A presentation for my social media class at the University of Nebraska-Omaha on the topic of polarization on social media, and the effects of echo chambers on online political discussions
2. Polarization on Social Media:
Echo Chambers and Their Effects on Online Political Discussions
Cecilie Larsen
December 6, 2018
University of Nebraska-Omaha
Professor Jeremy H. Lipschultz
JMC 8046 – Social Media Measurement and Management
3. OVERVIEW
• Contextualization
• Research questions
• Polarization
o Echo chambers
o Measurement of polarization
• Analysis of polarization
using NodeXL
• The effect of polarization on
online discussions
o Media bias
o Public opinion
o Effects on democracy
o Polarization gets personal
• Conclusion
4. CONTEXTUALIZATION
• Social media has shifted content creation, from a
publisher-centric model to a user-centric model
• Social media and news consumption
o More convenient access to political information
o Social media networks provide platforms to discuss politics
• Polarized crowds within the social media networks
Sources:
Quesenberry, K. (2019)
5. RESEARCH QUESTIONS
Research Question 1:
To what extent do “filter bubbles” contribute to the
polarized crowd structure in social media
conversations?
Research Question 2:
How do polarization and echo chambers affect online
political discussions?
6. POLARIZATION
• Polarization is a social process where a social group
is divided into two opposite sub-groups that have
conflicting and contradicting views, goals or opinions.
o The two sub-groups leave out very few, meaning other people
with a neutral or in-between position.
o There is very little interaction or bridging between the two
sub-groups
o Topics of discussions are usually highly divisive and on heated
political issues
Sources:
Guerra, P., Meira Jr., W., Cardie, C., & Kleinberg, R. (2013)
Smith, M., Rainie, L., Shneiderman, B., & Himelboim, I. (2014, February
7. POLARIZATION
• In the US, the two polarized crowds can be labeled
‘conservative’ and ‘liberal’
o The two crowds only represent a small fraction of all the
conversations
o Twitter-users: only 20 % of Internet users
o Twitter-users are more liberal than the overall population
• Polarization contributes to segregation and political
conflicts
Sources:
Guerra, P., Meira Jr., W., Cardie, C., & Kleinberg, R. (2013)
Smith, M., Rainie, L., Shneiderman, B., & Himelboim, I. (2014, February
8. Why should polarization matter to us, as students of
Social Media Management and Measurement and
future Social Media Managers and Consultants?
9. Because a biased social media user is more likely
to maintain his or her view over time, and prior
online behavior can predict future behavior.
Sources:
Guerra, P., Meira Jr., W., Cardie, C., & Kleinberg, R. (2013)
10. ECHO CHAMBERS
• The environment in which you surround yourself with
content that is ideologically pleasing, is called an
echo chamber.
• People tend to expose themselves selectively to
sources of information that reinforce their existing
views.
• Echo chambers online are like “filter bubbles” that
insulate the user from contrary views.
Sources:
Barbera, P., Jost, J., Nagler, J., Tucker, J., & Bonneau, R. (2015)
Allcott, H., & Gentzkow, M. (2017)
11. ECHO CHAMBERS
• The structure of social media differ from traditional
media
o Users can publish content without editorialization
o Unedited, content that has not been fact checked can reach far
beyond a user’s immediate social network
• Filter bubbles or echo chambers can form where
people actively monitor or seek information that
reinforces their beliefs
Sources:
Allcott, H., & Gentzkow, M. (2017)
Flaxman, S., Goel, S., & Rao, J. (2016)
12. ECHO CHAMBERS
• Personalization of online content
o Search engines, social media networks, news channels
o Machine-learning and algorithms
• Amplify political segregation (polarization) by
suggesting content that reinforces existing beliefs
Sources:
Flaxman, S., Goel, S., & Rao, J. (2016)
13. “THE POLARIZED CROWD”
• Polarized groups do not interact
• Ignoring other groups by referring to their own
content, hashtags and news sources
• Easier to predict a person’s position on an issue, given
that we know their party affiliation
Sources:
Smith, M., Rainie, L., Shneiderman, B., & Himelboim, I. (2014)
Bail, C., Argyle, L., Brown, T., Bumpus, J., Chen, H., Hunzaker, M.,
Volfovsky, A. (2018)
14. MEASUREMENT OF POLARIZATION
• Modularity
o Information on ties between people in the network, and
compare the strength of ties within each group to the total
strength between members of different groups in the network
o Can identify “communities” which is based on the intuitive
concept of having stronger ties within your group than with
people outside your group
o Higher levels of modularity imply stronger polarization
between groups in the network
Sources:
Waugh, A., Pei, L., Fowler, J., Mucha, P., & Porter, M. (2012)
15. MEASUREMENT OF POLARIZATION
• Partisan animosity
o Increased over time
• 72 % of ”consistently conservative” have a ”very
unfavorable view” of Democrats
• 53 % of “consistently liberal” have a “very unfavorable view
of Republicans
Sources:
Pew Research Center. (2014).
