• DocumentCode
    3282302
  • Title

    Automatic Mapping of Social Networks of Actors from Text Corpora: Time Series Analysis

  • Author

    Danowski, James A. ; Cepela, Noah

  • Author_Institution
    Univ. of Illinois at Chicago, Chicago, IL, USA
  • fYear
    2009
  • fDate
    20-22 July 2009
  • Firstpage
    137
  • Lastpage
    142
  • Abstract
    To illustrate the WORDij approach to automatic social network identification from large volumes of text, this research mined the social networks among President Clintonpsilas cabinet members (n=24) and also President G.W. Bushpsilas cabinet members (n=45) over each of their two terms based on the members co-occurrence in news stories. The software used a time-slice interval of 30 days for Clinton stories because the average days between Gallup presidential job approval poll ratings was 30 days, resulting in 97 time slices. For Bush the average number of days between polls was 22 days, resulting in a 132-point time series. This synchronized the social networks with presidential job approval ratings. Clinton and Bush had nearly opposite relationships between network centrality and job approval. Automatic network analysis of social actors from textual corpora is feasible and enables testing hypotheses over time.
  • Keywords
    data mining; social networking (online); text analysis; Gallup presidential job approval poll ratings; President Clinton; President G.W. Bush; WORDij approach; automatic mapping; automatic social network identification; cabinet members; data mining; news stories; social network mining; social networks; text corpora; time series analysis; Automatic testing; Computer science; Computerized monitoring; Data mining; Humans; Performance analysis; Social network services; Sociology; Time series analysis; Uncertainty; Time Series Data Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
  • Conference_Location
    Athens
  • Print_ISBN
    978-0-7695-3689-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2009.71
  • Filename
    5231910