My research interests are in the areas of social media analytics, disaster communications, library automation, philosophy of information sourcing, information sources and systems. My thesis is geared towards developing mechanisms that can enable disaster or emergency responders analyze social media conversations to detect emergency preparedness among the populace as well as predict situational awareness. I am of the opinion that disaster communicators can use machine learning to analyze online conversations to predict and categorize the messages that could point out critical success factors as well as the direction of the narratives surrounding an extreme event.
Asubiaro, T., Badmus, O., Ikenyei, U., Popoola, B., & Igwe, E. (2021). Exploring Sub-Saharan Africa’s Communication of COVID-19-Related Health Information on Social Media. Libri. https://doi.org/10.1515/libri-2020-0097
Badmus, M. O. (2020). When the storm is over: Sentiments, communities and information flow in the aftermath of Hurricane Dorian. International Journal of Disaster Risk Reduction, 47, 101645. https://doi.org/10.1016/j.ijdrr.2020.101645
Asubiaro, T. V., & Badmus, O. M. (2020). Collaboration clusters, interdisciplinarity, scope and subject classification of library and information science research from Africa: An analysis of Web of Science publications from 1996 to 2015. Journal of Librarianship and Information Science. https://doi.org/10.1177/0961000620907958
Badmus, OM. "Of Bubbles and Sentiments: Virtual Communities in the Aftermath of Dorian" CAIS2020 vCoference. Sept. 25th 2020.https://www.cais2020.ca/talk/when-the-storm-is-over/