The diffusion of information is a spatial and temporal process governed by the flow of inter-personal communication of information. Different from the diffusion of agricultural and technological innovation, the diffusion of information is largely in the private setup and it is difficult to capture the signals of an individual adopting the idea; thus, bring-ing challenges to this research domain. The emergence of the Internet and especially social media platforms has reshaped this process not only by scaling up the speed, range, and scale of information spreading, but also making these inter-person conversational data available. Although many research has waded into these human interactions in cy-berspace and studied how online social networks contribute to the diffusion dynamics, the role of geography in the process is yet to be understood. Activities in cyberspace are still confined to physical locations and this geographic connection tends to be over-looked. Focusing on geographic regions instead of individuals, this dissertation examines the diffusion of information with user-generated geo-social conversation data and ana-lyzes the impact of fundamental geography factors in shaping the spatial and temporal diffusion patterns. Chapter 2 focuses on establishing the baseline behavior of Twitter activities in each study area and analyzing the relationships between the spatial patterns of information diffusion and the structure of urban hierarchy. Chapter 3 is interested in how spatial attributes of the information (localness and relatedness) carry out differ-ence diffusion patterns in comparison to the baseline activity. In addition, the impact of physical distance is analyzed at the national and regional scale as the extension of the neighborhood effect identified in the literature. Examining both the active and passive aspects of diffusion over conversations, Chapter 4 analyzes the interactions between ur-ban regions and between users and opinion leaders with the spatial social network. This dissertation presents a research framework and methodological details for understanding diffusion of information using user-generated geo-social conversation data, and a variety of real-world cases are employed to demonstrate the proposed methods. The framework is not restricted to the data used in the chapters and can be adjusted to location-based conversation posts from other data source or social media platforms. Although with its limitations, I trust this work to contribute to the understanding and quantifying of information diffusion as a spatiotemporal process.