Abstract
We describe the results of a new computational experiment on Twitter data. By listening to Tweets on a selected topic, we generate a dynamic social interaction network. We then apply a recently proposed dynamic network analysis algorithm that ranks Tweeters according to their ability to broadcast information. In particular, we study the evolution of importance rankings over time. Our presentation will also describe the outcome of an experiment where results from automated ranking algorithms are compared with the views of social media experts.
| Original language | English |
|---|---|
| Number of pages | 3 |
| Publication status | Published - 23 Nov 2012 |
| Event | Digital Futures 2012 - Aberdeen, United Kingdom Duration: 23 Oct 2012 → 25 Oct 2012 |
Conference
| Conference | Digital Futures 2012 |
|---|---|
| Country | United Kingdom |
| City | Aberdeen |
| Period | 23/10/12 → 25/10/12 |
Keywords
- big hitters
- centrality
- social network analysis
- dynamic network
Fingerprint Dive into the research topics of 'Twitter’s big hitters'. Together they form a unique fingerprint.
Impacts
Commercial advantage through computational discovery of dynamic communicators in large digital networks
Desmond Higham (Participant), Ernesto Estrada (Participant) & Peter Grindrod (Participant)
Impact: Impact - for External Portal › Economic and commerce
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Cite this
Laflin, P., Mantzaris, A. V., Higham, D. J., Grindrod, P., Ainley, F., & Otley, A. (2012). Twitter’s big hitters. Paper presented at Digital Futures 2012, Aberdeen, United Kingdom.