IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v51y2017i5d10.1007_s11135-016-0395-1.html
   My bibliography  Save this article

Which factors affect the duration of hot topics on social media platforms?

Author

Listed:
  • Jinlou Zhao

    (Harbin Engineering University)

  • Hongyu Gao

    (Harbin Engineering University)

  • Yongli Li

    (Northeastern University)

  • Jiaguo Liu

    (Harbin Engineering University)

Abstract

Hot topics, as a common phenomenon on social media platform, play a major role in public opinion. This paper aims to discuss the issues about the duration of hot topics: which factors influence the duration of a hot topic on a social media platform? To answer this question, Cox regression model of survival analysis was introduced to make empirical analysis. The survey data containing 60 hot topics from 2011 to 2013 was collected from a popular social media platform of China. Besides, model verification is implemented to validate the adopted model and the calibrated parameters. As a result, this paper finds that the number of participants and opinion leaders have a significant positive influence on an incident’s duration, and official response times have a significant negative impact; whereas, the number of attending media has no significant impact. Furthermore, the prediction accuracy in the validation is up to 85 %, which implies that the obtained results would be robust. The established model and the designed empirical analysis are demonstrated to be adaptable to analyze the duration of hot topics, and three factors are found to effect the duration of a hot topic based on our collected dataset. Our analytic method could also be adopted in numerous problems related to the duration issues in the field of information management.

Suggested Citation

  • Jinlou Zhao & Hongyu Gao & Yongli Li & Jiaguo Liu, 2017. "Which factors affect the duration of hot topics on social media platforms?," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2395-2407, September.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0395-1
    DOI: 10.1007/s11135-016-0395-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-016-0395-1
    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/s11135-016-0395-1?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. Young Mee Shin & Seung Chang Lee & Bongsik Shin & Ho Geun Lee, 2010. "Examining influencing factors of post-adoption usage of mobile internet: Focus on the user perception of supplier-side attributes," Information Systems Frontiers, Springer, vol. 12(5), pages 595-606, November.
    2. Show-Ling Jang & Jennifer H. Chen, 2011. "What determines how long an innovative spell will last?," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 65-76, January.
    3. Hung-Pin Shih & Echo Huang, 2014. "Influences of Web interactivity and social identity and bonds on the quality of online discussion in a virtual community," Information Systems Frontiers, Springer, vol. 16(4), pages 627-641, September.
    4. Bo Wang & Shengbo Liu & Kun Ding & Zeyuan Liu & Jing Xu, 2014. "Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 685-704, October.
    5. Yue Wu & Yong Hu & Xiao-Hai He, 2013. "Public Opinion Formation Model Based On Opinion Entropy," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(11), pages 1-13.
    6. Yuen-Hsien Tseng & Yu-I Lin & Yi-Yang Lee & Wen-Chi Hung & Chun-Hsiang Lee, 2009. "A comparison of methods for detecting hot topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 73-90, October.
    7. Sujin Choi & Ji-young Park & Han Woo Park, 2012. "Using social media data to explore communication processes within South Korean online innovation communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 43-56, January.
    8. MinJae Lee & JinKyu Lee, 2012. "The impact of information security failure on customer behaviors: A study on a large-scale hacking incident on the internet," Information Systems Frontiers, Springer, vol. 14(2), pages 375-393, April.
    9. Bing Wu & Shan Jiang & Hsinchun Chen, 2015. "The impact of individual attributes on knowledge diffusion in web forums," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2221-2236, November.
    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. Yaxue Ma & Zhichao Ba & Yuxiang Zhao & Jin Mao & Gang Li, 2021. "Understanding and predicting the dissemination of scientific papers on social media: a two-step simultaneous equation modeling–artificial neural network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7051-7085, August.

