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Pathak, A. R., Agarwal, B., Pandey, M., & Rautaray, S. (2020). Application of Deep Learning Approaches for Sentiment Analysis. In B. Agarwal, R. Nayak, N. Mittal, & S. Patnaik (Eds.), Deep Learning-Based Approaches for Sentiment Analysis (pp. 1-31). Singapore: Springer.
https://doi.org/10.1007/978-981-15-1216-2_1

has been cited by the following article:

• TITLE: Positive Spillover of Political and Technological Crises on Persons, Organizations, and Destinations across Covid-19: A Data Triangulation Study

  AUTHORS: Anthony E. Onyeama

  KEYWORDS: Covid-19 Crisis, Political Crisis, Resilience, Spillover Effect, Technological Crisis

  JOURNAL NAME: Open Journal of Political Science, Vol.11 No.3, July 19, 2021

  ABSTRACT: Crises are now parts of daily experience, peoples, organizations, and destinations experience crises. Most times, it occurs without realizing it, and even when people take note, it is the negative spillovers that are often emphasized more than the positive spillovers. Little do people realize that the crisis they are in today prepares them for tomorrow’s strength. Unfortunately, there is little or no literature on the positive spillovers of crises. This study aims to fill the literature on the positive spillover of crises on peoples, organizations, and destinations using a qualitative data triangulation, comprising face-to-face interviews and textual data. The study employed spillover effect and resilience theories to justify the arguments. Findings from stage 1 analysis revealed three themes, and stage 2 analyzes supported the findings. Most times, survivors of crises end up becoming resilient after an experience. This study discussed managerial and practical implications, as well as limitations and future studies.