period13/12/1715/12/17

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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