Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Mapping the Political Landscape on Social Media Using Bibliometrics: : A Longitudinal Co-Word Analysis on Twitter and Facebook Publications Published Between 2012 and 2021

Published: 01 October 2023 Publication History

Abstract

Topics such as disinformation, misinformation, political polarization, and populism are frequently discussed in the social media literature. The purpose of this article is to investigate how the political emphasis on social media has evolved in the academic publications published in the last decade. Thus, using co-word analysis of the social science articles published between 2012 and 2021, which discuss politically about Facebook or Twitter (N = 3389), this article investigates whether certain major and unexpected political events—such as Donald Trump’s presidential victory and the Brexit referendum—have influenced in any way the knowledge field related to social media publications. Thus, the 2017–2021 map brings new and popular words, such as “Covid-19,” which is associated in similar clusters with words such as disinformation, fake news, and infodemic. Furthermore, the emergence of the word “Russia” places it in a common cluster with words such as bots, elections, and agenda-setting. Also, the Twitter map, unlike the Facebook one, brings a particular emphasis on Donald Trump’s activity, which appears in clusters that are similar to topics that brought him popularity on Twitter, such as: meme, migration, and refugees. Such bibliometric associations should increase policymakers’ attention to the potential use of social media as a political tool, along with designing the solutions to limit such intrusions into future political events.

