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Dynamics of Media Attention

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Presentation at ICCSA14, Le Havre, June 24, 2014

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Dynamics of Media Attention

  1. 1. Dynamics of Media Attention V.A. Traag, R. Reinanda, J. Hicks, G. Van Klinken KITLV, Leiden, the Netherlands e-Humanities, KNAW, Amsterdam, the Netherlands June 24, 2014 eRoyal Netherlands Academy of Arts and Sciences Humanities
  2. 2. Background Research focus • Study elite (network) behaviour. • Particular focus on regime changes. Case I: Indonesia, fall of Suharto 1998. Case II: Indonesian independence after WWII. • Data: newspaper articles. How can we use them? Data • Current corpus: Joyo/Indonesian News Service, 2004–2012. • Contains about 140 263 articles.
  3. 3. Network Building the network 1 Detect names automatically . “ Budhisantoso would ask Kalla to team up with Yudhoyono .” 2 Disambiguate names. Susilo Bambang Yudhoyono or Dr. Yudhoyono , etc. . . 3 Co-occurrence in sentence (record date). “ Budhisantoso would ask Kalla to team up with Yudhoyono .” K B Y 19-04-2004 19-04-2004 19-04-2004
  4. 4. Network Building the network 1 Detect names automatically . “ Budhisantoso would ask Kalla to team up with Yudhoyono .” 2 Disambiguate names. Susilo Bambang Yudhoyono or Dr. Yudhoyono , etc. . . 3 Co-occurrence in sentence (record date). “ Budhisantoso would ask Kalla to team up with Yudhoyono .” K B Y 19-04-2004 19-04-2004 19-04-2004
  5. 5. Network Building the network 1 Detect names automatically . “ Budhisantoso would ask Kalla to team up with Yudhoyono .” 2 Disambiguate names. Susilo Bambang Yudhoyono or Dr. Yudhoyono , etc. . . 3 Co-occurrence in sentence (record date). “ Budhisantoso would ask Kalla to team up with Yudhoyono .” K B Y 19-04-2004 19-04-2004 19-04-2004
  6. 6. Network Building the network 1 Detect names automatically . “ Budhisantoso would ask Kalla to team up with Yudhoyono .” 2 Disambiguate names. Susilo Bambang Yudhoyono or Dr. Yudhoyono , etc. . . 3 Co-occurrence in sentence (record date). “ Budhisantoso would ask Kalla to team up with Yudhoyono .” K B Y 19-04-2004 19-04-2004 19-04-2004
  7. 7. Media dynamics Dynamical characteristics • How does attention grow, decay? • How long do people stay in the news? • How often do new people enter the news? • Are there bursty patterns of attention? Comparison • Look at particular events. • Are dynamics any different? • Does attention grow or decay more quickly? • Do people drop from the news sooner than expected?
  8. 8. Media dynamics Dynamical characteristics • How does attention grow, decay? • How long do people stay in the news? • How often do new people enter the news? • Are there bursty patterns of attention? Comparison • Look at particular events. • Are dynamics any different? • Does attention grow or decay more quickly? • Do people drop from the news sooner than expected?
  9. 9. Weekly cycles 2004 2005 2006 2007 2008 2009 2010 2011 2012 Date 0 50 100 150 200 250 300 Frequency 0 5 10 15 20 25 30 35 40 Lag (days) 0.0 0.2 0.4 0.6 0.8 1.0 Autocorrelation 0.0 0.1 0.2 0.3 0.4 0.5 Frequency (days−1 ) 0 10000 20000 30000 40000 50000 Magnitude Neighbours’ timeseries correlate: underlying commonality.
  10. 10. Growth/decay attention -104 -103 -102 -101 0 101 102 103 104 Time relative to peak (days) 10-5 10-4 10-3 10-2 10-1 Attention α−βlog|t| α|t|−β αe−β|t| αe−β|t| |t|−γ Best fit e−βtt−γ.
  11. 11. Inter-event time 0 500 1000 1500 2000 2500 3000 Inter-event time (Days) 10-7 10-6 10-5 10-4 10-3 10-2 10-1 100 Probability Edges Nodes Powerlaw with exponential cut-off x−βe−γx .
  12. 12. Lifetime 0 500 1000 1500 2000 2500 3000 Lifetime (days) 10-3 10-2 10-1 100 Probability Edges Nodes Very long lifetime for nodes.
  13. 13. New nodes 1500 1000 500 0 500 1000 1500 2000 2500 3000 First Time Delay (days) 0.00 0.01 0.02 0.03 0.04 0.05 0.06Probability Edges Nodes New nodes (and edges) continuously appear in the media.
  14. 14. Conclusion Timescales Measure Short time Long time Peak growth/decay power law Poisson Inter-event power law Poisson Lifetime fast (very) slow New nodes/edges appear continuously Theory • Issues arise at a constant rate (Poisson process) • Within issues, faster dynamics, shorter lifetimes
  15. 15. Conclusion Questions?

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