The Co-retweeted Network and Its Applications for Measuring the Perceived Political Polarization

Samantha Finn, Eni Mustafaraj, Panagiotis T. Metaxas

2014

Abstract

This paper introduces a novel network, the co-retweeted network, that is constructed as the undirected weighted graph that connects highly visible accounts who have been retweeted by members of the audience during some real-time event. Like bibliographics co-citation used to indicate that two papers treat a related subject matter, co-retweeting is used to indicate that two accounts present similar opinions in an online discussion. Thus, the co-retweeted network can be seen as a form of consulting the opinion of the crowd that is following the discussion about the similarity (or difference) of positions expressed by the highly visible accounts. When applied on political conversations related to some event, the co-retweeted network enables the measurement of the polarity of political orientation of major players (including news organizations) based on the views of the audience. It can also measure the degree of polarization of the event itself.

References

  1. Adamic, L. A. and Glance, N. (2005). The political blogosphere and the 2004 US election: divided they blog. In Proc. of the 3rd Intl workshop on Link discovery, pages 36-43.
  2. Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 10.
  3. Cohen, R. and Ruths, D. (2013). Classifying political orientation on twitter: Its not easy! In Proc. of 7th ICWSM. AAAI.
  4. Conover, M. D., Gonc¸alves, B., Ratkiewicz, J., Flammini, A., and Menczer, F. (2011). Predicting the political alignment of twitter users. In 2011 3rd IEEE SocialCom, pages 192-199.
  5. Diakopoulos, N. and Shamma, D. A. (2010). Characterizing debate performance via aggregated twitter sentiment. In CHI, pages 1195-1198.
  6. Finn, S. and Mustafaraj, E. (2013). Visualizing co-retweeting behavior for recommending relevant real-time content. In Proc. of the 4th Intl Workshop on Modeling Social Media, MSM 7813, pages 4:1-4:2. ACM.
  7. Fiorina, M. P. and Abrams, S. J. (2008). Political polarization in the american public. Annual Review of Political Science, 11:563-588.
  8. Fruchterman, T. M. J. and Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21:1129- 1164.
  9. Gephi (2010). ForceAtlas2, the new version of our home-brew layout. http://bit.ly/1deeWht.
  10. Gerlitz, C. and Rieder, B. (2013). Mining one percent of twitter: Collections, baselines, sampling. M/C Journal, 16(2).
  11. Golbeck, J. and Hansen, D. (2011). Computing political preference among twitter followers. In Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, CHI 7811, pages 1105-1108, New York, NY, USA. ACM.
  12. Golbeck, J. and Hansen, D. (2014). A method for computing political preference among twitter followers. Social Networks, 36:177-184.
  13. Jungherr, A., Jürgens, P., and Schoen, H. (2012). Why the pirate party won the german election of 2009 or the trouble with predictions: A response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. “Predicting elections with Twitter: What 140 characters reveal about political sentiment”. Social Science Computer Review, 30(2):229-234.
  14. Metaxas, P. T. and Mustafaraj, E. (2010). From obscurity to prominence in minutes: Political speech and real-time search. In Proc. of the WebSci10: Extending the Frontiers of Society OnLine, April 26-27th, 2010, WebScience'10.
  15. Morstatter, F., Pfeffer, J., Liu, H., and Carley, K. M. (2013). Is the sample good enough? comparing data from twitters streaming api with twitters firehose. Proceedings of ICWSM.
  16. Mustafaraj, E., Finn, S., Whitlock, C., and Metaxas, P. T. (2011). Vocal minority versus silent majority: Discovering the opinions of the long tail. In Proc. of 3rd IEEE SocialCom, pages 103-110. IEEE.
  17. Pew Research Center for the People and the Press (2012). Partisan polarization surges in bush, obama years. http://bit.ly/1d2HZK6.
  18. Prior, M. (2013). Media and political polarization. Annual Review of Political Science, 16:101-127.
  19. Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proc. of the 10th WWW, pages 285-295. ACM.
  20. Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24:265-269.
  21. Suh, B., Hong, L., Pirolli, P., and Chi, E. H. (2010). Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. In 2010 2nd IEEE SocialCom, pages 177-184. IEEE.
  22. von Ahn, L., Liu, R., and Blum, M. (2006). Peekaboom: a game for locating objects in images. In Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, CHI 7806, pages 55-64, New York, NY, USA. ACM.
  23. Wellesley Trails Group (2014). Retweets indicate agreement, endorsement, trust: A meta-analysis of published twitter research. Forthcoming.
Download


Paper Citation


in Harvard Style

Finn S., Mustafaraj E. and T. Metaxas P. (2014). The Co-retweeted Network and Its Applications for Measuring the Perceived Political Polarization . In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-023-9, pages 276-284. DOI: 10.5220/0004788702760284


in Bibtex Style

@conference{webist14,
author={Samantha Finn and Eni Mustafaraj and Panagiotis T. Metaxas},
title={The Co-retweeted Network and Its Applications for Measuring the Perceived Political Polarization},
booktitle={Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2014},
pages={276-284},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004788702760284},
isbn={978-989-758-023-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - The Co-retweeted Network and Its Applications for Measuring the Perceived Political Polarization
SN - 978-989-758-023-9
AU - Finn S.
AU - Mustafaraj E.
AU - T. Metaxas P.
PY - 2014
SP - 276
EP - 284
DO - 10.5220/0004788702760284