{
  "id": "the-power-of-message-networks-a-big-data-analysis-of-the-network-agenda-setting-model-an",
  "type": "article-journal",
  "title": "The power of message networks: A big–data analysis of the network agenda setting model and issue ownership",
  "author": [
    {
      "family": "Guo",
      "given": "L."
    },
    {
      "family": "Vargo",
      "given": "C."
    }
  ],
  "URL": "https://chrisjvargo.com/publications/the-power-of-message-networks-a-big-data-analysis-of-the-network-agenda-setting-model-an/",
  "DOI": "10.1080/15205436.2015.1045300",
  "issued": {
    "date-parts": [
      [
        2015
      ]
    ]
  },
  "container-title": "Mass Communication & Society",
  "volume": "18",
  "issue": "5",
  "page-first": "557",
  "page-last": "576",
  "abstract": "This paper presents an empirical study that tests a new concept “issue ownership network,” which is based on the Network Agenda Setting (NAS) Model and the theory of issue ownership. Big data analytics and semantic network analysis were used to examine the large dataset collected on Twitter during the 2012 U.S. presidential election. Results showed that the news media could determine the public’s identification of a political candidate with not just individual issues, but also entire networks of issues. Here we argue that traditional news media still set the public agenda in this new media environment, and do so in ways more complicated through constructing message networks. The study also demonstrates that the NAS model and its unique focus can potentially enrich the understanding of other communication and social science theories and concepts.",
  "page": "557-576",
  "keyword": "Network Agenda Setting Model, agenda setting, issue ownership, network analysis, sentiment analysis, 2013, Guo & McCombs, 2011a, 2011b). Empirical"
}