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A Twitter-Based Analysis Of Hashtag And Mention Actions As An İndicator Of Turkish General Elections’ Outcomes

Year 2020, Issue: 33, 73 - 90, 30.06.2020
https://doi.org/10.31123/akil.619691

Abstract

Social media provides a
large-scale data that have substantial prospective to define collective actions
such as social trends, political participation and complex phenomena in real
world. When people use these channels, they leave a huge amount of digital
trace that can be easily reached by researchers. This digital trace bestows us
a unique possibility to observe and reveal collective actions at unpreceded
measures. In this research,
we have aimed to test if
the daily Twitter activities (tweet, retweet, mention) can serve as a
significant indicator regarding Turkish election results, an argument already
engaged in previous studies.
We have concluded that some of our results overlap
with previous studies. The correlation between the daily attention volume on
acquired in this study and the election results –even though it does not
directly impact the election results– shows Turkish Twitter data can be used as
a proxy tool.

Supporting Institution

The Scientific and Technological Research Council of Turkey

Project Number

A-2214

Thanks

I gratefully acknowledge the support of The Scientific and Technological Research Council of Turkey (2214-A).

References

  • Aral, Sinan. 2012. “Social Science: Poked to Vote.” Nature 489 (7415): 212–14. https://doi.org/10.1038/489212a.
  • Bond, Robert M., Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle, and James H. Fowler. 2012. “A 61-Million-Person Experiment in Social Influence and Political Mobilization.” Nature 489 (September): 295–98. https://doi.org/10.1038/nature11421.
  • Borondo, J., A. J. Morales, J. C. Losada, and R. M. Benito. 2012. “Characterizing and Modeling an Electoral Campaign in the Context of Twitter: 2011 Spanish Presidential Election as a Case Study.” Chaos: An Interdisciplinary Journal of Nonlinear Science 22: 023138. https://doi.org/10.1063/1.4729139.
  • Brundidge, Jennifer. 2010. “Encountering ‘Difference’ in the Contemporary Public Sphere: The Contribution of the Internet to the Heterogeneity of Political Discussion Networks.” Journal of Communication 60 (4): 680–700. https://doi.org/10.1111/j.1460-2466.2010.01509.x.
  • Budak, Ceren, and Duncan Watts. 2015. “Dissecting the Spirit of Gezi: Influence vs. Selection in the Occupy Gezi Movement.” Sociological Science 2: 370–97. https://doi.org/10.15195/v2.a18.
  • Caldarelli, Guido, Alessandro Chessa, Fabio Pammolli, Gabriele Pompa, Michelangelo Puliga, Massimo Riccaboni, and Gianni Riotta. 2014. “A Multi-Level Geographical Study of Italian Political Elections from Twitter Data.” Edited by Matjaz Perc. PLoS ONE 9 (May): e95809. https://doi.org/10.1371/journal.pone.0095809.
  • DiGrazia, Joseph, Karissa McKelvey, Johan Bollen, and Fabio Rojas. 2013. “More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior.” Edited by Luis M. Martinez. PLoS ONE 8 (November): e79449. https://doi.org/10.1371/journal.pone.0079449.
  • Eom, Young-Ho, Michelangelo Puliga, Jasmina Smailović, Igor Mozetič, and Guido Caldarelli. 2015. “Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties.” Edited by Matjaz Perc. PLOS ONE 10 (July): e0131184. https://doi.org/10.1371/journal.pone.0131184.
  • Ferguson, William D. 2013. Collective Action and Exchange: A Game-Theoretic Approach to Contemporary Political Economy. Stanford, CA: Stanford University Press.
  • Gayo-Avello, Daniel. 2013. “A Meta-Analysis of State-of-the-Art Electoral Prediction from Twitter Data.” Social Science Computer Review 31 (6): 649–79. https://doi.org/10.1177/0894439313493979.
  • Kwon, K. Hazel, Michael A. Stefanone, and George A. Barnett. 2014. “Social Network Influence on Online Behavioral Choices Exploring Group Formation on Social Network Sites.” American Behavioral Scientist 58: 1345–1360.
  • Lee, Jae Kook, Jihyang Choi, Cheonsoo Kim, and Yonghwan Kim. 2014. “Social Media, Network Heterogeneity, and Opinion Polarization.” Journal of Communication 64 (August): 702–22. https://doi.org/10.1111/jcom.12077.
  • Metcalfe, G., M.F.M. Speetjens, D.R. Lester, and H.J.H. Clercx. 2012. “Beyond Passive: Chaotic Transport in Stirred Fluids.” In Advances in Applied Mechanics, edited by Erik Van der Giessen and Hassan Aref, 45:109–88. San Diego, CA: Elsevier. https://doi.org/10.1016/B978-0-12-380876-9.00004-5.
  • Minto, Rob. 2013. “Twitter’s EM Uphill Battle.” Financial Times. October 4, 2013. http://blogs.ft.com/beyond-brics/2013/10/04/twitter-who-are-the-77/.
  • PEW. 2012. “Social Networking Popular across Globe.” Pew Research Center’s Global Attitudes Project (blog). December 12, 2012. http://www.pewglobal.org/2012/12/12/social-networking-popular-across-globe/.
  • Romero, Daniel M., Wojciech Galuba, Sitaram Asur, and Bernardo A. Huberman. 2011. “Influence and Passivity in Social Media.” In 20th International Conference Companion on World Wide Web, 113–14. New York, NY: ACM Press. https://doi.org/10.1145/1963192.1963250.
  • Varol, Onur, Emilio Ferrara, Christine L. Ogan, Filippo Menczer, and Alessandro Flammini. 2014. “Evolution of Online User Behavior during a Social Upheaval.” In , 81–90. ACM Press. https://doi.org/10.1145/2615569.2615699.

