Mapping Social Activities and Concepts with Social Media (Twitter) and Web Search Engines (Yahoo and Bing): A Case Study in 2012 US Presidential Election

By Tsou, Ming-Hsiang; Yang, Jiue-An et al. | Cartography and Geographic Information Science, September 2013 | Go to article overview

Mapping Social Activities and Concepts with Social Media (Twitter) and Web Search Engines (Yahoo and Bing): A Case Study in 2012 US Presidential Election


Tsou, Ming-Hsiang, Yang, Jiue-An, Lusher, Daniel, Han, Su, Spitzberg, Brian, Gawron, Jean Mark, Gupta, Dipak, An, Li, Cartography and Geographic Information Science


Introduction

The spread of ideas in the age of the Internet is a double-edged sword; it can enhance our collective welfare as well as produce forces that can destabilize the world. Traditional approaches to understanding the spread of impacts of ideas or events are based on twentieth century media--such as newsletters, advertisements, physically proximal group meetings, and telephone conversations. Cyberspace (Gibson 1984) (including web pages, social media, and online communities) is a powerful platform for collective social communications, personal networking, and idea exchange. Scientists now can trace, monitor, and analyze the spreads of radical social movements, protests, political campaigns, etc., via social media and weblogs. These research efforts can help us understand the diffusion of innovations (Roger 1962; Hagerstrand 1967; Brown 1981), a dynamic process whereby new concepts, ideas, and technologies spread through our society via cyberspace and digital social networks over time. An innovation is "an idea, practice, or object that is perceived as new by an individual or other unit of adoption" (Rogers 2003, 12). When an individual generates a new message, and that message is received and re-sent by others, it reflects a process of communicative innovation adoption. When spread across the potential population of all who might adopt a given message or idea, the diffusion rate, adoption curve shape, and market saturation all reflect aspects of the influence of that particular idea. In this sense, every message that is sent in cyberspace is a potential trace or reflection of an idea (i.e., potential influence), and every re-sent message is a trace of actual influence. The more interconnected certain social networks are, and the more central and durable certain ideas are in their recirculation within those social networks, they can illustrate potential signifiers of social and societal influence. This is not to ignore some of the critiques of traditional diffusion, such as in Blant (1987). Using users within social networks as the innovation centers, the diffusion assumption of constant centers of innovation disappears, as any number of people can innovate, let the idea spread, and cause another individual to innovate without physical geographic impediments. Using social networks also breaks down the cited exchange of diffusion (trading civilization/modernization for raw materials), as online idea sharing is often close to free (see Blaut 1987 for the cited exchange).

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To date, most empirical work on mapping cyberspace has viewed it as only loosely tethered to geospatial coordinates. Summary structural counts of messages or topics, and network linkages of message densities reflect the structure of cyberspace, but say relatively little about the realspaces (referring to the physical world that contains face-to-face communication and idea dispersion) from which such messages originate or terminate. Yet, real people in realspaces are sending and re-sending these messages, and it has long been known that propinquity and proximity significantly influence communication exchanges (see Rainie and Wellman 2012; Yin, Shaw, and Yu 2011). Investigating the correspondence between cyberspace and realspace is not only becoming increasingly possible given current technologies, but the discovery of such correspondences holds substantial promise for understanding the diffusion of ideas through time and space, both real and digital (see Adams 2010a, 2010b). Some, such as Lerman and Ghosh (2010) have been using social networks such as Digg and Twitter in mapping cyberspace related to news stories. Others, such as Paul and Dredze (2011), have been harnessing Twitter in relation to public health; isolating geographic regions related to cyberspace messages. There are also Vieweg et al. (2010) who examined Twitter in relation to natural hazard events.

This article introduces an innovative research framework, called Visualizing Information Space in Ontological Networks (VISION) (http://mappingideas. …

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