IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v21y2019i5d10.1007_s10796-018-9824-0.html
   My bibliography  Save this article

The Impact of Emotion: A Blended Model to Estimate Influence on Social Media

Author

Listed:
  • Wei-Lun Chang

    (Tamkang University)

Abstract

The goal of this research is to devise a model of social influence with sentiment analysis and help organization discover real influential people on social media. This study takes into account the quality of post and sentiment ratio simultaneously. We discovered the meaning of sentiment behind post, retweet, and reply is more important than numbers. This research selected four targets (two politicians and two celebrities) on Twitter to examine the proposed model. The results revealed the sentiment ratio of celebrities is higher than politicians. The reason may be the celebrities posted random issues in daily life and followers all supported them. However, the politicians’ tweets are easy to provoke a conflict which may cause emotional expressions from fans or followers. Sentiment analysis can adjust numbers based on the insights of content. We also provided the h-index to identify high impact of posted topics. The results showed various topics have different impact according to h-index. In summary, the proposed model can appropriately estimate the influence of a person in social media and assist firms allocate marketing resources efficiently.

Suggested Citation

  • Wei-Lun Chang, 2019. "The Impact of Emotion: A Blended Model to Estimate Influence on Social Media," Information Systems Frontiers, Springer, vol. 21(5), pages 1137-1151, October.
    • Handle: RePEc:spr:infosf:v:21:y:2019:i:5:d:10.1007_s10796-018-9824-0
    DOI: 10.1007/s10796-018-9824-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-018-9824-0
    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/s10796-018-9824-0?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. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    2. Younggue Bae & Hongchul Lee, 2012. "Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2521-2535, December.
    3. Younggue Bae & Hongchul Lee, 2012. "Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2521-2535, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Mohammadreza Mousavizadeh & Mehrdad Koohikamali & Mohammad Salehan & Dam J. Kim, 2022. "An Investigation of Peripheral and Central Cues of Online Customer Review Voting and Helpfulness through the Lens of Elaboration Likelihood Model," Information Systems Frontiers, Springer, vol. 24(1), pages 211-231, February.
    2. Haiman Tian & Shu-Ching Chen & Mei-Ling Shyu, 0. "Evolutionary Programming Based Deep Learning Feature Selection and Network Construction for Visual Data Classification," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
    3. Haiman Tian & Shu-Ching Chen & Mei-Ling Shyu, 2020. "Evolutionary Programming Based Deep Learning Feature Selection and Network Construction for Visual Data Classification," Information Systems Frontiers, Springer, vol. 22(5), pages 1053-1066, October.
    4. Jyoti Choudrie & Shruti Patil & Ketan Kotecha & Nikhil Matta & Ilias Pappas, 2021. "Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study," Information Systems Frontiers, Springer, vol. 23(6), pages 1431-1465, December.
    5. Yu Lehe & Gui Zhengxiu, 2021. "Analysis of Enterprise Social Media Intelligence Acquisition Based on Data Crawler Technology," Entrepreneurship Research Journal, De Gruyter, vol. 11(2), pages 3-23, April.

    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. Martin Quinn & Theodore Lynn & Stephen Jollands & Binesh Nair, 2016. "Domestic Water Charges in Ireland - Issues and Challenges Conveyed through Social Media," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3577-3591, August.
    2. Joaquin Sanchez & Carmen Abril & Michael Haenlein, 2020. "Competitive spillover elasticities of electronic word of mouth: an application to the soft drink industry," Journal of the Academy of Marketing Science, Springer, vol. 48(2), pages 270-287, March.
    3. Topaloglu, Omer & Dass, Mayukh & Kumar, Piyush, 2017. "Does who we are affect what we say and when? Investigating the impact of activity and connectivity on microbloggers' response to new products," Journal of Business Research, Elsevier, vol. 77(C), pages 23-29.
    4. Rowe, Francisco & Mahony, Michael & Graells-Garrido, Eduardo & Rango, Marzia & Sievers, Niklas, 2021. "Using Twitter to Track Immigration Sentiment During Early Stages of the COVID-19 Pandemic," SocArXiv pc3za, Center for Open Science.
    5. Vîiu, Gabriel-Alexandru, 2016. "A theoretical evaluation of Hirsch-type bibliometric indicators confronted with extreme self-citation," Journal of Informetrics, Elsevier, vol. 10(2), pages 552-566.
    6. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    7. Aurelia Magdalena Pisoschi & Claudia Gabriela Pisoschi, 2016. "Is open access the solution to increase the impact of scientific journals?," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1075-1095, November.
    8. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    9. Kaur, Jasleen & Radicchi, Filippo & Menczer, Filippo, 2013. "Universality of scholarly impact metrics," Journal of Informetrics, Elsevier, vol. 7(4), pages 924-932.
    10. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    11. R. Karpagam & S. Gopalakrishnan & M. Natarajan & B. Ramesh Babu, 2011. "Mapping of nanoscience and nanotechnology research in India: a scientometric analysis, 1990–2009," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 501-522, November.
    12. David L. Anderson & John Tressler, 2013. "The Relevance of the “h-” and “g-” Index to Economics in the Context of A Nation-Wide Research Evaluation Scheme: The New Zealand Case," Economic Papers, The Economic Society of Australia, vol. 32(1), pages 81-94, March.
    13. Ash Mohammad Abbas, 2011. "Weighted indices for evaluating the quality of research with multiple authorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 107-131, July.
    14. Michael Zhang, 2021. "Announcement of Retraction," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(12), pages 1-14, December.
    15. Richard S. J. Tol, 2009. "The h-index and its alternatives: An application to the 100 most prolific economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(2), pages 317-324, August.
    16. Soutar, Geoffrey N. & Murphy, Jamie, 2009. "Journal quality: A Google Scholar analysis," Australasian marketing journal, Elsevier, vol. 17(3), pages 150-153.
    17. Thor, Andreas & Marx, Werner & Leydesdorff, Loet & Bornmann, Lutz, 2016. "Introducing CitedReferencesExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardization," Journal of Informetrics, Elsevier, vol. 10(2), pages 503-515.
    18. Fan Li & Hao Zhou & De-Sheng Huang & Peng Guan, 2020. "Global Research Output and Theme Trends on Climate Change and Infectious Diseases: A Restrospective Bibliometric and Co-Word Biclustering Investigation of Papers Indexed in PubMed (1999–2018)," IJERPH, MDPI, vol. 17(14), pages 1-14, July.
    19. Perc, Matjaž, 2010. "Zipf’s law and log-normal distributions in measures of scientific output across fields and institutions: 40 years of Slovenia’s research as an example," Journal of Informetrics, Elsevier, vol. 4(3), pages 358-364.
    20. Nadeem Shafique Butt & Ahmad Azam Malik & Muhammad Qaiser Shahbaz, 2021. "Bibliometric Analysis of Statistics Journals Indexed in Web of Science Under Emerging Source Citation Index," SAGE Open, , vol. 11(1), pages 21582440209, January.

    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:infosf:v:21:y:2019:i:5:d:10.1007_s10796-018-9824-0. 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.