• DocumentCode
    1771266
  • Title

    Identifying and shifting social media network patterns with NodeXL

  • Author

    Smith, Michael A.

  • Author_Institution
    Social Media Res. Found., Belmont, CA, USA
  • fYear
    2014
  • fDate
    19-23 May 2014
  • Firstpage
    3
  • Lastpage
    8
  • Abstract
    As people use social media they form networks that have several basic forms: divided, unified, fragmented, clustered, and hub and spoke patterns with in and outward facing links. These patterns are associated with different types of topics and discussions: polarized, in-group, brand, community, broadcast, and support. Since each pattern has specific properties in terms of its ability to spread information and form relationships, participants in these networks often find that the pattern they have is not the pattern they want. For example, people may seek to move from a fragmented brand pattern to a denser, more connected clustered community pattern. Network metrics can describe each of these patterns and provide a possible guide to effective methods to shift from one pattern to another. Tracking these metrics can provide practitioners with a method of assessing their efforts to cultivate the most desirable forms of network structures.
  • Keywords
    pattern classification; social networking (online); NodeXL; clustered pattern; divided pattern; fragmented pattern; hub-and-spoke pattern; network metrics; network structures; pattern identification; pattern shifting; social media network patterns; unified pattern; Communities; Measurement; Media; Sociology; Statistics; Twitter; InfoVis; Network Analysis; Semantic Networks; Social Media; Social Networks; Twitter; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Collaboration Technologies and Systems (CTS), 2014 International Conference on
  • Conference_Location
    Minneapolis, MN
  • Print_ISBN
    978-1-4799-5157-4
  • Type

    conf

  • DOI
    10.1109/CTS.2014.6867534
  • Filename
    6867534