Abstract
In recent years we have seen a large adherence to social media by various Higher Education Institutions (HEI) with the intent of reaching their target audiences and improve their public image. These institutional publications are guided by a specific editorial strategy, designed to help them better accomplish and fulfill their mission. The current Covid-19 pandemic has had major consequences in many different fields (political, economic, social, educational) beyond the spread of the disease itself. In this paper, we attempt to determine the impact of the pandemic on the HEI content strategies by gauging if these social-economical, cultural and psychological changes that occurred during this global catastrophe are actively reflected in their publications. Furthermore, we identified the topics that emerge from the pandemic situation checking the trend changes and the concept drift that many topics had. We gathered and analyzed more than 18k Twitter publications from 12 of the top HEI according to the 2019 Center for World University Rankings (CWUR). Utilizing machine learning techniques, and topic modeling, we determined the emergent content topics for each institution before, and during, the Covid-19 pandemic to uncover any significant differences in the strategies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mitchell, M., Leachman, M., Masterson, K.: A Lost Decade in Higher Education Funding State Cuts Have Driven up Tuition and Reduced Quality (2017)
Çiçek, M., Erdogmus, I.: The impact of social media marketing on brand loyalty. Procedia. Soc. Behav. Sci. 58, 1353–1360 (2012). https://doi.org/10.1016/j.sbspro.2012.09.1119
Figueira, A.: Uncovering social media content strategies for worldwide top-ranked universities. In: CENTERIS/ProjMAN/HCist 2018, vol. 138, pp. 663–670 (2018). https://doi.org/10.1016/j.procs.2018.10.088
Oliveira, L., Figueira, A.: Measuring performance and efficiency on social media: a longitudinal study. In: ECSM 2018 5th European Conference on Social Media, pp. 198–207 (2018)
Peruta, A., Shields, A.: Social media in higher education: understanding how colleges and universities use Facebook. J. Market. High. Educ. 27, 131–143 (2017). https://doi.org/10.1080/08841241.2016.1212451
Albalawi, R., Yeap, T., Benyoucef, M.: Using topic modeling methods for short-text data: a comparative analysis. Front. Artif. Intell. 3, 42 (2020). https://doi.org/10.3389/frai.2020.00042
Hoffman, M., Blei, D., Bach, F.: Online learning for latent dirichlet allocation. In: Advances in Neural Information Processing Systems 23, pp. 856–864 (2010)
Yao, L., Mimno, D., McCallum, A.: Efficient methods for topic model inference on streaming document collections. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 937–946 (2009). https://doi.org/10.1145/1557019.1557121
Mikolov, T., Sutskever, I., Chen, K, Corrado, G., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Proceedings of the 26th International Conference on Neural Information Processing Systems, vol. 2, pp. 3111–3119 (2013). https://doi.org/10.5555/2999792.2999959
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Coelho, T., Figueira, A. (2021). Covid-19 Impact on Higher Education Institution’s Social Media Content Strategy. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12950. Springer, Cham. https://doi.org/10.1007/978-3-030-86960-1_49
Download citation
DOI: https://doi.org/10.1007/978-3-030-86960-1_49
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-86959-5
Online ISBN: 978-3-030-86960-1
eBook Packages: Computer ScienceComputer Science (R0)