Developing a Social Index for Measuring the Public Opinion Regarding the Attainment of Sustainable Development Goals


In 2015, United Nations adopted 17 Sustainable Development Goals (SDGs) to be achieved by 2030. Implementing SDGs is an important issue for companies as well as for nations. However, to consistently monitor and evaluate progress towards these goals, major efforts in developing objective indices for measuring the levels of SDGs are essential. Currently almost all SDG studies uniformly use available country-level official statistics to synthesize an SDG index, failing to reflect the feelings and opinions of the general public. In this paper we introduce an SDG Social Index developed by a Natural Language Processing (NLP) algorithm. By using social media text data rather than conventional survey data, this index can measure and evaluate the outspoken feelings and opinions of the public toward the SDGs. Here we produce an SDG Social Index for a global company and statistically assess its effectiveness. This framework for producing an SDG Social Index can easily be extended to make other indices where various text data are available. It can also be easily extended to yield country-specific SDG indices across nations. In Conclusion section we summarize the implications of our approach and discuss limitations and future research areas.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4


  1. Australasian Campuses Towards Sustainability. (2017). Mapping University contributions to the SDGs. Retrieved December 20 2019 from

  2. Bamberger, M., Segone, M., & Tateossian, F. (2016). Evaluating the sustainable development goals with a “No one left behind” lens through equity-focused and gender-responsive evaluations. New York: UN Women.

    Google Scholar 

  3. Böhringer, C., & Jochem, P. E. (2007). Measuring the immeasurable—A survey of sustainability indices. Ecological economics, 63(1), 1–8.

    Article  Google Scholar 

  4. Casini, M., Bastianoni, S., Gagliardi, F., Gigliotti, M., Riccaboni, A., & Betti, G. (2019). Sustainable development goals indicators: a methodological proposal for a multidimensional fuzzy index in the Mediterranean area. Sustainability, 11(4), 1198.

    Article  Google Scholar 

  5. SDG Compass. (2015). Retrieved December 20 2019 from

  6. S Compass (2015) The guide for business action on the SDGs. Geneva, Switzerland World Business Council for Sustainable Development (WBCSD)

  7. Crutzen, P. (2002). Geology of mankind. Nature.

    Article  Google Scholar 

  8. Dhaoui, C., Webster, C. M., & Tan, L. P. (2017). Social media sentiment analysis: Lexicon versus machine learning. Journal of Consumer Marketing.

    Article  Google Scholar 

  9. Dickens, C., Smakhtin, V., McCartney, M., O’Brien, G., & Dahir, L. (2019). Defining and quantifying National-level targets, indicators and benchmarks for management of natural resources to achieve the sustainable development goals. Sustainability, 11(2), 462.

    Article  Google Scholar 

  10. Enríquez, F., Troyano, J. A., & López-Solaz, T. (2016). An approach to the use of word embeddingsin an opinion classification task. Expert Systems with Applications, 66, 1–6.

    Article  Google Scholar 

  11. Grainger-Brown, J., & Malekpour, S. (2019). Implementing the sustainable development goals: A review of strategic tools and frameworks available to organisations. Sustainability, 11(5), 1381.

    Article  Google Scholar 

  12. Gruner, R. L., Homburg, C., & Lukas, B. A. (2014). Firm-hosted online brand communities and new product success. Journal of the Academy of Marketing Science, 42(1), 29–48.

    Article  Google Scholar 

  13. Guijarro, F., & Poyatos, J. A. (2018). Designing a sustainable development goal index through a goal programming model: The case of EU-28 countries. Sustainability, 10(9), 3167.

    Article  Google Scholar 

  14. Huan, Y., Li, H., & Liang, T. (2019). A new method for the quantitative assessment of sustainable development goals (SDGs) and a case study on central Asia. Sustainability, 11(13), 3504.

    Article  Google Scholar 

  15. Kharrazi, A., Qin, H., & Zhang, Y. (2016). Urban big data and sustainable development goals: Challenges and opportunities. Sustainability, 8(12), 1293.

    Article  Google Scholar 

  16. Körfgen, A., Förster, K., Glatz, I., Maier, S., Becsi, B., Meyer, A., et al. (2018). It’s a Hit! mapping austrian research contributions to the sustainable development goals. Sustainability, 10(9), 3295.

    Article  Google Scholar 

  17. Levy, O., Goldberg, Y., & Dagan, I. (2015). Improving distributional similarity with lessons learned from word embeddings. Transactions of the Association for Computational Linguistics, 3, 211–225.

