Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election

We introduce a new research framework for analyzing the spatial distribution of web pages and social media (Twitter) messages with related contents, called Visualizing Information Space in Ontological Networks (VISION). This innovative method can facilitate the tracking of ideas and social events disseminated in cyberspace from a spatial-temporal perspective. Thousands of web pages and millions of tweets associated with the same keywords were converted into visualization maps using commercial web search engines (Yahoo application programming interface (API) and Bing API), a social media search engine (Twitter APIs), Internet Protocol (IP) geolocation methods, and Geographic Information Systems (GIS) functions (e.g., kernel density and raster-based map algebra methods). We found that comparing multiple web information landscapes with different keywords or different dates can reveal important spatial patterns and "geospatial fingerprints" for selected keywords. We used the 2012 US Presidential Election candidates as our case study to validate this method. We noticed that the weekly changes of the geographic probability of hosting "Barack Obama" or "Mitt Romney" web pages are highly related to certain major campaign events. Both attention levels and the content of the tweets were deeply impacted by Hurricane Sandy. This new approach may provide a new research direction for studying human thought, human behaviors, and social activities quantitatively.