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Opinion Dynamics         ModellingSocial Impact Theory and the 2011 Portuguese                 Elections                  ...
Summary:• Online social network data on 2011 portuguese elections• Social impact theory• Multi-agent based modelling• Data...
Online data collection:• Data collected between the 30th October 2010 and the 21th of January 2011 andbetween 27 March and...
Presidential elections:• Six Candidates• Final Results:                    Candidate   Result                      Cavaco ...
A. Fonseca, J. Louçã - ECCS 2011
Final Results:A. Fonseca, J. Louçã - ECCS 2011
A. Fonseca, J. Louçã - ECCS 2011
Final Results:A. Fonseca, J. Louçã - ECCS 2011
Polls:A. Fonseca, J. Louçã - ECCS 2011
Covariance between community and media tweets                                 A. Fonseca, J. Louçã - ECCS 2011
Legislative elections:• Five major parties• Final Results*:                                    Party    Result            ...
A. Fonseca, J. Louçã - ECCS 2011
Final Results:A. Fonseca, J. Louçã - ECCS 2011
A. Fonseca, J. Louçã - ECCS 2011
Final Results:A. Fonseca, J. Louçã - ECCS 2011
Polls:A. Fonseca, J. Louçã - ECCS 2011
Covariance between community and media tweets                                 A. Fonseca, J. Louçã - ECCS 2011
Experimental data conclusions:• Users tend to tweet proportionaly to the quantity of news.• Users tend to tweet about the ...
Social Impact Modelling                A. Fonseca, J. Louçã - ECCS 2011
[Latané B., 1981]A. Fonseca, J. Louçã - ECCS 2011
Model of political debate:• Media influences agents, agents influence each other.• Each agent has propensity or aversion (...
Simulation - 1 run legislatives                        A. Fonseca, J. Louçã - ECCS 2011
Results Analysis            A. Fonseca, J. Louçã - ECCS 2011
Experimental validation:• Agent community as real community (1903 users, 46423 links).• Input stimulus, media twitting , i...
A. Fonseca, J. Louçã - ECCS 2011
A. Fonseca, J. Louçã - ECCS 2011
Network modification through link randomization:                                     A. Fonseca, J. Louçã - ECCS 2011
‣ Better similarity (lower degree between multidimentional vectors) on lowerrandomizations and on lattice..‣ There seems t...
‣ Greater media coverages increase cosine similarity.‣ Greater dependency on the lattice network.                         ...
‣ Large influence at 100% (k = 1) delayed impact in Legislatives. Dayafter debate? Need validation from content analysis.‣...
Multi-agent model conclusions:• Cosine similarity between agent expression and real community is high.• Expression is subj...
Future Work:• To better qualify topology dependance.• The role of Sij and Pij parameters.• Examine other stimulus selectio...
Some references: [Latané, B, 1981] Latané, B. (1981). The psychology of social impact, American Psychologist 36, 343-356. ...
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ECCS