21. EFFECTS OF POLARIZATION
• Sub-groups rely on similar news sources
• Differences between platforms
o Facebook
o Twitter
Sources:
Smith, M., Rainie, L., Shneiderman, B., & Himelboim, I. (2014)
Duggan, M., & Smith, A. (2016)
23. MEDIA BIAS
• Impacts the quality of online discussions
• Intensifies echo chambers and “filter bubbles”
• Media’s power to shape the public discourse through
agenda setting
• Political polarization connected to the information
environment of an individual
Sources:
Smith, M., Rainie, L., Shneiderman, B., & Himelboim, I. (2014)
Pew Research Center. (2014)
24. PUBLIC OPINION
• Online polarization and partisan hostility leads to
frustration
• 37 % of social media users are “worn out by how
many political posts and discussions they see”
• 59 % said they found it “stressful and frustrating” to
discuss politics with people they disagree with
Sources:
Duggan, M., & Smith, A. (2016)
25. POLARIZATION AND ITS EFFECT
ON DEMOCRACY
• If people avoid public discourse due to increased
polarization and partisan hostility, it could potentially
harm our democracy
• Twitter will have an increasingly important role as
news source going forward
• Polarization and media bias will shape how we
consume, and accept or reject news
Sources:
Bail, C., Argyle, L., Brown, T., Bumpus, J., Chen, H., Hunzaker, M.,
Volfovsky, A. (2018)
Garrett, R. (2009)
Duggan, M., & Smith, A. (2016)
27. CONCLUSION
RQ1: ”Filter bubbles” insulate online users from contrary
views, and media bias contributes to the reinforcement
of users’ own beliefs
• ”Filter bubbles” do to a certain extent facilitate the
polarized crowd structure on social media
RQ2: Polarization and echo chambers have a negative
impact on online political discussions
• Polarization and partisan hostility have increased
29. BIBLIOGRAPHY
Ad Fontes Media. (2018, August 28). Media Bias Chart 4.0. Retrieved from Ad Fontes Media:
https://www.adfontesmedia.com/wp-content/uploads/2018/08/Media-Bias-Chart_4.0_8_28_2018-min.jpg
Allcott, H., & Gentzkow, M. (2017). Social Media and Fake News in the 2016 Election. Journal of Economic
Perspectives, 31(2), 211-236.
Bail, C., Argyle, L., Brown, T., Bumpus, J., Chen, H., Hunzaker, M., . . . Volfovsky, A. (2018). Exposure to opposing
views on social media can increase political polarization. Proceedings of the National Academy of Sciences of
the United States of America.
Barbera, P., Jost, J., Nagler, J., Tucker, J., & Bonneau, R. (2015). Tweeting From Left to Right: Is Online Political
Communication More Than an Echo Chamber? Psychological Science, 1-12.
Duggan, M., & Smith, A. (2016, October 25). The Political Environment on Social Media. Retrieved from Pew
Internet: http://www.pewinternet.org/2016/10/25/the-political-environment-on-social-media/
Flaxman, S., Goel, S., & Rao, J. (2016). Filter bubbles, echo chambers and online news consumption. Public
Opinion Quarterly, 298-320.
30. BIBLIOGRAPHY
Guerra, P., Meira Jr., W., Cardie, C., & Kleinberg, R. (2013). A Measure of Polarization on Social Media Networks
Based on Community Boundaries. Association for the Advancement of Artificial Intelligence.
Garrett, R. (2009). Echo chambers online?: Politically motivated selective exposure among Internet news users.
Journal of Computer-Mediated Communication, 265-285.
NodeXL. (2018, October 18). @karaforcongress Twitter NodeXL SNA Map and Report. Retrieved from NodeXL
Graph Gallery: http://nodexlgraphgallery.org/Images/Image.ashx?graphID=171805&type=f
Pew Research Center. (2014). Political Polarization in the American Public. Pew Research center.
Quesenberry, K. (2019). Social Media Strategy. Lanham, MD: Rowman & Littlefield.
Smith, M., Rainie, L., Shneiderman, B., & Himelboim, I. (2014, February 20). Mapping Twitter Topic Networks:
From Polarized Crowds to Community Clusters. Retrieved from Pew Internet:
http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-
community-clusters/
Waugh, A., Pei, L., Fowler, J., Mucha, P., & Porter, M. (2012). Party Polarization in Congress: A Network Science
Approach.
