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Analyzing Social Media Networks with NodeXL,[object Object],Derek L. Hansen,[object Object],Maryland’s iSchool,[object Object]
NodeXL Research
Patterns are left behind,[object Object]
Research Goal,[object Object],Develop powerful tools, processes, and methods that dramatically lower the barriers for community managers and researchers to make sense of social media interactions.,[object Object]
Online Community Analysis,[object Object]
Social Network Analysis,[object Object],A systematic method for understanding relationships between entities.,[object Object],Vertex-Specific Metrics,[object Object],[object Object]
 Degree Centrality
 Eigenvector Centrality
 Closeness CentralityNetwork-Specific Metrics,[object Object],[object Object]
DensityClusters & Subgroups,[object Object],[object Object],[object Object]
NodeXL Research
NodeXL (http://nodexl.codeplex.com),[object Object]
Lesson’s Learned,[object Object],+ Tight integration of spreadsheet & visualization,[object Object],+ Attribute data and SNA metrics can be mapped onto rich set of visual properties,[object Object],+ Data importers,[object Object],+ Dynamic filters,[object Object],-  Not platform independent or web-based,[object Object],[object Object]
Poor at dealing with multiple networks,[object Object]
Novice SNA Study,[object Object],[object Object]
Task: create insightful network visualization & explanation of online community they’d been studying (3 weeks with feedback from peers & instructor)
Data collection: diaries, observations, interviews, questionnaire, content analysis of assignments, in-class process recap
Data analysis: grounded theory approach
Output: process model; challenges; supports,[object Object]
Finding an Alternate Admin,[object Object]
Inferring Relationships,[object Object]
Challenges & Supports,[object Object]
What Novices Need…,[object Object],Social media “network” data importers,[object Object],Better defined & recognized network visualization “genres”,[object Object],Improved layout algorithms,[object Object],The ability to share visualizations & analysis,[object Object],Basic network literacy,[object Object]
Research Questions (3),[object Object],How can SNA be applied to different social media platforms to gain actionable insights?,[object Object],What network “genres” lead to actionable insights?,[object Object]
NodeXL Research
Personal Email Collection,[object Object]
Mapping Corporate Email Communication Between Research Groups,[object Object]
Surgery Videos on YouTube,[object Object]
Finding Friendship Clusters in Facebook,[object Object],By Bernie Hogan,[object Object]
Finding Theorists in Lostpedia,[object Object]

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Hinweis der Redaktion

  1. One key characteristic of technology-mediated communication is that it can (and typically does) capture detailed data on social interactions.Just like footprints left on the sand tell a story about walking a dog on the beach, our digital footprints tell stories about our online behaviors and interactions.The mass of data created by social media has the potential to usher in a golden age of social science and data-driven decision making.However, to put this social data to good use by researchers, as well as non-technical community managers and decision makers, we need usable and powerful tools that support social media data analysis.