    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. Kweku-Muata Osei-Bryson, 2015. "A hybrid decision support framework for generating & selecting causal explanatory regression splines models for information systems research," Information Systems Frontiers, Springer, vol. 17(4), pages 845-856, August.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    3. Shahla Ghobadi & John Campbell & Stewart Clegg, 2017. "Pair programming teams and high-quality knowledge sharing: A comparative study of coopetitive reward structures," Information Systems Frontiers, Springer, vol. 19(2), pages 397-409, April.
    4. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    5. Aladwani, Adel M. & Dwivedi, Yogesh K., 2018. "Towards a theory of SocioCitizenry: Quality anticipation, trust configuration, and approved adaptation of governmental social media," International Journal of Information Management, Elsevier, vol. 43(C), pages 261-272.
    6. Hong Joo Lee & Hoyeon Oh, 2020. "A Study on the Deduction and Diffusion of Promising Artificial Intelligence Technology for Sustainable Industrial Development," Sustainability, MDPI, vol. 12(14), pages 1-15, July.
    7. Antonio Fernández-Cano & Manuel Torralbo & Mónica Vallejo, 2012. "Time series of scientific growth in Spanish doctoral theses (1848–2009)," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 15-36, April.
    8. Jae Kyu Lee & Younghoon Chang & Hun Yeong Kwon & Beopyeon Kim, 2020. "Reconciliation of Privacy with Preventive Cybersecurity: The Bright Internet Approach," Information Systems Frontiers, Springer, vol. 22(1), pages 45-57, February.
    9. Li, Jingjing & Zhang, Yumei & Man, Jiayu & Zhou, Yun & Wu, Xiaojun, 2017. "SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 740-749.
    10. Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
    11. Kim Holmberg & Mike Thelwall, 2014. "Disciplinary differences in Twitter scholarly communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1027-1042, November.
    12. Mutlu Yuksel Avcilar & Akin Alkevli, 2017. "The Antecedents of Mobile Repurchasing Intentions: An Empirical Investigation among Turkish Mobile Shoppers," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(3), pages 105-105, February.
    13. Panigrahi, Ritanjali & Srivastava, Praveen Ranjan & Sharma, Dheeraj, 2018. "Online learning: Adoption, continuance, and learning outcome—A review of literature," International Journal of Information Management, Elsevier, vol. 43(C), pages 1-14.
    14. Heeyong Noh & Sungjoo Lee, 2019. "Where technology transfer research originated and where it is going: a quantitative analysis of literature published between 1980 and 2015," The Journal of Technology Transfer, Springer, vol. 44(3), pages 700-740, June.
    15. A. F. Salam & Hua Dai & Lei Wang, 2022. "Online Users’ Identity Theft and Coping Strategies, Attribution and Sense of Urgency: A Non-Linear Quadratic Effect Assessment," Information Systems Frontiers, Springer, vol. 24(6), pages 1929-1948, December.
    16. Jun Gao & Xiang Yu, 2022. "Factors Affecting the Evolution of Technical Cooperation among “Belt and Road Initiative” Countries Based on TERGMs and ERGMs," Sustainability, MDPI, vol. 14(3), pages 1-16, February.
    17. Han Woo Park, 2014. "Mapping election campaigns through negative entropy: Triple and Quadruple Helix approach to South Korea’s 2012 presidential election," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 187-197, April.
    18. Chung, Jaemin & Ko, Namuk & Kim, Hyeonsu & Yoon, Janghyeok, 2021. "Inventor profile mining approach for prospective human resource scouting," Journal of Informetrics, Elsevier, vol. 15(1).
    19. Yawen Qin & Xiaozhen Qin & Haohui Chen & Xun Li & Wei Lang, 2021. "Measuring cognitive proximity using semantic analysis: A case study of China's ICT industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6059-6084, July.
    20. Juan Máñez & María Rochina-Barrachina & Amparo Sanchis-Llopis & Juan Sanchis-Llopis, 2015. "The determinants of R&D persistence in SMEs," Small Business Economics, Springer, vol. 44(3), pages 505-528, March.

    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:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0395-1. 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.