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首页> 外文期刊>Cartography and geographic information science >Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election
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Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election

机译：使用社交媒体（Twitter）和网络搜索引擎（雅虎和必应）绘制社交活动和概念图：2012年美国总统大选的案例研究

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摘要

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.
机译：我们引入了一个新的研究框架，用于分析具有相关内容的网页和社交媒体（Twitter）消息的空间分布，称为本体网络中的可视化信息空间（VISION）。这种创新方法可以从时空的角度促进在网络空间中传播的思想和社会事件的追踪。使用商业网络搜索引擎（Yahoo应用程序编程接口（API）和Bing API），社交媒体搜索引擎（Twitter API），互联网协议（IP），将成千上万的网页和与相同关键字相关联的数百万条推文转换为可视化地图。 ）地理定位方法和地理信息系统（GIS）功能（例如，核密度和基于栅格的地图代数方法）。我们发现，将多个Web信息环境与不同的关键字或不同的日期进行比较，可以揭示所选关键字的重要空间格局和“地理分布指纹”。我们使用2012年美国总统大选候选人作为我们的案例研究来验证这种方法。我们注意到，托管“巴拉克·奥巴马”或“米特·罗姆尼”网页的地理概率的每周变化与某些重大竞选活动高度相关。关注程度和推文内容都受到飓风桑迪的影响。这种新方法可能为定量研究人类思想，人类行为和社会活动提供新的研究方向。

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  • 来源
    《Cartography and geographic information science》 |2013年第4期|337-348|共12页
  • 作者

    Ming-Hsiang Tsou; Jiue-An Yang; Daniel Lusher; Su Han; Brian Spitzberg; Jean Mark Gawron; Dipak Gupta; Li An;

  • 作者单位

    Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA;

    Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA,Joint Doctoral program with University of California, Santa Barbara, CA, USA;

    Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA;

    Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA,Joint Doctoral program with University of California, Santa Barbara, CA, USA;

    School of Communication, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA;

    Department of Linguistics, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA;

    Department of Political Science, San Diego State University, 5500 Campanile Drive,San Diego, CA 92182-4493, USA;

    Department of Geography, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    web information landscapes; geospatial fingerprints; social media; twitter; election;

    机译：网络信息格局;地理空间指纹;社交媒体;推特;选举;

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