Data Science: Case "Political Communication 1/2"

Introducing. . . Studying social media in poltical communication Conclusion

Fundamentals of Data Science: Case “PoliticalCommunication”

Damian Trilling

[email protected]@damian0604

www.damiantrilling.net

Afdeling CommunicatiewetenschapUniversiteit van Amsterdam

12-09-2016

Fundamentals of Data Science: Case “Political Communication” Damian Trilling



Today

1 Introducing. . .. . . the people. . . the schedule. . . the topic

2 Studying social media in poltical communicationSelective exposure and filter bubblesFragmentationPolarizationPoliticians on social mediaSocial media and public opinion

3 Conclusion



. . . the people

Introducing. . .. . . the people



. . . the people

Introducing. . .Stevan

dr. Stevan RudinacPostdoctoral Researcher @ Intelligent SensoryInformation Systems // IvI // UvA

• received PhD degree in Computer Science @TU Delft 2013

• graduated in Electrical Engineering @University of Belgrade 2006

• worked @ NFI, TU Delft, TU Eindhoven andUniversity of Belgrade

• interested in multimedia information retrievalwith a focus on urban computing and securityapplications.

[email protected] Science Park 904 C3.253https://staff.fnwi.uva.nl/s.rudinac/


https://staff.fnwi.uva.nl/s.rudinac/


. . . the people

Introducing. . .Damian

dr. Damian TrillingAssistant Professor Political Communication &Journalism

• studied Communication Science in Münsterand at the VU 2003–2009

• PhD candidate @ UvA 2009–2012

• interested in political communication andjournalism in a changing media environmentand in innovative (digital, large-scale,computational) research methods

@damian0604 [email protected] 8th floor www.damiantrilling.net




. . . the people

Introducing. . .You

Your name?Your background?Your reason to follow this course?



. . . the schedule

Introducing. . .. . . the schedule


Monday, 12 Sept., 11–13 (Damian)Intro to our social science case:Social media analysis in political communication

Tuesday, 13 Sept., 9-11 (Stevan)The research pipelineWorking with the Twitter APIData preprocessing and sentiment analysis

Tuesday, 13 Sept., 13-17 (you)Project: It’s your turn!

Thursday, 15 Sept., 9-11 (Stevan & Damian)Practical work: Helping you with the project

Thursday, 15 Sept., 11-17 (you)Project: It’s your turn!

Thursday, 15 Sept., 17-19 (Stevan & Damian)Presentations: Teams pitching the progress

Monday, 19 Sept., 11–13 (Damian)Analyzing political content on social media: Examples of research so far

Tuesday, 20 Sept., 9-11 (Stevan)Topic analysis, correlations, visualizationGuest presentation Joost Boonzajer Flaes, Twitter UK

Tuesday, 20 Sept., 13-17 (you)Project: It’s your turn!

Thursday, 22 Sept., 9-11 (Stevan & Damian)Practical work: Helping you with the project

Thursday, 22 Sept., 11-17 (you)Project: It’s your turn!

Thursday, 22 Sept., 17-19 (Stevan & Damian)Presentations: Teams pitching the final results


. . . the topic

Introducing. . .. . . the topic



. . . the topic

This case is about

social sciences⇒communication science

⇒political communication



. . . the topic

What is Communication Science?

• looks at communication between actors in society• is one of the empirical social sciences• (mainly) focuses on mediated communication rather thaninterpersonal communication



. . . the topic

Political communication

journalists citizens

political actors



. . . the topic

Methods to study communication

qualitative

• discourse analysis• interviews• focus groups

quantitative

• survey• experiment• content analysis• network analysis



. . . the topic


qualitative


quantitative




. . . the topic


qualitative


quantitative




. . . the topic

The link with data science

• “Computational social science”

• “In short, a computational social science is emerging thatleverages the capacity to collect and analyze data with anunprecedented breadth and depth and scale.’ (Lazer et al.)

• “the computational social sciences employ the scientificmethod, complementing descriptive statistics with inferentialstatistics that seek to identify associations and causality. Inother words, they are underpinned by an epistemology whereinthe aim is to produce sophisticated statistical models thatexplain, simulate and predict human life.” (Kitchin)

Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., . . . van Alstyne, M. (2009).Computational social science. Science, 323, 721–723. doi:10.1126/science.1167742Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 1–12.doi:10.1177/2053951714528481



. . . the topic


• “Computational social science”• “In short, a computational social science is emerging that

leverages the capacity to collect and analyze data with anunprecedented breadth and depth and scale.’ (Lazer et al.)





. . . the topic


• “Computational social science”• “In short, a computational social science is emerging that

leverages the capacity to collect and analyze data with anunprecedented breadth and depth and scale.’ (Lazer et al.)




Studying social media in poltical communicationSelective exposure and filter bubbles


Selective exposure and filter bubbles

Avoiding dissonant information is human.

Festinger, 1956

• People tend to avoid cognitive dissonance• One effective way: avoiding information that conflictspre-existing beliefs



Selective exposure and filter bubbles

And it does happen in political communication.

Lazarsfeld, Berelson, & Gaudet, 1944

• Republicans are mainly exposed to the Republican campaign• Democrats are mainly exposed to the Democratic campaign


All very well.But where can people actually be selective?


