IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v61y2010i1p190-199.html
   My bibliography  Save this article

Data mining emotion in social network communication: Gender differences in MySpace

Author

Listed:
  • Mike Thelwall
  • David Wilkinson
  • Sukhvinder Uppal

Abstract

No abstract is available for this item.

Suggested Citation

  • Mike Thelwall & David Wilkinson & Sukhvinder Uppal, 2010. "Data mining emotion in social network communication: Gender differences in MySpace," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(1), pages 190-199, January.
    • Handle: RePEc:bla:jinfst:v:61:y:2010:i:1:p:190-199
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Roser Beneito-Montagut, 2017. "Emotions, Everyday Life, and the Social Web: Age, Gender, and Social Web Engagement Effects on Online Emotional Expression," Sociological Research Online, , vol. 22(4), pages 87-104, December.
    2. Jacqueline Ng Lane & Bruce Ankenman & Seyed Iravani, 2018. "Insight into Gender Differences in Higher Education: Evidence from Peer Reviews in an Introductory STEM Course," Service Science, INFORMS, vol. 10(4), pages 442-456, December.
    3. Julia Neidhardt & Nataliia Rümmele & Hannes Werthner, 2017. "Predicting happiness: user interactions and sentiment analysis in an online travel forum," Information Technology & Tourism, Springer, vol. 17(1), pages 101-119, March.
    4. Chen, Aihui & Lu, Yaobin & Wang, Bin & Zhao, Ling & Li, Ming, 2013. "What drives content creation behavior on SNSs? A commitment perspective," Journal of Business Research, Elsevier, vol. 66(12), pages 2529-2535.
    5. 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.
    6. Tian Tian & Stijn Speelman, 2021. "Pursuing Development behind Heterogeneous Ideologies: Review of Six Evolving Themes and Narratives of Rural Planning in China," Sustainability, MDPI, vol. 13(17), pages 1-16, September.
    7. Ibtesam AbdulAziz Bajri & Nada Abdulmajeed Lashkar, 2020. "Saudi Gender Emotional Expressions in Using Instagram," English Language Teaching, Canadian Center of Science and Education, vol. 13(5), pages 1-94, May.
    8. F. Schweitzer & D. Garcia, 2010. "An agent-based model of collective emotions in online communities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 533-545, October.
    9. Chmiel, Anna & Sobkowicz, Pawel & Sienkiewicz, Julian & Paltoglou, Georgios & Buckley, Kevan & Thelwall, Mike & Hołyst, Janusz A., 2011. "Negative emotions boost user activity at BBC forum," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2936-2944.
    10. Yulei Gavin Zhang & Mandy Yan Dang & Hsinchun Chen, 2020. "An Explorative Study on the Virtual World: Investigating the Avatar Gender and Avatar Age Differences in their Social Interactions for Help-Seeking," Information Systems Frontiers, Springer, vol. 22(4), pages 911-925, August.
    11. Avi Rosenfeld & Sigal Sina & David Sarne & Or Avidov & Sarit Kraus, 2018. "WhatsApp usage patterns and prediction of demographic characteristics without access to message content," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(22), pages 647-670.
    12. Julia Neidhardt & Nataliia Rümmele & Hannes Werthner, 0. "Predicting happiness: user interactions and sentiment analysis in an online travel forum," Information Technology & Tourism, Springer, vol. 0, pages 1-19.
    13. Li, Xianghua & Wang, Zhen & Gao, Chao & Shi, Lei, 2017. "Reasoning human emotional responses from large-scale social and public media," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 182-193.
    14. Gohar Feroz Khan, 2013. "Social media-based systems: an emerging area of information systems research and practice," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 159-180, April.
    15. Anupriya Khan & Satish Krishnan & Jithesh Arayankalam, 2022. "The Role of ICT Laws and National Culture in Determining ICT Diffusion and Well-Being: A Cross-Country Examination," Information Systems Frontiers, Springer, vol. 24(2), pages 415-440, April.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jinfst:v:61:y:2010:i:1:p:190-199. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    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.