    Article  Google Scholar 

  18. Loh, S., Lorenzi, F., Saldaña, R., & Licthnow, D. (2003). A tourism recommender system based on collaboration and text analysis. Information Technology and Tourism, 6(3), 157–165.

    Article  Google Scholar 

  19. Lozano, R., Fullman, N., Abate, D., Abay, S. M., Abbafati, C., Abbasi, N., et al. (2018). Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related sustainable development goals for 195 countries and territories: A systematic analysis for the global burden of disease study 2017. The Lancet, 392(10159), 2091–2138.

    Article  Google Scholar 

  20. McAlexander, J. H., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of marketing, 66(1), 38–54.

    Article  Google Scholar 

  21. Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint

  22. Misuraca, M., Scepi, G., & Spano, M. (2020). A network-based concept extraction for managing customer requests in a social media care context. International Journal of Information Management, 51, 101956.

    Article  Google Scholar 

  23. Monash University, SDSN Australia/Pacific. (2015). Compiled Keywords for SDG Mapping. Retrieved December 20 2019 from

  24. Nhemachena, C., Matchaya, G., Nhemachena, C. R., Karuaihe, S., Muchara, B., & Nhlengethwa, S. (2018). Measuring baseline agriculture-related sustainable development goals index for southern Africa. Sustainability, 10(3), 849.

    Article  Google Scholar 

  25. Pennington, J., Socher, R., & Manning, C. D. Glove (2014) Global vectors for word representation. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), (pp. 1532-1543).

  26. Perera, S. (2017) Reporting of Swiss and German companies on contributions to the sustainable development goals. Unpublished master’s thesis, ZHAW School of Management and Law, Winterthur.

  27. Porter, M. F. (2001) Snowball: A language for stemming algorithms. Accessed 20 Dec 2019.

  28. Porter, M. F. (1980) An algorithm for suffix stripping. Program: electronic library and information systems, 14(3), 130–137.

    Article  Google Scholar 

  29. Preston, M., Scott, L. (2015) Make It Your Business: Engaging with the Sustainable Development Goals. Accessed 20 Dec 2019.

  30. PwC. (2015). Shaping our future: Global Annual Review 2015. Retrieved December 20 2019 from

  31. Sachs, J., Schmidt-Traub, G., Kroll, C., Durand-Delacre, D., & Teksoz, K. (2016). SDG index & dashboards: A global report: Bertelsmann Stiftung.

  32. Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., & Fuller, G. (2018). Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN); New York: 2018. SDG index and dashboards report.

  33. Schmidt-Traub, G., Kroll, C., Teksoz, K., Durand-Delacre, D., & Sachs, J. D. (2017). National baselines for the sustainable development goals assessed in the SDG index and dashboards. Nature geoscience, 10(8), 547–555.

    Article  Google Scholar 

  34. Schnabel, T., Labutov, I., Mimno, D., & Joachims, T. (2015) Evaluation methods for unsupervised word embeddings. In Proceedings of the 2015 conference on empirical methods in natural language processing, (pp. 298-307).

  35. Sidorov, G., Gelbukh, A., Gómez-Adorno, H., & Pinto, D. (2014). Soft similarity and soft cosine measure: Similarity of features in vector space model. Computación y Sistemas, 18(3), 491–504.

    Article  Google Scholar 

  36. TextBlob. (2020). Retrieved November 16 2020 from

  37. United Nations. (2015). Transforming Our World: The 2030 Agenda for Sustainable Development. Retrieved December 20 2019 from

  38. United Nations. (2018). The Sustainable Development Goals Report 2018. New York City.

  39. Woodbridge, M. (2019). Measuring, Monitoring and Evaluating the SDGs. Retrieved December 20 2019 from

  40. Xue, B., Fu, C., & Shaobin, Z. (2014) A study on sentiment computing and classification of sina weibo with word2vec. In 2014 IEEE International Congress on Big Data, (pp. 358-363): IEEE

Download references


Not applicable

Author information




Conceptualization: Raejung Lee, Jinho Kim; Formal analysis: Raejung Lee; Methodology: Raejung Lee; Investigation: Raejung Lee, Jinho.Kim.; Software: Raejung Lee; Validation: Raejung Lee, Jinho Kim.; Writing: Raejung Lee, Jinho Kim; Writing - review & editing: Raejung Lee, Jinho Kim; Supervision: Jinho.Kim

Corresponding author

Correspondence to Raejung Lee.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lee, R., Kim, J. Developing a Social Index for Measuring the Public Opinion Regarding the Attainment of Sustainable Development Goals. Soc Indic Res (2021).

Download citation


  • Sustainable development goals
  • SDG index
  • SDG compass
  • NLP
  • Text mining
  • Word2Vec