IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v6y2014i3p457-481d39185.html
   My bibliography  Save this article

Should I Care about Your Opinion? Detection of Opinion Interestingness and Dynamics in Social Media

Author

Listed:
  • Diana Maynard

    (Department of Computer Science, University of Sheffield, 211 Portobello, Sheffield, S1 4DP, UK)

  • Gerhard Gossen

    (Leibniz Universität Hannover, Forschungszentrum L3S, Appelstrasse 9a, 30169 Hannover, Germany)

  • Adam Funk

    (Department of Computer Science, University of Sheffield, 211 Portobello, Sheffield, S1 4DP, UK)

  • Marco Fisichella

    (Leibniz Universität Hannover, Forschungszentrum L3S, Appelstrasse 9a, 30169 Hannover, Germany)

Abstract

In this paper, we describe a set of reusable text processing components for extracting opinionated information from social media, rating it for interestingness, and for detecting opinion events. We have developed applications in GATE to extract named entities, terms and events and to detect opinions about them, which are then used as the starting point for opinion event detection. The opinions are then aggregated over larger sections of text, to give some overall sentiment about topics and documents, and also some degree of information about interestingness based on opinion diversity. We go beyond traditional opinion mining techniques in a number of ways: by focusing on specific opinion-target extraction related to key terms and events, by examining and dealing with a number of specific linguistic phenomena, by analysing and visualising opinion dynamics over time, and by aggregating the opinions in different ways for a more flexible view of the information contained in the documents.

Suggested Citation

  • Diana Maynard & Gerhard Gossen & Adam Funk & Marco Fisichella, 2014. "Should I Care about Your Opinion? Detection of Opinion Interestingness and Dynamics in Social Media," Future Internet, MDPI, vol. 6(3), pages 1-25, August.
  • Handle: RePEc:gam:jftint:v:6:y:2014:i:3:p:457-481:d:39185
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/6/3/457/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/6/3/457/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mike Thelwall & Kevan Buckley & Georgios Paltoglou, 2011. "Sentiment in Twitter events," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 406-418, February.
    2. Mike Thelwall & Kevan Buckley & Georgios Paltoglou, 2011. "Sentiment in Twitter events," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 406-418, February.
    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. Ma, Jie & Tse, Ying Kei & Wang, Xiaojun & Zhang, Minhao, 2019. "Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 192-205.
    2. Luis-Millán González & José Devís-Devís & Maite Pellicer-Chenoll & Miquel Pans & Alberto Pardo-Ibañez & Xavier García-Massó & Fernanda Peset & Fernanda Garzón-Farinós & Víctor Pérez-Samaniego, 2021. "The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis," IJERPH, MDPI, vol. 18(9), pages 1-20, April.
    3. Karin Sim Smith & Richard McCreadie & Craig Macdonald & Iadh Ounis, 2018. "Regional Sentiment Bias in Social Media Reporting During Crises," Information Systems Frontiers, Springer, vol. 20(5), pages 1013-1025, October.
    4. Beatriz Barros & Ana Fernández-Zubieta & Raul Fidalgo-Merino & Francisco Triguero, 2018. "Scientific knowledge percolation process and social impact: A case study on the biotechnology and microbiology perceptions on Twitter," Science and Public Policy, Oxford University Press, vol. 45(6), pages 804-814.
    5. Lipizzi, Carlo & Iandoli, Luca & Ramirez Marquez, José Emmanuel, 2015. "Extracting and evaluating conversational patterns in social media: A socio-semantic analysis of customers’ reactions to the launch of new products using Twitter streams," International Journal of Information Management, Elsevier, vol. 35(4), pages 490-503.
    6. Thomas T. Hills & Eugenio Proto & Daniel Sgroi & Chanuki Illushka Seresinhe, 2019. "Historical analysis of national subjective wellbeing using millions of digitized books," Nature Human Behaviour, Nature, vol. 3(12), pages 1271-1275, December.
    7. Ping-Yu Hsu & Hong-Tsuen Lei & Shih-Hsiang Huang & Teng Hao Liao & Yao-Chung Lo & Chin-Chun Lo, 2019. "Effects of sentiment on recommendations in social network," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 253-262, June.
    8. Widmar, Nicole Olynk & Bir, Courtney & Clifford, McKenna & Slipchenko, Natalya, 2020. "Social media sentimentas an additional performance measure? Examples from iconic theme park destinations," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    9. Stefan Stieglitz & Christian Meske & Björn Ross & Milad Mirbabaie, 2020. "Going Back in Time to Predict the Future - The Complex Role of the Data Collection Period in Social Media Analytics," Information Systems Frontiers, Springer, vol. 22(2), pages 395-409, April.
    10. Neu, Dean & Saxton, Greg & Rahaman, Abu & Everett, Jeffery, 2019. "Twitter and social accountability: Reactions to the Panama Papers," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 61(C), pages 38-53.
    11. Dhiraj Murthy, 2017. "Comparative Process-oriented Research Using Social Media and Historical Text," Sociological Research Online, , vol. 22(4), pages 3-26, December.
    12. Herbst, Chris M. & Desouza, Kevin C. & Alashri, Saud & Kandala, Srinivasa Srivatsav & Khullar, Mayank & Bajaj, Vikash, 2018. "What Do Parents Value in a Child Care Provider? Evidence from Yelp Consumer Reviews," IZA Discussion Papers 11741, Institute of Labor Economics (IZA).
    13. Dibya Nandan Mishra & Rajeev Kumar Panda, 2023. "Decoding customer experiences in rail transport service: application of hybrid sentiment analysis," Public Transport, Springer, vol. 15(1), pages 31-60, March.
    14. Zavala, Araceli & Ramirez-Marquez, Jose Emmanuel, 2019. "Visual analytics for identifying product disruptions and effects via social media," International Journal of Production Economics, Elsevier, vol. 208(C), pages 544-559.
    15. Mohammad Masoud Rahimi & Elham Naghizade & Mark Stevenson & Stephan Winter, 2023. "SentiHawkes: a sentiment-aware Hawkes point process to model service quality of public transport using Twitter data," Public Transport, Springer, vol. 15(2), pages 343-376, June.
    16. Simone Pizzi & Sara Moggi & Fabio Caputo & Pierfelice Rosato, 2021. "Social media as stakeholder engagement tool: CSR communication failure in the oil and gas sector," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(2), pages 849-859, March.
    17. Wu He & Xin Tian & Andy Hung & Vasudeva Akula & Weidong Zhang, 2018. "Measuring and comparing service quality metrics through social media analytics: a case study," Information Systems and e-Business Management, Springer, vol. 16(3), pages 579-600, August.
    18. Liwen Vaughan, 2016. "Uncovering information from social media hyperlinks: An investigation of twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1105-1120, May.
    19. Sashittal, Hemant C. & Hodis, Monica & Sriramachandramurthy, Rajendran, 2015. "Entifying your brand among Twitter-using millennials," Business Horizons, Elsevier, vol. 58(3), pages 325-333.
    20. Ana Condeço-Melhorado & Inmaculada Mohino & Borja Moya-Gómez & Juan Carlos García-Palomares, 2020. "The Rio Olympic Games: A Look into City Dynamics through the Lens of Twitter Data," Sustainability, MDPI, vol. 12(17), pages 1-16, August.

    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:gam:jftint:v:6:y:2014:i:3:p:457-481:d:39185. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.