A Twitter-Based Analysis Of Hashtag And Mention Actions As An İndicator Of Turkish General Elections’ Outcomes

Year 2020, Issue: 33, 73 - 90, 30.06.2020
https://doi.org/10.31123/akil.619691

Abstract

Sosyal medya; gerçek dünyadaki sosyal eğilimleri, siyasi katılım ve gösteriler gibi kolektif eylemleri tanımlamak için önemli ve geniş çaplı bir veri sunmaktadır. İnsanlar bu kanalları kullandıklarında, araştırmacılar tarafından kolayca ulaşılabilecek büyük miktarda dijital iz bırakmaktadırlar. Bu dijital iz, kolektif eylemleri gözlemleme ve ortaya çıkarma konusunda araştırmacılara eşsiz bir imkân sunmaktadır. Bu araştırma, günlük Twitter aktivitelerinin (tweet, retweet, mention), birçok çalışmada ele alındığı gibi, Türkiye seçim sonuçlarına ilişkin önemli bir gösterge olup olmadığını test etmeyi amaçlamıştır. Bunu test etmek için, Eom ve arkadaşları (2015) tarafından günlük tweet hacmine dayalı olarak değişkenlerin sırasını tahmin etmek için geliştirilen bir yöntem seçilerek uygulanmıştır. Partilerin ve adayların tahmini sıralamasında en uygun zaman aralığını bulmak için günlük tweet hacimlerindeki dalgalanmalar kullanılmıştır. Çalışma sonucunda, elde edilen sonuçlardan bazılarının önceki çalışmalarla örtüştüğü görülmüştür. Bu çalışma sonucunda elde edilen günlük ilgi miktarı ile seçim sonuçları arasındaki korelasyon –seçim sonuçlarını doğrudan etkilemese de– Türkiye’de Twitter verilerinin bir gösterge olarak kullanılabileceğini göstermiştir.

