PEP-TFSocial Media Monitoring of the Campaigns for the 2013 German Bundestag Elections on Facebook and Twitter

Lead: Lars Kaczmirek1, Philipp Mayr1, Ravi Vatrapu*

Members: Arnim Bleier1, Manuela Blumenberg1, Tobias Gummer1, Kjeld Hansen*, Abid Hussein*, Zeshan Ali Jaffari*, Katharina Kinder-Kurlanda1, Haiko Lietz, Markus Strohmaier1, Claudia Wagner1, Katrin Weller1, Christof Wolf1, Chris James Zimmerman*

1 GESIS – Leibniz Institute for the Social Sciences

* Department of IT Management, Copenhagen Business School

Please cite as:

Lars Kaczmirek, Philipp Mayr, Ravi Vatrapu, Arnim Bleier, Manuela Blumenberg, Tobias Gummer, Kjeld Hansen, Abid Hussein, Zeshan Ali Jaffari, Katharina Kinder-Kurlanda, Haiko Lietz, Markus Strohmaier, Claudia Wagner, Katrin Weller, Christof Wolf, Chris James Zimmerman. (2014). PEP-TF: Social Media Monitoring of the Campaigns for the 2013 German Bundestag Elections on Facebook and Twitter. Presentation at the Social Media Communication Workshop, May 28-29, 2014, MZES, Germany.

Research domain

• To examine communication structures in online media and how such data can add new insights in comparison to existing data from surveys, print media analyses, and the TV candidates’ debate.

• Describe and visualize dynamics in political debates in socia media: e.g. pure social media phenomena like hypes, memes and hoaxes

• Analyze the influence of classical media on social media (e.g. second screen analyses)

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Social Media Data political communication with respect to the German Bundestag election on

22 Sep 2013

CBSFacebook

WTSTwitter

DBGSample

3

DBG

WTS

CBS

DAS

CSS

4

Social Media Corpora

RECHERCHEspezial

Social media

CDU/CSU SPDFDP Grüne LinkePiraten

Working Paper:Social Media Monitoring of the Campaigns for the 2013 German Bundestag Elections on Facebook and Twitter

Lars Kaczmirek1, Philipp Mayr1, Ravi Vatrapu*, Arnim Bleier1, Manuela Blumenberg1, Tobias Gummer1, Abid Hussein*, Katharina Kinder-Kurlanda1, Kaveh Manshaei1, Mark Thamm1, Katrin Weller1, Alexander Wenz1, Christof Wolf1

1 GESIS – Leibniz Institute for the Social Sciences

* Department of IT Management, Copenhagen Business School

PEP-TF Fact Sheet

• 2346 candidates• 1408 Facebook walls with 469 000 posts• 1009 Twitter accounts with >8 million tweets

– +76 gate keepers, such as journalists– +100 authorities

• 175 topics and campaign hashtags, #btw13 #partei #hartz4 #maut …• 20 hashtags about #nsa #snowden #yeswescan …

• 67% of the candidates have a wall or page,

• 43% have a Twitter account

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Corpora

1. Facebook corpus of candidates

2. Twitter corpus of candidates

3. Twitter corpus of media agents

4. Twitter hashtag corpus of basic political topics

5. Twitter hashtag corpus of media topics

6. Twitter hashtag corpus about NSA / Snowden

Data collection periods:– Twitter: 20 June 2013 - 17 December 2013– Facebook: in November 2013 for the period of

1 Jan 2009 – 31 Oct 2013

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@

@

#

#

#

C

C1 + C2: retrieving the Bundestag candidates

• Reasonable likelihood of becoming a member of the Bundestag• Stage 1

– Search listings of candidatures– Web, email and telephone call – Continuous update and extension necessary

• Stage 2– Identify and verify Facebook and Twitter accounts– Verification

1. Is a reference to the party, for example a party logo visible? Are Facebook friends and Twitter followers members of this party?

2. Do the candidate’s personal or party website link to the profile?

3. Can the candidate be recognized via image or constituency (for direct candidates)?

4. Accounts used only for private purposes were not included.8

@

Data types

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Attribute Description

guid Unique ID to identify an object, such as the account name

Date and time stamps Identify the date and time of an action, such as a like

Comment Information about a comment on the wall

Likes Information about a like on the wall

Post texts Information about the posted text

Actor attributes Information about the person who made an action, such as a like

Data types

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Attribute Description

_id tweet ID

userid numeric user ID

screenName alpha numeric user ID

name username

replyid ID of the original tweet, if this tweet is a reply; otherwise -1

replyuserid user ID of original tweet

createdAt date of tweet

tweettext text of this tweet

Number of tweets per day

Note. Green peaks coincide with candidates TV debate and election day.11

Corpus 2: Frequency of Tweets over time Absolute

frequency of tweets is correlated with major political events.

Intensity was highest in the mid & end of campaigning.

Gummer et al. (2014)

Corpus 2: Frequency of Tweets over time by party PIRATEN do

account for most of the Tweets.

Bias in aggregated distribution when not controlling for parties.

Gummer et al. (2014)

When Politicians TalkAssessing Online Conversational Practices of Political Parties on Twitter

following

14Lietz et al. (2014)

mentioningretweeting

Further research agenda

• Identification of topics in short texts (140 characters) via unsupervised topic modeling (large PEP-TF corpora)

• Identification and visualization of topic drifts over time (small PEP-TF corpora)

• Social media data for search support in portals like sowiport– Recommendation services for „hot“ topics, debates and persons

Thank you

• Gummer, T., Roßmann, J., & Wolf, C. (2014). Candidates’ Twitter Use in the German Election 2013. Presentation at the General Online Research 2014, Cologne, Germany.

• Lietz, H., Wagner, C., Bleier, A., & Strohmaier, M. (2014). When politicians talk: Assessing online conversational practices of political parties on twitter. In International AAAI Conference on Weblogs and Social Media (ICWSM2014), Ann Arbor, MI, USA, June 2-4, 2014.

• Thamm, M., & Bleier, A. (2013). When Politicians Tweet: A Study on the Members of the German Federal Diet. In ACM Web Science 2013. Paris, France. Retrieved from http://www.websci13.org/

• Weller, K., Bruns, A., Burgess, J., Mahrt, M. & Puschmann, C. (Eds.). (2014). Twitter and Society. New York: Peter Lang.

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