Skip to main content
SpringerLink
Log in

Identification of future signal based on the quantitative and qualitative text mining: a case study on ethical issues in artificial intelligence

  • Published:
Quality & Quantity Aims and scope Submit manuscript

Abstract

To foresee the advent of new technologies and their socio-economic impact is a necessity for academia, governments and private enterprises as well. In the future studies, the identification of future signal is one of the renowned techniques for analysis of trends, emerging issue, and gaining future insights. In the Big Data era, recent scholars have proposed using a text mining procedure focusing upon web data such as new social media and academic papers. However, the detection of future signals is still under a developing area of research, and there is much to improve existing methodology as well as developing theoretical foundations. The present study reviews previous literature on identifying emerging issue based on the weak signal detection approach. Then the authors proposed a revised framework that incorporate quantitative and qualitative text mining for assessing the strength of future signals. The authors applied the framework to the case study on the ethical issues of artificial intelligence (hereafter AI). From EBSCO host database, the authors collected text data covering the ethical issues in AI and conducted text mining analysis. Results reveal that emerging ethical issues can be classified as strong signal, weak signal, well-known but not so strong signal, and latent signal. The revised methodology will be able to provide insights for government and business stakeholders by identifying the future signals and their meanings in various fields.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. In the literature the term ‘signal’ and ‘sign’ were used interchangeably, we consider Hiltunen (2008)’s weak sign to be a synonym with weak signal for preventing confusion.

  2. Sam Byford, ‘Google’s AlphaGo AI beats Lee Se-dol again to wi Go series 4-1’ on The Verge (15 March 2016), http://www.theverge.com/2016/3/15/11213518/alphago-deepmind-go-match-5-result.

  3. Lilian Kim, ‘Parents Upset after Palo Alto Security Robot Injures Child’ on ABC7 (11 July 2016), http://abc7.com/news/parents-upset-after-norcal-security-robot-injures-child/1424537/.

  4. Samuel Gibbs, ‘Microsoft’s racist chatbot returns with drug-smoking Twitter meltdown’ on The Guardian (30 March 2016), https://www.theguardian.com/technology/2016/mar/30/microsoft-racist-sexist-chatbot-twitter-drugs.

  5. Neal Boudette, ‘Tesla’s Self-Driving System Cleared in Deadly Crash’ on The New York Times (19 January 2017), https://www.nytimes.com/2017/01/19/business/tesla-model-s-autopilot-fatal-crash.html?_r=0.

  6. Executive Office of the President of the United States, Artificial Intelligence, Automation and the Economy (Executive Office of the President, 2016), https://www.whitehouse.gov/sites/whitehouse.gov/files/images/EMBARGOED%20AI%20Economy%20Report.pdf.

  7. Alex Hern, ‘give Robots Personhood Status, EU Committee Argues’ on The Guardian (12 January 2017), https://www.theguardian.com/technology/2017/jan/12/give-robots-personhood-status-eu-committee-argues.

  8. IEEE, ‘Robot Ethics’ on IEEE (2017), http://www.ieee-ras.org/robot-ethics.

  9. Peer reviewers include participants of WATEF International Conference 2016: DISC (data, innovation, social, and conversion).

References

  • Ansoff, H.I.: Managing strategic surprise by response to weak signals. Calif. Manag. Rev. 18(2), 21–33 (1975)

    Article  Google Scholar 

  • Carley, K., Kaufer, D.: Semantic connectivity: an approach for analyzing symbols in semantic networks. Commun. Theory 3(3), 183–213 (1993)

    Article  Google Scholar 

  • Cho, S.E., Choi, M.G., Park, H.W.: Government-civic group conflicts and communication strategies: a text analysis of TV debates on Korea’s import of U.S. beef. J. Contemp. East. Asia 11(1), 1–20 (2012)

    Article  Google Scholar 

  • Choi, S., Park, H.W.: Networking interest and networked structure: a quantitative analysis of Twitter data. Soc. Sci. Comput. Rev. 33(2), 145–162 (2015)

