Doctor of Philosophy (PhD)
First Advisor's Name
Arif Mohaimin Sadri
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The increased availability of technology-enabled transportation options and modern communication devices (smartphones, in particular) is transforming travel-related decision-making in the population differently at different places, points in time, modes of transportation, and socio-economic groups. The emergence of COVID-19 made the dynamics of passenger travel behavior more complex, forcing a worldwide, unparalleled change in human travel behavior and introducing a new normal into their existence. This dissertation explores the potential of social media platforms (SMPs) as a viable alternative to traditional approaches (e.g., travel surveys) to understand the complex dynamics of people’s mobility patterns in the emergence of COVID-19. In this dissertation, we focus on three objectives. First, a novel approach to developing comparative infographics of emerging transportation trends is introduced by natural language processing and data-driven techniques using large-scale social media data. Second, a methodology has been developed to model community-based travel behavior under different socioeconomic and demographic factors at the community level in the emergence of COVID-19 on Twitter, inferring users’ demographics to overcome sampling bias. Third, the communication patterns of different transportation agencies on Twitter regarding message kinds, communication sufficiency, consistency, and coordination were examined by applying text mining techniques and dynamic network analysis.
The methodologies and findings of the dissertation will allow real-time monitoring of transportation trends by agencies, researchers, and professionals. Potential applications of the work may include: (1) identifying spatial diversity of public mobility needs and concerns through social media platforms; (2) developing new policies that would satisfy the diverse needs at different locations; (3) introducing new plans to support and celebrate equity, diversity, and inclusion in the transportation sector that would improve the efficient flow of goods and services; (4) designing new methods to model community-based travel behavior at different scales (e.g., census block, zip code, etc.) using social media data inferring users’ socio-economic and demographic properties; and (5) implementing efficient policies to improve existing communication plans, critical information dissemination efficacy, and coordination of different transportation actors to raise awareness among passengers in general and during unprecedented health crises in the fragmented communication world.
Previously Published In
1. Alam, Md Rakibul, and Arif Mohaimin Sadri. "Examining the Communication Pattern of Transportation and Transit Agencies on Twitter: A Longitudinal Study in the Emergence of COVID-19 on Twitter." Transportation Research Record (2022): 03611981221082564..
2. Alam, Md Rakibul, Arif Mohaimin Sadri, and Xia Jin. "Identifying Public Perceptions toward Emerging Transportation Trends through Social Media-Based Interactions." Future Transportation 1, no. 3 (2021): 794-813.
3. Jin, Xia, Md Rakibul Alam, Arif Sadri, and Lu Zhang. "Identifying and Tracking Emerging Transportation Trends and Indicators." (2020).
Alam, Md Rakibul, "Community-Based Behavioral Understanding of Mobility Trends and Public Attitude through Transportation User and Agency Interactions on Social Media in the Emergence of Covid-19" (2022). FIU Electronic Theses and Dissertations. 5008.
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