IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v143y2019icp114-124.html
   My bibliography  Save this article

Technology news and their linkage to production of knowledge in robotics research

Author

Listed:
  • Mejía, Cristian
  • Kajikawa, Yuya

Abstract

Robotics is a growing academic field that has received extensive social attention, where both promising and contested opinions can be found with regard to its applications. To understand commonalities and differences between social expectations and academic research, we analyzed the relationship between sentiment polarity appearing in news articles and topical coverage of academic publications. We found that news discourse is shifting from a prevailing positive view towards a more neutral stance in recent years. However, the sentiment and levels of attention vary widely depending on the specific topic being covered. When topics in the news are compared to those in academic articles, news coverage leans towards applied academic research. Also, highly similar topics in both news and academic publishing tend to appear earlier as a social discussion when expressing a positive sentiment. We discuss these findings in the contexts of science communication and transdisciplinary research.

Suggested Citation

  • Mejía, Cristian & Kajikawa, Yuya, 2019. "Technology news and their linkage to production of knowledge in robotics research," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 114-124.
  • Handle: RePEc:eee:tefoso:v:143:y:2019:i:c:p:114-124
    DOI: 10.1016/j.techfore.2019.03.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162518312575
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2019.03.016?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. Petersen, Alan, 2001. "Biofantasies: genetics and medicine in the print news media," Social Science & Medicine, Elsevier, vol. 52(8), pages 1255-1268, April.
    2. Jahn, Thomas & Bergmann, Matthias & Keil, Florian, 2012. "Transdisciplinarity: Between mainstreaming and marginalization," Ecological Economics, Elsevier, vol. 79(C), pages 1-10.
    3. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    4. Jun, Seung-Pyo, 2012. "A comparative study of hype cycles among actors within the socio-technical system: With a focus on the case study of hybrid cars," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1413-1430.
    5. Jacques Marescaux & Joel Leroy & Michel Gagner & Francesco Rubino & Didier Mutter & Michel Vix & Steven E. Butner & Michelle K. Smith, 2001. "Transatlantic robot-assisted telesurgery," Nature, Nature, vol. 413(6854), pages 379-380, September.
    6. Kayser, Victoria & Blind, Knut, 2017. "Extending the knowledge base of foresight: The contribution of text mining," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 208-215.
    7. Richard Klavans & Kevin W. Boyack, 2017. "Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 984-998, April.
    8. Zhengyin Hu & Shu Fang & Tian Liang, 2014. "Empirical study of constructing a knowledge organization system of patent documents using topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 787-799, September.
    9. Meppem, Tony, 2000. "The discursive community: evolving institutional structures for planning sustainability," Ecological Economics, Elsevier, vol. 34(1), pages 47-61, July.
    10. Kayser, Victoria, 2017. "Comparing public and scientific discourse in the context of innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 348-357.
    11. van Lente, Harro & Spitters, Charlotte & Peine, Alexander, 2013. "Comparing technological hype cycles: Towards a theory," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1615-1628.
    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. Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2020. "Knowledge, robots and productivity in SMEs: Explaining the second digital wave," Journal of Business Research, Elsevier, vol. 108(C), pages 119-131.
    2. Weiss, Daniel & Nemeczek, Fabian, 2021. "A text-based monitoring tool for the legitimacy and guidance of technological innovation systems," Technology in Society, Elsevier, vol. 66(C).
    3. Hung, Shih-Chang & Chang, Shu-Chen, 2023. "Framing the virus: The political, economic, biomedical and social understandings of the COVID-19 in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Jon Ander Garibi & Alvaro Antón & José Domingo Villarroel, 2021. "Information about Human Evolution: An Analysis of News Published in Communication Media in Spanish between 2015 and 2017," Publications, MDPI, vol. 9(3), pages 1-10, July.
    5. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    6. Dhar, Suparna & Tarafdar, Pratik & Bose, Indranil, 2022. "Understanding the evolution of an emerging technological paradigm and its impact: The case of Digital Twin," Technological Forecasting and Social Change, Elsevier, vol. 185(C).

    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. White, Gareth R.T. & Samuel, Anthony, 2019. "Programmatic Advertising: Forewarning and avoiding hype-cycle failure," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 157-168.
    2. Kriechbaum, Michael & López Prol, Javier & Posch, Alfred, 2018. "Looking back at the future: Dynamics of collective expectations about photovoltaic technology in Germany & Spain," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 76-87.
    3. Dhar, Suparna & Tarafdar, Pratik & Bose, Indranil, 2022. "Understanding the evolution of an emerging technological paradigm and its impact: The case of Digital Twin," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    4. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
    5. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    6. Kriechbaum, Michael & Posch, Alfred & Hauswiesner, Angelika, 2021. "Hype cycles during socio-technical transitions: The dynamics of collective expectations about renewable energy in Germany," Research Policy, Elsevier, vol. 50(9).
    7. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    8. Weiss, Daniel & Nemeczek, Fabian, 2021. "A text-based monitoring tool for the legitimacy and guidance of technological innovation systems," Technology in Society, Elsevier, vol. 66(C).
    9. Jun, Seung-Pyo & Sung, Tae-Eung & Park, Hyun-Woo, 2017. "Forecasting by analogy using the web search traffic," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 37-51.
    10. Uddin, Md Hamid & Mollah, Sabur & Ali, Md Hakim, 2020. "Does cyber tech spending matter for bank stability?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    11. Jessica Mancilla-de-la-Cruz & Marisela Rodriguez-Salvador & Laura Ruiz-Cantu, 2020. "The Next Pharmaceutical Path: Determining Technology Evolution in Drug Delivery Products Fabricated with Additive Manufacturing," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(3), pages 55-70.
    12. Kirkels, Arjan, 2016. "Biomass boom or bubble? A longitudinal study on expectation dynamics," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 83-96.
    13. Kristóf Gyódi & Łukasz Nawaro & Michał Paliński & Maciej Wilamowski, 2023. "Informing policy with text mining: technological change and social challenges," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 933-954, February.
    14. Hashemi, Fariba & Gallay, Olivier & Hongler, Max-Olivier, 2021. "Opinion formation dynamics — Swift collective disillusionment triggered by unmet expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    15. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    16. Hansen, Ulrich Elmer & Nygaard, Ivan, 2014. "Sustainable energy transitions in emerging economies: The formation of a palm oil biomass waste-to-energy niche in Malaysia 1990–2011," Energy Policy, Elsevier, vol. 66(C), pages 666-676.
    17. Sabinne Lee & Kwangho Jung, 2018. "The Role of Community-led Governance in Innovation Diffusion: The Case of RFID Waste Pricing System in the Republic of Korea," Sustainability, MDPI, vol. 10(9), pages 1-23, September.
    18. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    19. Hopkins, Debbie & Schwanen, Tim, 2023. "Sociotechnical expectations of vehicle automation in the UK trucking sector," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    20. Bjerkan, Kristin Ystmark & Ryghaug, Marianne, 2021. "Diverging pathways to port sustainability: How social processes shape and direct transition work," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

    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:143:y:2019:i:c:p:114-124. 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.