Project Number

A-2214

References

  • Aral, Sinan. 2012. “Social Science: Poked to Vote.” Nature 489 (7415): 212–14. https://doi.org/10.1038/489212a.
  • Bond, Robert M., Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle, and James H. Fowler. 2012. “A 61-Million-Person Experiment in Social Influence and Political Mobilization.” Nature 489 (September): 295–98. https://doi.org/10.1038/nature11421.
  • Borondo, J., A. J. Morales, J. C. Losada, and R. M. Benito. 2012. “Characterizing and Modeling an Electoral Campaign in the Context of Twitter: 2011 Spanish Presidential Election as a Case Study.” Chaos: An Interdisciplinary Journal of Nonlinear Science 22: 023138. https://doi.org/10.1063/1.4729139.
  • Brundidge, Jennifer. 2010. “Encountering ‘Difference’ in the Contemporary Public Sphere: The Contribution of the Internet to the Heterogeneity of Political Discussion Networks.” Journal of Communication 60 (4): 680–700. https://doi.org/10.1111/j.1460-2466.2010.01509.x.
  • Budak, Ceren, and Duncan Watts. 2015. “Dissecting the Spirit of Gezi: Influence vs. Selection in the Occupy Gezi Movement.” Sociological Science 2: 370–97. https://doi.org/10.15195/v2.a18.
  • Caldarelli, Guido, Alessandro Chessa, Fabio Pammolli, Gabriele Pompa, Michelangelo Puliga, Massimo Riccaboni, and Gianni Riotta. 2014. “A Multi-Level Geographical Study of Italian Political Elections from Twitter Data.” Edited by Matjaz Perc. PLoS ONE 9 (May): e95809. https://doi.org/10.1371/journal.pone.0095809.
  • DiGrazia, Joseph, Karissa McKelvey, Johan Bollen, and Fabio Rojas. 2013. “More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior.” Edited by Luis M. Martinez. PLoS ONE 8 (November): e79449. https://doi.org/10.1371/journal.pone.0079449.
  • Eom, Young-Ho, Michelangelo Puliga, Jasmina Smailović, Igor Mozetič, and Guido Caldarelli. 2015. “Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties.” Edited by Matjaz Perc. PLOS ONE 10 (July): e0131184. https://doi.org/10.1371/journal.pone.0131184.
  • Ferguson, William D. 2013. Collective Action and Exchange: A Game-Theoretic Approach to Contemporary Political Economy. Stanford, CA: Stanford University Press.
  • Gayo-Avello, Daniel. 2013. “A Meta-Analysis of State-of-the-Art Electoral Prediction from Twitter Data.” Social Science Computer Review 31 (6): 649–79. https://doi.org/10.1177/0894439313493979.
  • Kwon, K. Hazel, Michael A. Stefanone, and George A. Barnett. 2014. “Social Network Influence on Online Behavioral Choices Exploring Group Formation on Social Network Sites.” American Behavioral Scientist 58: 1345–1360.
  • Lee, Jae Kook, Jihyang Choi, Cheonsoo Kim, and Yonghwan Kim. 2014. “Social Media, Network Heterogeneity, and Opinion Polarization.” Journal of Communication 64 (August): 702–22. https://doi.org/10.1111/jcom.12077.
  • Metcalfe, G., M.F.M. Speetjens, D.R. Lester, and H.J.H. Clercx. 2012. “Beyond Passive: Chaotic Transport in Stirred Fluids.” In Advances in Applied Mechanics, edited by Erik Van der Giessen and Hassan Aref, 45:109–88. San Diego, CA: Elsevier. https://doi.org/10.1016/B978-0-12-380876-9.00004-5.
  • Minto, Rob. 2013. “Twitter’s EM Uphill Battle.” Financial Times. October 4, 2013. http://blogs.ft.com/beyond-brics/2013/10/04/twitter-who-are-the-77/.
  • PEW. 2012. “Social Networking Popular across Globe.” Pew Research Center’s Global Attitudes Project (blog). December 12, 2012. http://www.pewglobal.org/2012/12/12/social-networking-popular-across-globe/.
  • Romero, Daniel M., Wojciech Galuba, Sitaram Asur, and Bernardo A. Huberman. 2011. “Influence and Passivity in Social Media.” In 20th International Conference Companion on World Wide Web, 113–14. New York, NY: ACM Press. https://doi.org/10.1145/1963192.1963250.
  • Varol, Onur, Emilio Ferrara, Christine L. Ogan, Filippo Menczer, and Alessandro Flammini. 2014. “Evolution of Online User Behavior during a Social Upheaval.” In , 81–90. ACM Press. https://doi.org/10.1145/2615569.2615699.
There are 17 citations in total.

Details

Primary Language English
Subjects Communication and Media Studies
Journal Section Articles
Authors

Enes Abanoz 0000-0002-4250-1845

Project Number A-2214
Publication Date June 30, 2020
Submission Date September 13, 2019
Published in Issue Year 2020 Issue: 33

Cite

APA Abanoz, E. (2020). A Twitter-Based Analysis Of Hashtag And Mention Actions As An İndicator Of Turkish General Elections’ Outcomes. Akdeniz Üniversitesi İletişim Fakültesi Dergisi(33), 73-90. https://doi.org/10.31123/akil.619691