Twitter’s big hitters

Peter Laflin, Alexander Vassilios Mantzaris, Desmond J. Higham, Peter Grindrod, Fiona Ainley, Amanda Otley

Research output: Contribution to conference › Paper

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.
LanguageEnglish
Number of pages3
Publication statusPublished - 23 Nov 2012
EventDigital Futures 2012 - Aberdeen, United Kingdom
Duration: 23 Oct 2012 → 25 Oct 2012

Conference

ConferenceDigital Futures 2012
CountryUnited Kingdom
CityAberdeen
Period23/10/12 → 25/10/12

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Electric network analysis
Experiments

Keywords

  • twitter
  • big hitters
  • centrality
  • social network analysis
  • dynamic network

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.
Laflin, Peter ; Mantzaris, Alexander Vassilios ; Higham, Desmond J. ; Grindrod, Peter ; Ainley, Fiona ; Otley, Amanda. / Twitter’s big hitters. Paper presented at Digital Futures 2012, Aberdeen, United Kingdom.3 p.
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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.",
keywords = "twitter, big hitters, centrality, social network analysis, dynamic network",
author = "Peter Laflin and Mantzaris, {Alexander Vassilios} and Higham, {Desmond J.} and Peter Grindrod and Fiona Ainley and Amanda Otley",
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note = "Digital Futures 2012 ; Conference date: 23-10-2012 Through 25-10-2012",

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Laflin, P, Mantzaris, AV, Higham, DJ, Grindrod, P, Ainley, F & Otley, A 2012, 'Twitter’s big hitters' Paper presented at Digital Futures 2012, Aberdeen, United Kingdom, 23/10/12 - 25/10/12, .

Twitter’s big hitters. / Laflin, Peter; Mantzaris, Alexander Vassilios; Higham, Desmond J.; Grindrod, Peter; Ainley, Fiona; Otley, Amanda.

2012. Paper presented at Digital Futures 2012, Aberdeen, United Kingdom.

Research output: Contribution to conference › Paper

TY - CONF

T1 - Twitter’s big hitters

AU - Laflin, Peter

AU - Mantzaris, Alexander Vassilios

AU - Higham, Desmond J.

AU - Grindrod, Peter

AU - Ainley, Fiona

AU - Otley, Amanda

PY - 2012/11/23

Y1 - 2012/11/23

N2 - 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.

AB - 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.

KW - twitter

KW - big hitters

KW - centrality

KW - social network analysis

KW - dynamic network

UR - http://www.de2012.org/

M3 - Paper

ER -

Laflin P, Mantzaris AV, Higham DJ, Grindrod P, Ainley F, Otley A. Twitter’s big hitters. 2012. Paper presented at Digital Futures 2012, Aberdeen, United Kingdom.

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