Fragmentation

Fragmentation

Sunstein, 2001 (and many others)

• People will only use those news media that cater to theirinterest

• “echo chambers”• Loss of a common core of issues• Loss of democratic discourse

⇒ news avoidance, entertainment preference as predictor of newsuse in the new media ecosystem (Prior, 2015)



Polarization

Polarization

Selective exposure to ideologically congruent content

• If people don’t hear the other side any more, they becomemore extreme



Polarization

US Presidential Elections: Vote share 1952, 1956

http://xenocrypt.blogspot.de/2013/02/presidential-results-by-1952-districts.html



Polarization

US Presidential Elections: Vote share 2008, 2012

http://xenocrypt.blogspot.de/2013/02/presidential-results-by-1952-districts.html



Polarization

Let’s conclude. . .

• People are selective• Nowadays, there is more media content to choose from

• content one politically agrees with ⇒ polarization• entertainment over politics, only exposure to topics one is

interested in beforehand ⇒ fragmentation



Polarization

The filter bubble

Pariser, 2011

• Algorithms increasingly guess what we might like and choosefor us (FB, Google,. . . )

• Even if we do not avoid actively, we are living in a filter bubble


Conover, M. D., Gonçalves, B., Flammini, A., & Menczer, F. (2012). Partisan asymmetries in online politicalactivity. EPJ Data Science, 1(6), 1–19.


Polarization

How much of an echo chamber are social media?

“We estimated ideological preferences of 3.8 million Twitter usersand, using a data set of nearly 150 million tweets concerning 12political and nonpolitical issues. [...] Overall, we conclude thatprevious work may have overestimated the degree of ideologicalsegregation in social-media usage”Barbera, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015). Tweeting from left to right: Is onlinepolitical communication more than an echo chamber? Psychological Science, 26(10), 1531–1542.

“We find that users share news in similar ways regardless of outletor perceived ideology of outlet, and that as a user shares morenews content, they tend to quickly include outlets with opposingviewpoints. [...] Specifically, users in our sample who sent multipletweets tended to increase the ideological diversity in news theyshared within two or three tweets”Morgan, J. S., Shafiq, M. Z., & Lampe, C. (2013). Is news sharing on Twitter ideologically biased? Proceedings ofthe 2013 conference on Computer supported cooperative work (pp. 887–897). ACM.



Polarization

How much of an echo chamber are social media?“We estimated ideological preferences of 3.8 million Twitter usersand, using a data set of nearly 150 million tweets concerning 12political and nonpolitical issues. [...] Overall, we conclude thatprevious work may have overestimated the degree of ideologicalsegregation in social-media usage”Barbera, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015). Tweeting from left to right: Is onlinepolitical communication more than an echo chamber? Psychological Science, 26(10), 1531–1542.




Polarization

How much of an echo chamber are social media?“We estimated ideological preferences of 3.8 million Twitter usersand, using a data set of nearly 150 million tweets concerning 12political and nonpolitical issues. [...] Overall, we conclude thatprevious work may have overestimated the degree of ideologicalsegregation in social-media usage”Barbera, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015). Tweeting from left to right: Is onlinepolitical communication more than an echo chamber? Psychological Science, 26(10), 1531–1542.




Polarization

A first answer to the question why we should study socialmedia:

They might change the way peopleare exposed to news and politicalmessages – which could lead tofragmentation and polarization.But we don’t have conclusive answers yet. . .


Studying social media in poltical communicationPoliticians on social media


Politicians on social media

The politician–citizen edge is now finally a viable way. . . no need to take the detour through mass media any more.

journalists citizens

political actors




Consequences

• politicians use social media to be more in control, bypassingthe journalistic filter

• reach other target groups• but also: from one-way to two-way communication




How politicians (should) communicate only

• interactivity• personalization

can enhance political involvement

Kruikemeier, S., van Noort, G., Vliegenthart, R., & de Vreese, C. H. (2013). Getting closer: The effects ofpersonalized and interactive online political communication. European Journal of Communication, 28(1), 53–66.




Effects of politicians on social media

• Using social media impacts voting, especially“voorkeurstemmen”

Jacobs, K., & Spierings, N. (2014). . . .Maar win je er stemmen mee ? De impact van Twittergebruik door politicibij de Nederlandse Tweede Kamerverkiezingen. Tijdschrift Voor Communicatiewetenschap, 42(1), 22–38.Kruikemeier, S. (2014). How political candidates use Twitter and the impact on votes.Computers in HumanBehavior, 34, 131–139.


Studying social media in poltical communicationSocial media and public opnion


Social media and public opinion

Things to keep in mind

• Be careful in generalizing!• Often used because of easy to access API, but is it really theright data source for your question? . . .



Social media and public opinion

Example: Twitter-based prediction of election results

Fundamental flaws

• heavily skewed user base• better than random does not mean better then more sensiblebaseline (last election results, . . . )

• published after results were known• arbitrary choices on what to include• overly simplistic assumptions (e.g., number of mentions =support)

Gayo-Avello, D. (2013). A Meta-Analysis of State-of-the-Art Electoral Prediction From Twitter Data. SocialScience Computer Review, 31(6), 649–679.Jungherr, A., Jürgens, P., & Schoen, H. (2011). Why the Pirate Party Won the German Election of 2009 or TheTrouble 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 ScienceComputer Review, 30(2), 229–234.


Conclusion


Conclusion (1)

• The changing media environent can have impact on society atlarge (fragmentation, polarization)

• It changes the communication triangle between politicians,journalists, and the public



Conclusion (2)

• Social media data can be linked to political outcomes• But be careful to generalize!



Questions?

[email protected]@damian0604



Education

Data Science: Case "Political Communication 1/2"