Home / Current Issue / Paper 1712783
Earth?s Healing Pulse: Tracking Ecosystem Recovery Through Data and Social Media Insights (2000?2024)
Subject area: Science,Engineering and Technology · Area of research: Science
DOI: https://doi.org/10.64388/IREV9I6-1712783
Abstract
This study empirically examines the dynamics of ecosystem recovery using environmental quality indicators and social media?driven public sentiment data over the period 2000?2024. Using the Biodiversity Recovery Index as a proxy for ecosystem restoration, the study applies descriptive statistics, correlation analysis, and Ordinary Least Squares regression to evaluate the effects of forest cover, air quality, water quality, social media environmental mentions, public environmental sentiment, and conservation investment. The regression results reveal that forest cover, water quality, public environmental sentiment, and conservation investment exert significant positive effects on biodiversity recovery, confirming the central role of both biophysical restoration and social engagement in ecosystem regeneration. Social media environmental mentions also display a positive and statistically meaningful influence, indicating that digital awareness and online environmental discourse contribute to real-world conservation outcomes. Air quality shows a weaker but directionally consistent relationship with ecosystem recovery. These findings align with Nigerian and international evidence that digital platforms, ICT-driven monitoring, and data-driven public engagement significantly enhance environmental governance and sustainability outcomes (Eke, 2015; Eke, 2019a). Recent artificial intelligence and digital analytics research further supports the effectiveness of high-dimensional environmental data systems in predicting and improving ecological performance (Eke, Al-Shamayleh, Phiri, Maswadi, Kwaghtyo, Mulenga, & Iyidobi, 2025). Global environmental data studies equally confirm that social media and digital sensing technologies have become powerful tools for tracking ecosystem change and public environmental behavior (World Bank, 2021; IPBES, 2022). Overall, the results establish that ecosystem recovery is jointly driven by biophysical restoration, digital awareness, and sustained conservation investment, underscoring the strategic importance of integrating environmental data analytics with digital public engagement for long-run ecological sustainability.
Keywords
Ecosystem Recovery, Biodiversity, Social Media Analytics, Environmental Sentiment, Conservation Investment, Digital Environmental Monitoring.
References
[1] Arrow, K. J. (1962). Economic welfare and the allocation of resources for invention. In R. R. Nelson (Ed.), The rate and direction of inventive activity: Economic and social factors (pp. 609–626). Princeton University Press.
[2] Bandura, A. (1977). Social learning theory. Prentice Hall.
[3] Dasgupta, P. (2021). The economics of biodiversity: The Dasgupta review. HM Treasury.
[4] Eke, C. I. (2012). Global system for mobile communication and urban employment in Nigeria: A case of Abuja. LAP Lambert Academic Publishing.
[5] Eke, C. I. (2015). An economic assessment of the impact of information and communication technology (ICT) on performance indicators of water management in West Africa. International Journal of Water Resources and Environmental Engineering, 7(4), 66–74.
[6] Eke, C. I. (2016). An economic assessment of Nigeria’s smartphone data bundle consumption, subscriber resource constraints and dynamics: The case of Abuja and Lagos States. Journal of Telecommunication System Management, 5, 122.
[7] Eke, C. I. (2019a). Telecommunication infrastructure, economic growth and development in Nigeria, 1980–2014: Prospects, challenges and policy assessment. FUDMA Economic and Development Review, 2(1), 1–16.
[8] Eke, C. I. (2019b). Teledensity and economic growth in Nigeria: An impact assessment. Bingham Journal of Economics and Allied Studies, 2(2), 120–131.
[9] Eke, C. I., & El-Yaqub, A. B. (2018). GSM network uncertainty, social media and consumption theory: Challenges and prospects of harnessing ICT platform for inclusive growth in Nigeria. Pennsylvania Economic Review, 25(1), 91–111.
[10] Eke, C. I., & Eze, M. (2010). An economic assessment of the labour strategies of successful family-owned small scale telecommunication enterprises in Nigeria’s urban areas: The case of Gwagwalada, Abuja. Abuja Journal of Banking and Finance, 1(1), 78–84.
