IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v22y2022i5d10.1007_s12351-022-00714-0.html
   My bibliography  Save this article

Unsupervised consumer intention and sentiment mining from microblogging data as a business intelligence tool

Author

Listed:
  • Symeon Symeonidis

    (Democritus University of Thrace)

  • Georgios Peikos

    (University of Milano-Bicocca)

  • Avi Arampatzis

    (Democritus University of Thrace)

Abstract

The present study aims to create a framework that analyses user posts related to a product of interest on social networking platforms. More precisely, by applying information mining techniques, posts are categorised according to the intention they express, the sentiment polarisation, and the type of opinion. The model operates based on linguistic rules, machine learning, and combinations. Six different methodologies are implemented to extract intent, sentiment, and type of opinion from a tweet. The final model automatically detects intention to buy or not to buy the product, intention to compare the product with other competitors, and finally, intention to search for information about the product. It then categorises the text according to the sentiment and depending on their expressed opinion. The dataset comprises tweets for each day of the iPhone 5’s life cycle, corresponding to 365 days. Additionally, it demonstrated that the business’s external or internal decisions affect the public purchasing audience’s opinions, sentiments, and intentions expressed on social media. Lastly, as a Business Intelligence tool, the framework recognises and analyses these points, which contribute substantially to the company’s decision-making through the findings.

Suggested Citation

  • Symeon Symeonidis & Georgios Peikos & Avi Arampatzis, 2022. "Unsupervised consumer intention and sentiment mining from microblogging data as a business intelligence tool," Operational Research, Springer, vol. 22(5), pages 6007-6036, November.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:5:d:10.1007_s12351-022-00714-0
    DOI: 10.1007/s12351-022-00714-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-022-00714-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12351-022-00714-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhiqiang (Eric) Zheng & Peter Fader & Balaji Padmanabhan, 2012. "From Business Intelligence to Competitive Intelligence: Inferring Competitive Measures Using Augmented Site-Centric Data," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 698-720, September.
    2. Xu, Xun & Wang, Xuequn & Li, Yibai & Haghighi, Mohammad, 2017. "Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors," International Journal of Information Management, Elsevier, vol. 37(6), pages 673-683.
    3. Wang, Le & Yan, Jie & Lin, Jun & Cui, Wentian, 2017. "Let the users tell the truth: Self-disclosure intention and self-disclosure honesty in mobile social networking," International Journal of Information Management, Elsevier, vol. 37(1), pages 1428-1440.
    4. Smith, Andrew N. & Fischer, Eileen & Yongjian, Chen, 2012. "How Does Brand-related User-generated Content Differ across YouTube, Facebook, and Twitter?," Journal of Interactive Marketing, Elsevier, vol. 26(2), pages 102-113.
    5. Wolfgang Becker & Oliver Schmid, 2020. "The right digital strategy for your business: an empirical analysis of the design and implementation of digital strategies in SMEs and LSEs," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 985-1005, November.
    6. Faulds, David J. & Mangold, W. Glynn & Raju, P.S. & Valsalan, Sarath, 2018. "The mobile shopping revolution: Redefining the consumer decision process," Business Horizons, Elsevier, vol. 61(2), pages 323-338.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhao, Lu & Zhang, Mingli & Tu, Jianbo & Li, Jialing & Zhang, Yan, 2023. "Can users embed their user experience in user-generated images? Evidence from JD.com," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    2. Diwanji, Vaibhav S. & Cortese, Juliann, 2020. "Contrasting user generated videos versus brand generated videos in ecommerce," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    3. Wang, Le & Luo, Xin (Robert) & Li, Han, 2022. "Envy or conformity? An empirical investigation of peer influence on the purchase of non-functional items in mobile free-to-play games," Journal of Business Research, Elsevier, vol. 147(C), pages 308-324.
    4. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    5. Yadav, Manjit S. & de Valck, Kristine & Hennig-Thurau, Thorsten & Hoffman, Donna L. & Spann, Martin, 2013. "Social Commerce: A Contingency Framework for Assessing Marketing Potential," Journal of Interactive Marketing, Elsevier, vol. 27(4), pages 311-323.
    6. Rikhardsson, Pall & Yigitbasioglu, Ogan, 2018. "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 37-58.
    7. M. S. Balaji & Subhash Jha & Marla B. Royne, 2015. "Customer e-complaining behaviours using social media," The Service Industries Journal, Taylor & Francis Journals, vol. 35(11-12), pages 633-654, August.
    8. Hong-Wen Lin & Ya-Cing Jhan & Yuan Tseng, 2019. "Behavioral intention of using one-stop mobile application: evidence from department stores," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 9(12), pages 401-412, December.
    9. Agrawal, Shiv Ratan & Mittal, Divya, 2022. "Optimizing customer engagement content strategy in retail and E-tail: Available on online product review videos," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    10. Pauwels, Koen & Aksehirli, Zeynep & Lackman, Andrew, 2016. "Like the ad or the brand? Marketing stimulates different electronic word-of-mouth content to drive online and offline performance," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 639-655.
    11. Saito, Taiga & Takahashi, Akihiko & Koide, Noriaki & Ichifuji, Yu, 2019. "Application of online booking data to hotel revenue management," International Journal of Information Management, Elsevier, vol. 46(C), pages 37-53.
    12. Ivanete Schneider Hahn & Flavia Luciane Scherer & Kenny Basso & Marindia Brachak dos Santos, 2016. "Consumer Trust in and Emotional Response to Advertisements on Social Media and their Influence on Brand Evaluation," Brazilian Business Review, Fucape Business School, vol. 13(4), pages 49-71, July.
    13. Divakaran, Pradeep Kumar Ponnamma & Xiong, Jie, 2022. "Eliciting brand association networks: A new method using online community data," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    14. Baccarella, Christian V. & Wagner, Timm F. & Kietzmann, Jan H. & McCarthy, Ian P., 2018. "Social media? It's serious! Understanding the dark side of social media," European Management Journal, Elsevier, vol. 36(4), pages 431-438.
    15. N. Serdar Sever & Goknil Nur Sever & Salar Kuhzady, 2015. "The Evaluation of Potentials of Gamification in Tourism Marketing Communication," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 5(10), pages 188-202, October.
    16. Hofman-Kohlmeyer Magdalena, 2021. "Brand-Related User-Generated Content in Simulation Video Games: Qualitative Research Among Polish Players," Journal of Management and Business Administration. Central Europe, Sciendo, vol. 29(1), pages 61-87, March.
    17. Maria Antonietta Raimondo & Stefania Farace & Gaetano Nino Miceli, 2018. "User-Generated Systems of Signs and Meanings in Product Customization: Taxonomies and Research Directions," MERCATI & COMPETITIVIT?, FrancoAngeli Editore, vol. 2018(2), pages 61-83.
    18. He, Yi & Chen, Qimei & Lee, Ruby P. & Wang, Yonggui & Pohlmann, Attila, 2017. "Consumers' Role Performance and Brand Identification: Evidence from a Survey and a Longitudinal Field Experiment," Journal of Interactive Marketing, Elsevier, vol. 38(C), pages 1-11.
    19. V. Kumar & Alok R. Saboo & Amit Agarwal & Binay Kumar, 2020. "Generating Competitive Intelligence with Limited Information: A Case of the Multimedia Industry," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 192-213, January.
    20. Kawaf, Fatema & Istanbulluoglu, Doga, 2019. "Online fashion shopping paradox: The role of customer reviews and facebook marketing," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 144-153.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:operea:v:22:y:2022:i:5:d:10.1007_s12351-022-00714-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.