    Article  Google Scholar 

  • Choo, C.W.: The art of scanning the environment. Bull. Am. Soc. Inf. Sci. Technol. 25(3), 21–24 (1999)

    Article  Google Scholar 

  • Choo, C.W., Auster, E.: Environmental scanning: acquisition and use of information by managers. Ann. Rev. Inf. Sci. Technol. 28, 279–314 (1993)

    Google Scholar 

  • Coffman, B.: Weak signal research. Part I. Introduction, MG Taylor Corporation (1997)

    Google Scholar 

  • Dator, J. A.: Advancing futures: Futures studies in higher education. Greenwood Publishing Group (2002)

  • Danowski, J.A.: WORDij 3.0 [Computer Program]. University of Illinois at Chicago, Chicago (2010)

    Google Scholar 

  • Doerfel, M.L.: What constitutes semantic network analysis? A comparison of research and methodologies. Connections 21(2), 16–26 (1998)

    Google Scholar 

  • Doerfel, M. L., Barnett, G. A.: A Semantic Network Analysis of the International Communication Association. Human Communication Research. 25(4), 589–603 (1999)

    Article  Google Scholar 

  • Girvan, M., Newman, M.E.: Community structure in social and biological networks. Proc. Natl. Acad. Sci. 99(12), 7821–7826 (2002)

    Article  Google Scholar 

  • Hellsten, I., Dawson, J., Leydesdorff, L.: Implicit media frames: automated analysis of public debate on artificial sweeteners. Public Underst. Sci. 19(5), 590–608 (2010)

    Article  Google Scholar 

  • Hiltunen, E.: Was it a wild card or just our blindness to gradual change. J. Futures Stud. 11(2), 61–74 (2006)

    Google Scholar 

  • Hiltunen, E.: The future sign and its three dimensions. Futures 40(3), 247–260 (2008)

    Article  Google Scholar 

  • Hong, S.W., Kim, Y.E., Bae, K.J., Park, Y.W., Park, J.K.: Development of analysis model for R&D environment change in search of the weak signal. J. Korea Technol. Innov. Soc. 12(1), 189–211 (2009)

    Google Scholar 

  • Hong, Y.J., Shin, D., Kim, J.H.: High/low reputation companies’ dialogic communication activities and semantic networks on Facebook: a comparative study. Technol. Forecast. Soc. Change 110, 78–92 (2016)

    Article  Google Scholar 

  • Hsu, C.L., Park, S.J., Park, H.W.: Political discourse among key Twitter users: the case of Sejong City in South Korea. J. Contemp. East. Asia 12(1), 65–79 (2013)

    Article  Google Scholar 

  • Julien, P.A., Andriambeloson, E., Ramangalahy, C.: Networks, weak signals and technological innovations among SMEs in the land-based transportation equipment sector. Entrep. Reg. Dev. 16(4), 251–269 (2004)

    Article  Google Scholar 

  • Jung, K., Valero, J.N.: Assessing the evolutionary structure of homeless network: social media use, keywords, and influential stakeholders. Technol. Forecast. Soc. Change 110, 51–60 (2016)

    Article  Google Scholar 

  • Kamppinen, M., Kuusi, O., Soderlund, S.: Tulevaisuudentutkimus Perusteet ja Sovellukset (Futures Studies, Foundations and Directions). Suomalaisen Kirjallisuuden Seura, Helsinki (2002)

    Google Scholar 

  • Kuosa, T.: Futures signals sense-making framework (FSSF): a start-up tool to analyse and categorise weak signals, wild cards, drivers, trends and other types of information. Futures 42(1), 42–48 (2010)

    Article  Google Scholar 

  • Kuusi, O., Hiltunen, E.: The signification process of the future sign. J. Futures Stud. 16(1), 47–66 (2011)

    Google Scholar 

  • Lee, Y.-J., Lee, J.-H., Ham, K.S.: Balancing efficiency and flexibility in software project: the role of team collective improvisation, behavioral integration, and member diversity. J. Contemp. East. Asia 16(1), 22–45 (2017)

