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Twitter Sentiment Analysis of New IKEA Stores Using Machine Learning
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2018 (English)In: International Conference on Computer and Applications, July 25th-26th, 2018, Beirut, Lebanon, 2018Conference paper, Published paper (Refereed)
Abstract [en]

This paper studied public emotion and opinion concerning the opening of new IKEA stores, specifically, how much attention are attracted, how much positive and negative emotion are aroused, what IKEA-related topics are talked due to this event. Emotion is difficult to measure in retail due to data availability and limited quantitative tools. Twitter texts, written by the public to express their opinion concerning this event, are used as a suitable data source to implement sentiment analysis. Around IKEA opening days, local people post IKEA related tweets to express their emotion and opinions on that. Such “IKEA” contained tweets are collected for opinion mining in this work. To compute sentiment polarity of tweets, lexiconbased approach is used for English tweets, and machine learning methods for Swedish tweets. The conclusion is new IKEA store are paid much attention indicated by significant increasing tweets frequency, most of them are positive emotions, and four studied cities have different topics and interests related IKEA. This paper extends knowledge of consumption emotion studies of prepurchase, provide empirical analysis of IKEA entry effect on emotion. Moreover, it develops a Swedish sentiment prediction model, elastic net method, to compute Swedish tweets’ sentiment polarity which has been rarely conducted.  

Place, publisher, year, edition, pages
2018.
Keywords [en]
big-box effect, opinion analysis, customer emotion, elastic net model, text mining, natural language processing
National Category
Computer Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-27646OAI: oai:DiVA.org:du-27646DiVA, id: diva2:1204643
Conference
International Conference on Computer and Applications, July 25th-26th, 2018, Beirut, Lebanon
Available from: 2018-05-08 Created: 2018-05-08 Last updated: 2018-06-15Bibliographically approved

Open Access in DiVA

TwitterIkea(768 kB)49 downloads
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File name FULLTEXT01.pdfFile size 768 kBChecksum SHA-512
fe386b5f260e5e07da85b49d92dacf771e3eb7fc37c7fe9d78accf227f56a36a8e4aa3ff3c055a7c7bdb8f2c99eb07a1288282c14816dd2a121ff976eb5723ce
Type fulltextMimetype application/pdf

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Li, YujiaoFleyeh, Hasan

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf