IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v171y2021ics0040162521003723.html
   My bibliography  Save this article

News and user characteristics used by personalized algorithms: The case of Korea's news aggregators, Naver News and Kakao News

Author

Listed:
  • Kwak, Kyu Tae
  • Lee, Seung Yeop
  • Lee, Sang Woo

Abstract

Digital intermediaries, such as search engines and news aggregators, have recently implemented personalized algorithms as a method for recommending news articles to their users. This study is focused on Korea's representative news aggregators, Naver News and Kakao News, to discern differences between news characteristics when personalized algorithms are applied and when they are not, and analyze which user characteristics have an effect on the news articles recommended by personalized algorithms. The results are as follows. There was a difference in the topics of news articles selected when personalized algorithms were applied and when they were not, with articles selected by algorithms displaying a greater diversity of news sources. News articles selected by personalized algorithms included fewer articles with sizeable audience feedback, press endorsements, and recency. When selecting news articles, personalized algorithms were shown to be affected not only by the demographic characteristics of users but also by their political orientation and level of news consumption. In particular, users who consumed less news or had politically conservative tendencies were provided with news articles that were differentiated from the news articles of users who did not use personalized algorithms.

Suggested Citation

  • Kwak, Kyu Tae & Lee, Seung Yeop & Lee, Sang Woo, 2021. "News and user characteristics used by personalized algorithms: The case of Korea's news aggregators, Naver News and Kakao News," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:tefoso:v:171:y:2021:i:c:s0040162521003723
    DOI: 10.1016/j.techfore.2021.120940
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521003723
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2021.120940?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. Tien T. Nguyen & F. Maxwell Harper & Loren Terveen & Joseph A. Konstan, 2018. "User Personality and User Satisfaction with Recommender Systems," Information Systems Frontiers, Springer, vol. 20(6), pages 1173-1189, December.
    2. Kyu Tae Kwak & Seong Choul Hong & Sang Woo Lee, 2018. "An Analysis of a Repetitive News Display Phenomenon in the Digital News Ecosystem," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
    3. Wonchan Choi & Besiki Stvilia, 2015. "Web credibility assessment: Conceptualization, operationalization, variability, and models," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2399-2414, December.
    4. Chang, Yu-Ting & Yu, Hueiju & Lu, Hsi-Peng, 2015. "Persuasive messages, popularity cohesion, and message diffusion in social media marketing," Journal of Business Research, Elsevier, vol. 68(4), pages 777-782.
    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. Betty Purwandari & Latifatul Khairiyah & Mardiana Purwaningsih & Achmad Nizar Hidayanto & Nur Fitriah Ayuning Budi & Kongkiti Phusavat, 2023. "Why do people donate online? A perspective from dual credibility transfer," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 20(2), pages 393-425, June.
    2. Jingjing Wu & Yiwei Chen & Lin Hu & Anxin Xu, 2022. "Influence Factors on Consumers’ Instant Cross-buying under Supermarkets’ Cross-border Integration: From the Perspective of the Elaboration Likelihood Model," SAGE Open, , vol. 12(3), pages 21582440221, September.
    3. Lianne Foti & Lance Warwick & Eric Lyons & Sonia Dhaliwal & Michael Alcorn, 2023. "Knowledge Transfer and Innovation: Universities as Catalysts for Sustainable Decision Making in Industry," Sustainability, MDPI, vol. 15(14), pages 1-11, July.
    4. Hu, Miao & Chen, Jie & Chen, Qimei & He, Wei, 2020. "It pays off to be authentic: An examination of direct versus indirect brand mentions on social media," Journal of Business Research, Elsevier, vol. 117(C), pages 19-28.
    5. Tsung-Hung Lee & Fen-Hauh Jan, 2022. "Development and Validation of the Smart Tourism Experience Scale," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    6. Yazan Alshamaila & Ibrahim Aljarah & Ala’ M. Al-Zoubi, 2018. "Explaining Individuals’ Usage of Social Commerce: A Data Mining Approach," Modern Applied Science, Canadian Center of Science and Education, vol. 12(8), pages 116-116, August.
    7. Hajer Kefi & Sitesh Indra & Talel Abdessalem, 2016. "Social media marketing analytics : a multicultural approach applied to the beauty & cosmetic sector," Post-Print hal-01456580, HAL.
    8. Sheng, Jie, 2019. "Being Active in Online Communications: Firm Responsiveness and Customer Engagement Behaviour," Journal of Interactive Marketing, Elsevier, vol. 46(C), pages 40-51.
    9. Wonchan Choi, 2020. "Older adultsʼ credibility assessment of online health information: An exploratory study using an extended typology of web credibility," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(11), pages 1295-1307, November.
    10. Ryan, James Christopher, 2016. "Old knowledge for new impacts: Equity theory and workforce nationalization," Journal of Business Research, Elsevier, vol. 69(5), pages 1587-1592.
    11. Eryarsoy, Enes & Delen, Dursun & Davazdahemami, Behrooz & Topuz, Kazim, 2021. "A novel diffusion-based model for estimating cases, and fatalities in epidemics: The case of COVID-19," Journal of Business Research, Elsevier, vol. 124(C), pages 163-178.
    12. Huan-Ming Chuang & Chien-I Chen, 2023. "The Role of Two-Way Influences on Sustaining Green Brand Engagement and Loyalty in Social Media," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    13. Narjes Vara & Mahdieh Mirzabeigi & Hajar Sotudeh & Seyed Mostafa Fakhrahmad, 2022. "Application of k-means clustering algorithm to improve effectiveness of the results recommended by journal recommender system," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3237-3252, June.
    14. Ethan, Amelia, 2023. "The Effects of Social Media Marketing on Customer’s Purchase Intention; a Moderated Mediation Model from Apparel Industry of Pakistan," OSF Preprints 4dv2s, Center for Open Science.
    15. Montathar Faraon & Agnieszka Jaff & Liegi Paschoalini Nepomuceno & Victor Villavicencio, 2020. "Fake News and Aggregated Credibility: Conceptualizing a Co-Creative Medium for Evaluation of Sources Online," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 11(4), pages 93-117, October.
    16. Min Ho Ryu & Jieun Park & Kyu Tae Kwak, 2020. "Joint Ventures between Online Portals and News Publishers: Will they be an Alternative to Symbiosis?," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    17. Sabih Ahmad Khan & Hsien-Tsung Chang, 2019. "Comparative analysis on Facebook post interaction using DNN, ELM and LSTM," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-26, November.
    18. Saeed Pahlevan Sharif & Paolo Mura, 2019. "Narratives on Facebook: the impact of user-generated content on visiting attitudes, visiting intention and perceptions of destination risk," Information Technology & Tourism, Springer, vol. 21(2), pages 139-163, June.
    19. Han Zheng & Dion Hoe‐Lian Goh & Edmund Wei Jian Lee & Chei Sian Lee & Yin‐Leng Theng, 2022. "Understanding the effects of message cues on COVID‐19 information sharing on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(6), pages 847-862, June.
    20. Xiongfei Cao & Ali Nawaz Khan & Ahsan Ali & Naseer Abbas Khan, 0. "Consequences of Cyberbullying and Social Overload while Using SNSs: A Study of Users’ Discontinuous Usage Behavior in SNSs," Information Systems Frontiers, Springer, vol. 0, pages 1-14.

    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:eee:tefoso:v:171:y:2021:i:c:s0040162521003723. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.