References

[1]
Akkerman A., Mudde C., and Zaslove A. (2014). How populist are the people? Measuring populist attitudes in voters. Comparative Political Studies, 47(9), 1324–1353. https://doi.org/10.1177/0010414013512600
[2]
Alexandre I., Jai-sung Yoo J., and Murthy D. (2021). Make tweets great again: Who are opinion leaders, and what did they tweet about Donald Trump? Social Science Computer Review. https://doi.org/10.1177/08944393211008859
[3]
Alvares C. and Dahlgren P. (2016). Populism, extremism and media: Mapping an uncertain terrain. European Journal of Communication, 31(1), 46–57. https://doi.org/10.1177/0267323115614485
[4]
Alves H., Fernandes C., and Raposo M. (2016). Social media marketing: A literature review and implications. Psychology & Marketing, 33(12), 1029–1038. https://doi.org/10.1002/mar.20936
[5]
Arroyo-Machado W., Torres-Salinas D., and Robinson-Garcia N. (2021). Identifying and characterizing social media communities: A socio-semantic network approach to altmetrics. Scientometrics, 126(11), 9267–9289. https://doi.org/10.1007/s11192-021-04167-8
[6]
Buccoliero L., Bellio E., Crestini G., and Arkoudas A. (2018). Twitter and politics: Evidence from the US presidential elections 2016. Journal of Marketing Communications, 26(1), 88–114. https://doi.org/10.1080/13527266.2018.1504228
[7]
Caiani M. and Graziano P. R. (2016). Varieties of populism: Insights from the Italian case. Italian Political Science Review/Rivista Italiana di Scienza Politica, 46(2), 243–267. https://doi.org/10.1017/ipo.2016.6
[8]
Crockett Z. (2016, May 16). What I learned analyzing 7 months of Donald Trump’s tweets. Vox. https://www.vox.com/2016/5/16/11603854/donald-trump-twitter (Accessed 23 December 2021).
[9]
Ellegaard O. (2018). The application of bibliometric analysis: Disciplinary and user aspects. Scientometrics, 116(1), 181–202. https://doi.org/10.1007/s11192-018-2765-z
[10]
Engesser S., Ernst N., Esser F., and Büchel F. (2017). Populism and social media: How politicians spread a fragmented ideology. Information, Communication & Society, 20(8), 1109–1126. https://doi.org/10.1080/1369118x.2016.1207697
[11]
Gabler N. (2016, September 28). Donald Trump, the emperor of social media. Moyers & Company. https://billmoyers.com/story/donald-trump-the-emperor-of-social-media/ (Accessed 21 December 2021).
[12]
Gebhardt M. (2019). The populist moment: Affective orders, protest, and politics of belonging. Distinktion: Journal of Social Theory, 22(2), 129–151. https://doi.org/10.1080/1600910x.2019.1653346
[13]
Gerbaudo P. (2018). Social media and populism: An elective affinity? Media, Culture & Society, 40(5), 745–753. https://doi.org/10.1177/0163443718772192
[14]
Goldie D., Linick M., Jabbar H., and Lubienski C. (2014). Using bibliometric and social media analyses to explore the “echo chamber” hypothesis. Educational Policy, 28(2), 281–305. https://doi.org/10.1177/0895904813515330
[15]
Hochschild A. R. (2016). Strangers in their own land: Anger and mourning on the American right. The New Press.
[16]
Hu C. P., Hu J. M., Deng S. L., and Liu Y. (2013). A co-word analysis of library and information science in China. Scientometrics, 97(2), 369–382. https://doi.org/10.1007/s11192-013-1076-7
[17]
Judis J. B. (2016). The populist explosion: How the great recession transformed American and European politics. Columbia Global Reports.
[18]
Khasseh A. A., Soheili F., Moghaddam H. S., and Chelak A. M. (2017). Intellectual structure of knowledge in iMetrics: A co-word analysis. Information Processing & Management, 53(3), 705–720. https://doi.org/10.1016/j.ipm.2017.02.001
[19]
Laclau E. (2005). On populist reason. Verso.
[20]
Leung X. Y., Sun J., and Bai B. (2017). Bibliometrics of social media research: A co-citation and co-word analysis. International Journal of Hospitality Management, 66, 35–45. https://doi.org/10.1016/j.ijhm.2017.06.012
[21]
Liu G. Y., Hu J. M., and Wang H. L. (2012). A co-word analysis of digital library field in China. Scientometrics, 91(1), 203–217. https://doi.org/10.1007/s11192-011-0586-4
[22]
Mazzoleni G. and Bracciale R. (2018). Socially mediated populism: The communicative strategies of political leaders on Facebook. Palgrave Communications, 4(1), 1–10. https://doi.org/10.1057/s41599-018-0104-x
[23]
Moore M. (2018). Democracy hacked: How technology is destabilizing global politics. Oneworld Publications.
[24]
Mouffe C. (2019). The populist moment. Simbiótica. Revista Eletrônica, 6(1), 06–11. https://doi.org/10.47456/simbitica.v6i1.27192
[25]
Mudde C. (2004). The populist zeitgeist. Government and Opposition, 39(4), 542–563. https://doi.org/10.1111/j.1477-7053.2004.00135.x
[26]
Mudde C. and Rovira Kaltwasser C. (2017). Populism: A very short introduction. Oxford University Press.
[27]
Muller J. W. (2016). What is populism? University of Pennsylvania Press.
[28]
Nagle A. (2017). Kill all normies: Online culture wars from 4Chan and Tumblr to Trump and the alt-right. Zero Books.
[29]
Obreja D. M. (2022). Increasingly dense and connected field: A longitudinal co-word analysis of youth sociological articles from 1990 to 2019. Youth, 2(2), 150–164. https://doi.org/10.3390/youth2020012
[30]
Ott B. L. (2017). The age of Twitter: Donald J. Trump and the politics of debasement. Critical Studies in Media Communication, 34(1), 59–68. https://doi.org/10.1080/15295036.2016.1266686
[31]
Perez S. (2018, October 30). Twitter’s doubling of characters count from 140 to 280 had little impact on length of tweets. TechCrunch+. https://techcrunch.com/2018/10/30/twitters-doubling-of-character-count-from-140-to-280-had-little-impact-on-length-of-tweets/ (Accessed 23 December 2021).
[32]
Postill J. (2018). Populism and social media: A global perspective. Media, Culture & Society, 40(5), 754–765. https://doi.org/10.1177/0163443718772186
[33]
Pritchard A. (1969). Statistical bibliography or bibliometrics. Journal of Documentation, 25(4), 348–349.
[34]
Ravikumar S., Agrahari A., and Singh S. N. (2015). Mapping the intellectual structure of scientometrics: A co-word analysis of the journal Scientometrics (2005–2010). Scientometrics, 102(1), 929–955. https://doi.org/10.1007/s11192-014-1402-8
[35]
Reiter-Haas M., Klösch B., Hadler M., and Lex E. (2022). Polarization of opinions on COVID-19 measures: Integrating Twitter and survey data. Social Science Computer Review. https://doi.org/10.1177/08944393221087662
[36]
Ronda-Pupo G. A. and Guerras-Martin L. Á. (2012). Dynamics of the evolution of the strategy concept 1962–2008: A co-word analysis. Strategic Management Journal, 33(2), 162–188. https://doi.org/10.1002/smj.948
[37]
Salimi D., Tavasoli K., Gilani E., Jouyandeh M., and Sadjadi S. (2019). The impact of social media on marketing using bibliometrics analysis. International Journal of Data and Network Science, 3(3), 165–184. https://doi.org/10.5267/j.ijdns.2019.2.006
[38]
Shafer J. (2015, August 13). Donald trump talks like a third-grader. Politico. https://www.politico.com/magazine/story/2015/08/donald-trump-talks-like-a-third-grader-121340/ (Accessed 23 December 2021).
[39]
Snyder T. (2018). The road to unfreedom. Russia, Europe, America. Tim Duggan Books.
[40]
Stieglitz S. and Dang-Xuan L. (2013). Emotions and information diffusion in social media – sentiment of microblogs and sharing behavior. Journal of Management Information Systems, 29(4), 217–247. https://doi.org/10.2753/mis0742-1222290408
[41]
Su H. N. and Lee P. C. (2010). Mapping knowledge structure by keyword co-occurrence: A first look at journal papers in Technology foresight. Scientometrics, 85(1), 65–79. https://doi.org/10.1007/s11192-010-0259-8
[42]
Thelwall M., Buckley K., and Paltoglou G. (2011). Sentiment in Twitter events. Journal of the American Society for Information Science and Technology, 62(2), 406–418. https://doi.org/10.1002/asi.21462
[43]
Tranfield D., Denyer D., and Smart P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375
[44]
Waltman L., Van Eck N. J., and Noyons E. C. (2010). A unified approach to mapping and clustering of bibliometric networks. Journal of Informetrics, 4(4), 629–635. https://doi.org/10.1016/j.joi.2010.07.002
[45]
Zeng B. and Gerritsen R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10, 27–36. https://doi.org/10.1016/j.tmp.2014.01.001
[46]
Zubiaga A., Spina D., Martinez R., and Fresno V. (2015). Real-time classification of Twitter trends. Journal of the Association for Information Science and Technology, 66(3), 462–473. https://doi.org/10.1002/asi.23186

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Social Science Computer Review
Social Science Computer Review  Volume 41, Issue 5
Oct 2023
443 pages

Publisher

Sage Publications, Inc.

United States

Publication History

Published: 01 October 2023

Author Tags

  1. bibliometrics
  2. co-word analysis
  3. disinformation
  4. populism
  5. social media
  6. Facebook
  7. Twitter
  8. Trump

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 13 Feb 2025

Other Metrics

Citations

View Options

View options

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media