Exploring social media relationships
Bibliographic Data
| ID | 12428489 |
|---|---|
| Authors | Dana Lee Hansen (0000-0002-9645-3279, University of Maryland, College Park, corresponding author), Derek L Hansen |
| Editors | Christine Greenhow (0000-0002-5637-2319) |
| Year | 2011 |
| Volume | 19 |
| Issue | 1 |
| Pages | 43-51 |
| Publication date | 2011-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | On the Horizon The International Journal of Learning Futures (JOURNAL) |
| Journal identifiers | ISSN: 1074-8121 • E-ISSN: 2054-1708 |
| Publisher | Emerald Publishing Limited (PUBLISHER • GB) |
| DOI | 10.1108/10748121111107726 |
| OpenAlex | W2066330713 |
| Language | EN |
| Citations received | 9 |
| References cited | 7 |
Purpose The purpose of this paper is to demonstrate novel techniques for exploring relationship data extracted from social media sites for actionable insights by educators, researchers, and administrators. Design/methodology/approach The paper demonstrates how non‐programmers can use NodeXL, an open source social network analysis tool built into Excel 2007/2010, to collect, analyze, and visualize network data from social media sites like Twitter and YouTube. Findings Researchers and education professionals can use NodeXL to explore (a) social networks to identify important individuals and subgroups, as well as (b) content networks to map the underlying structure of a domain and find important content. Illustrative examples are provided using NodeXL to examine followers of a Twitter user focused on open education, as well as a content network of YouTube videos about surgery. Research limitations/implications Tools like NodeXL are making network analysis accessible to non‐technical researchers in a variety of fields spanning the sciences, social sciences, and the humanities. Despite their value, network analysis techniques are only as good as the data that underlie them, requiring careful assessment of possible selection biases and triangulation of findings. Practical implications Educational institutions and educators can benefit from more systematically analyzing their social media initiatives from a network perspective. Originality/value This paper describes some of the techniques and tools needed to make sense of the social relationships that underlie social media sites. As relational data are increasingly made public, such techniques will enable more systematic analysis by researchers studying social phenomena and practitioners implementing social media initiatives
Content analysis · Data science · Domain (mathematical analysis · Knowledge management · Originality · Perspective (graphical · Qualitative research · Social media · Social network (sociolinguistics · Social network analysis · Social science · Sociology · Triangulation · Value (mathematics · Variety (cybernetics · World Wide Web · Complex Network Analysis Techniques · Computer Science · Impact of Technology on Adolescents · Social Media and Politics
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| Unique citing works | 9 |
|---|---|
| Citations per year | 0,64 |
| Citation span | 2012 - 2024 (13) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 9 |