    Google Scholar 

  • Maurits Butter, M.L., Cagnin, C., Carabias, V., Könnölä, T., van Rij, V., Klerx, J., Schape Rinkel, P., Amanatidou, E., Saritas, O., Harper, J.C., Pace, L.: Scanning for early recognition of emerging issues; dealing with the unexpected, an operational framework for the identification and assessment of new future developments. Workshop paper: SESTI methodology, workshop 26 October 2010

  • Murtagh, F., Pianosi, M., Bull, R.: Semantic mapping of discourse and activity, using Habermas’s theory of communicative action to analyze process. Qual. Quant. 50(4), 1675–1694 (2016)

    Article  Google Scholar 

  • Ponomareva, J., Sokolova, A.: The identification of weak signals and wild cards in foresight methodology: stages and methods (No. WP BRP 46/STI/2015). National Research University Higher School of Economics (2015)

  • Pratama, A.B.: Online-based local government image typology: a case study on jakarta provincial government official YouTube videos. J. Contemp. East. Asia 16(1), 1–21 (2017)

    Google Scholar 

  • Smith, M.: Catalyzing social media scholarship with open tools and data. J. Contemp. East. Asia 14(2), 87–96 (2015)

    Article  Google Scholar 

  • Stek, P.E., van Geenhuizen, M.S.: The influence of international research interaction on national innovation performance: a bibliometric approach. Technol. Forecast. Soc. Change 110, 61–70 (2016)

    Article  Google Scholar 

  • Sudhahar, S., Veltri, G., Christianini, N.: Automated analysis of the US presidential elections using Big Data and network analysis. Big Data Soc. 2(1), 1–28 (2015)

    Article  Google Scholar 

  • Thorleuchter, D., Van den Poel, D.: Technology classification with latent semantic indexing. Expert Syst. Appl. 40(5), 1786–1795 (2013a)

    Article  Google Scholar 

  • Thorleuchter, D., Van den Poel, D.: Protecting research and technology from espionage. Expert Syst. Appl. (2013b). doi:10.1016/j.eswa.2012.12.051

    Google Scholar 

  • Thorleuchter, D., Van den Poel, D.: Weak signal identification with semantic web mining. Expert Syst. Appl. 40(12), 4978–4985 (2013c)

    Article  Google Scholar 

  • Thorleuchter, D., Van den Poel, D.: Idea mining for web-based weak signal detection. Futures 66, 25–34 (2015)

    Article  Google Scholar 

  • Thorleuchter, D., Scheja, T., Van den Poel, D.: Semantic weak signal tracing. Expert Syst. Appl. 41(11), 5009–5016 (2014)

    Article  Google Scholar 

  • Wang, W., Rada, R.: Structured hypertext with domain semantics. ACM Trans. Inf. Syst. 16(4), 372–412 (1998)

    Article  Google Scholar 

  • Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)

    Book  Google Scholar 

  • Yoo, S.H., Park, H.W., Kim, K.H.: A study on exploring weak signals of technology innovation using informetrics. J. Technol. Innov. 17(2), 109–130 (2009)

    Google Scholar 

  • Yoon, J.: Detecting weak signals for long-term business opportunities using text mining of Web news. Expert Syst. Appl. 39(16), 12543–12550 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Future Strategy Center, National Information Society Agency (NIA), 53, Cheomdan-ro, Dong-gu, Daegu, 40168, Korea

    Young-Joo Lee & Ji-Young Park

Authors
  1. Young-Joo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ji-Young Park
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Young-Joo Lee.

Appendix

Appendix

See Table 5.

Table 5 Top 30 keyword with high frequency
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, YJ., Park, JY. Identification of future signal based on the quantitative and qualitative text mining: a case study on ethical issues in artificial intelligence. Qual Quant 52, 653–667 (2018). https://doi.org/10.1007/s11135-017-0582-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11135-017-0582-8

Keywords

Search

Navigation