[11] Eke, C. I., & Isa, M. N. (2010). An economic assessment of customer service in the telecommunication industry in Nigeria: The case of mobile telecommunication network providers. Journal of the Faculty of Social and Management Sciences (Kaduna State University), 4(1), 101–121.
[12] Eke, C. I., & Mohammed, Y. (2009). The impact of small-scale communication business on the economic wellbeing of rural dwellers in Cross River State, Nigeria. Journal of General Studies, 1(2), 96–102.
[13] Eke, C. I., Egwaikhide, C. I., Saheed, Z. S., Alexander, A. A., Farouk, B. U. K., & Adeleke, A. O. (2019). Impact of teledensity on economic growth in Nigeria, 1980–2018. Article.
[14] Eke, C. I., Norman, A. A., & Shuib, L. (2021). Context-based feature technique for sarcasm identification in benchmark datasets using deep learning and BERT model. IEEE Access, 9, 48501–48518.
[15] Eke, C. I., Al-Shamayleh, A. S., Phiri, M., Maswadi, K., Kwaghtyo, D. K., Mulenga, M., & Iyidobi, C. J. (2025). Machine learning based mobile big data analytics: State-of-the-art applications, taxonomy, challenges and future research directions. Nigerian Journal of Technological Development, 22(4), 65–89.
[16] Emmoh, P. U., Eke, C. I., Moses, T., & Ovre, A. J. (2025). Feature selection techniques for high-dimensional data analysis: Applications, challenges, and future directions. Nigerian Journal of Technological Development, 22(1), 201–214.
[17] Federal Ministry of Environment. (2020). *Nigeria environment sector
How to cite this paper
@article{1712783,
author = {Dr. Chukwuemeka Ifegwu Eke, Linda Nguavese Akpera; Hawakulu Abdullahi, Nurudeen Fauziyya Mohammed; Ughamadu Chinonso Christian; Ajumobi Folashade Victoria, Abdul-aleem Habibat Odunayo; Onoja Simeon; Adesanya Akhile Mercy, Richard Femi Timothy; Igbinomwanhia Osahon Steven; Ahmad Ajisafe},
title = {Earth?s Healing Pulse: Tracking Ecosystem Recovery Through Data and Social Media Insights (2000?2024)},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {6},
pages = {1035-1047},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712783.pdf},
abstract = {This study empirically examines the dynamics of ecosystem recovery using environmental quality indicators and social media?driven public sentiment data over the period 2000?2024. Using the Biodiversity Recovery Index as a proxy for ecosystem restoration, the study applies descriptive statistics, correlation analysis, and Ordinary Least Squares regression to evaluate the effects of forest cover, air quality, water quality, social media environmental mentions, public environmental sentiment, and conservation investment. The regression results reveal that forest cover, water quality, public environmental sentiment, and conservation investment exert significant positive effects on biodiversity recovery, confirming the central role of both biophysical restoration and social engagement in ecosystem regeneration. Social media environmental mentions also display a positive and statistically meaningful influence, indicating that digital awareness and online environmental discourse contribute to real-world conservation outcomes. Air quality shows a weaker but directionally consistent relationship with ecosystem recovery. These findings align with Nigerian and international evidence that digital platforms, ICT-driven monitoring, and data-driven public engagement significantly enhance environmental governance and sustainability outcomes (Eke, 2015; Eke, 2019a). Recent artificial intelligence and digital analytics research further supports the effectiveness of high-dimensional environmental data systems in predicting and improving ecological performance (Eke, Al-Shamayleh, Phiri, Maswadi, Kwaghtyo, Mulenga, & Iyidobi, 2025). Global environmental data studies equally confirm that social media and digital sensing technologies have become powerful tools for tracking ecosystem change and public environmental behavior (World Bank, 2021; IPBES, 2022). Overall, the results establish that ecosystem recovery is jointly driven by biophysical restoration, digital awareness, and sustained conservation investment, underscoring the strategic importance of integrating environmental data analytics with digital public engagement for long-run ecological sustainability.},
keywords = {Ecosystem Recovery, Biodiversity, Social Media Analytics, Environmental Sentiment, Conservation Investment, Digital Environmental Monitoring.},
month = {December},
doi = {https://doi.org/10.64388/IREV9I6-1712783}
}