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ECCS

  1. 1. Opinion Dynamics ModellingSocial Impact Theory and the 2011 Portuguese Elections A. Fonseca, J. Louçã - ECCS 2011
  2. 2. Summary:• Online social network data on 2011 portuguese elections• Social impact theory• Multi-agent based modelling• Data validation• Conclusions A. Fonseca, J. Louçã - ECCS 2011
  3. 3. Online data collection:• Data collected between the 30th October 2010 and the 21th of January 2011 andbetween 27 March and the 6th of June 2011.• Community of 1903 Twitter users after data cleaning.• Set of 44 news feeds from media on Twitter (TV, Journals, Radio).• Data filtered though a set of keywords.• Average of circa 200 daily tweets.• Complete tweets collected. In this study we use: • daily_quantity_of_tweets(candidate) • daily_quantity_of_tweets(party)• Analysis of expression magnitude instead of expression content.• Data available at http://www.theobservatorium.eu/elections. A. Fonseca, J. Louçã - ECCS 2011
  4. 4. Presidential elections:• Six Candidates• Final Results: Candidate Result Cavaco 53,14% Alegre 19,67% Nobre 14,04% Lopes 7,05% Moura 4,52% Coelho 1,58% A. Fonseca, J. Louçã - ECCS 2011
  5. 5. A. Fonseca, J. Louçã - ECCS 2011
  6. 6. Final Results:A. Fonseca, J. Louçã - ECCS 2011
  7. 7. A. Fonseca, J. Louçã - ECCS 2011
  8. 8. Final Results:A. Fonseca, J. Louçã - ECCS 2011
  9. 9. Polls:A. Fonseca, J. Louçã - ECCS 2011
  10. 10. Covariance between community and media tweets A. Fonseca, J. Louçã - ECCS 2011
  11. 11. Legislative elections:• Five major parties• Final Results*: Party Result PSD 41,19% PS 30,42% CDS/PP 12,72% CDU 8,61% BE 5,69%*After normalization between major parties A. Fonseca, J. Louçã - ECCS 2011
  12. 12. A. Fonseca, J. Louçã - ECCS 2011
  13. 13. Final Results:A. Fonseca, J. Louçã - ECCS 2011
  14. 14. A. Fonseca, J. Louçã - ECCS 2011
  15. 15. Final Results:A. Fonseca, J. Louçã - ECCS 2011
  16. 16. Polls:A. Fonseca, J. Louçã - ECCS 2011
  17. 17. Covariance between community and media tweets A. Fonseca, J. Louçã - ECCS 2011
  18. 18. Experimental data conclusions:• Users tend to tweet proportionaly to the quantity of news.• Users tend to tweet about the news of the same day.• The relative magnitude of tweeting between candidates/parties is similar to the resultsobtained from classical pools (telephone, presential), with less accuracy however.• The final election results can roughly be estimated by the magnitude of twitting eitherfrom common users or the news media. [Véronis J., 2007] [Tumasjan A. et al, 2010] A. Fonseca, J. Louçã - ECCS 2011
  19. 19. Social Impact Modelling A. Fonseca, J. Louçã - ECCS 2011
  20. 20. [Latané B., 1981]A. Fonseca, J. Louçã - ECCS 2011
  21. 21. Model of political debate:• Media influences agents, agents influence each other.• Each agent has propensity or aversion ( ) for expressing about certain candidate/party of +1 or -1 respectively.• Each agent has a potential of supportiveness and persuasiveness that is the same foreach of its neighbors and that have a Normal probability distribution over the set ofagents.• Agent i talks about A if the impact on agent i about A is above average in relation toall the other impacts (about B, C, ...).• The news media acts as an autonomous agent over a fraction of agents on thecommunity with zero supportiveness and equal persuasiveness towards its audience. A. Fonseca, J. Louçã - ECCS 2011
  22. 22. Simulation - 1 run legislatives A. Fonseca, J. Louçã - ECCS 2011
  23. 23. Results Analysis A. Fonseca, J. Louçã - ECCS 2011
  24. 24. Experimental validation:• Agent community as real community (1903 users, 46423 links).• Input stimulus, media twitting , is given to 10% of agents (~190 agents).• Media twitting is processed as normal inter-agent stimulus processing.• Average of 20 runs.• Benchmark: ‣ The cosine similarity between MABS ‘twitting’ and real community tweets.• Variants: ‣ Network topology (random link rewiring and lattice network) ‣ Media coverage (percentage of media receptors) ‣ Lagged impact (lagged positive or negative aditional social impact) A. Fonseca, J. Louçã - ECCS 2011
  25. 25. A. Fonseca, J. Louçã - ECCS 2011
  26. 26. A. Fonseca, J. Louçã - ECCS 2011
  27. 27. Network modification through link randomization: A. Fonseca, J. Louçã - ECCS 2011
  28. 28. ‣ Better similarity (lower degree between multidimentional vectors) on lowerrandomizations and on lattice..‣ There seems to be a worst case at randomization 50% but overall there is no significantdependency on topology.‣ Lattice network has a good performance on news reproduction as agents discuss withlesser agents (avrg degree ~ 4).‣ Network ‘hub’ tends to impose its opinion over the community [Atay F., 2006]. A. Fonseca, J. Louçã - ECCS 2011
  29. 29. ‣ Greater media coverages increase cosine similarity.‣ Greater dependency on the lattice network. A. Fonseca, J. Louçã - ECCS 2011
  30. 30. ‣ Large influence at 100% (k = 1) delayed impact in Legislatives. Dayafter debate? Need validation from content analysis.‣ Uncharacteristic at Presidentials. A. Fonseca, J. Louçã - ECCS 2011
  31. 31. Multi-agent model conclusions:• Cosine similarity between agent expression and real community is high.• Expression is subject to an internal ‘subjective’ election replicated at community scale.• Simulation similarity with real tweets not dependent on expression magnitude.• Good difusion of media information.• Non uniform influence of delayed impact of discussion.• Dependence on the network topology. ‣ Hub nodes tend to influence community debates. ‣ Debate on ‘lattice’ tend to replicate know information from media. ‣ Scale-free seems to be most favorable topology for debate influence on overall community. A. Fonseca, J. Louçã - ECCS 2011
  32. 32. Future Work:• To better qualify topology dependance.• The role of Sij and Pij parameters.• Examine other stimulus selection mechanism other than ‘greather than average’.• Content analysis. A. Fonseca, J. Louçã - ECCS 2011
  33. 33. Some references: [Latané, B, 1981] Latané, B. (1981). The psychology of social impact, American Psychologist 36, 343-356. [Atay, F. 2006] Atay, F. M., T. Biyikoglu, and J. Jost, Synchronization of networks with prescribed degree, IEEE Trans. Circuits Syst. I 53(1):92–98 (2006). [Tumasjan et al, 2010] Tumasjan, A., Sprenger, T. O., Sandner, P. G., and Welpe, I. M. (2010). Predicting Elections with Twitter : What 140 Characters Reveal about Political Sentiment. In Word Journal Of The International Linguistic Association, pages 178–185. [Véronis, 2007] Véronis, J. (2007).Citations dans la presse et résultats du premier tour de la présidentielle 2007. Technical report. Castellano, C., Fortunato, S, and Loreto, V. (2007). Statistical physics of social dynamics. Reviews of Modern Physics, pages 1-58. Connor, B. O. Balasubramanyam, R., Routledge, B. R. And Smitth, N.A. (2010) From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. In 4th Internation AAAI Conference on Weblogs and Social Media, number May. Gayo-avello, D. (2011). Limits of Electoral Predictions using Twitter. In ICSWSM-11 Barcelona, Spain. Ghosh, R. And Lerman, K. (2010). Predicting Influential Users in Online Social Networks. In 4th SNA-KDD Workshop at 16th ACM SIGKDD. Holyst, J. A., Kacpersky, K., and Scheitzer, F. (2001). Social impact models of opinion dynamics. Annual Reviews of Computational Physics, 48(22):253-273. A. Fonseca, J. Louçã - ECCS 2011

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