Televised Debates, Second Screens,and Filter Bubbles
presented at the EPSA Annual Conference 2018
Simon Richter1 & Prof. Dr. Thorsten Faas1
1Otto-Suhr-Institut
23.06.2018
TV Debates in Context: Past & Present
TV Debates in Context: Past & Present
Second Screening
Second screening
= ”bundle of practices that involve integrating, and switchingacross and between, live broadcast and social media”(Vaccari et al. 2015)
I increasingly popular in general
I most prominent during media events
I motivations for second screening: discuss, get furtherinformation and gauge others’ opinions
Filter Bubbles
Filter Bubbles= communicative spaces in which “content is selected byalgorithms according to a viewer’s previous behaviors” (Bakshy et al.
2015) , thereby providing “content an individual is likely to agreewith” (Flaxman et al. 2016).
I Homophily on social media platforms is a thing, ...
I ... but there is a fair chance that users get confronted withattitude-discordant contents.
I Unexplored: Effects of Filter Bubbles on perception of politicalinformation. Why is that?
I Idiosyncratic information environments: unobservable fromoutside and hard to generalize their features
I Endogeneity: self-selection into exposure makes effectestimation through purely observational data pretty muchimpossible
Filter Bubbles
Filter Bubbles= communicative spaces in which “content is selected byalgorithms according to a viewer’s previous behaviors” (Bakshy et al.
2015) , thereby providing “content an individual is likely to agreewith” (Flaxman et al. 2016).
I Homophily on social media platforms is a thing, ...
I ... but there is a fair chance that users get confronted withattitude-discordant contents.
I Unexplored: Effects of Filter Bubbles on perception of politicalinformation. Why is that?
I Idiosyncratic information environments: unobservable fromoutside and hard to generalize their features
I Endogeneity: self-selection into exposure makes effectestimation through purely observational data pretty muchimpossible
Filter Bubbles
Filter Bubbles= communicative spaces in which “content is selected byalgorithms according to a viewer’s previous behaviors” (Bakshy et al.
2015) , thereby providing “content an individual is likely to agreewith” (Flaxman et al. 2016).
I Homophily on social media platforms is a thing, ...
I ... but there is a fair chance that users get confronted withattitude-discordant contents.
I Unexplored: Effects of Filter Bubbles on perception of politicalinformation. Why is that?
I Idiosyncratic information environments: unobservable fromoutside and hard to generalize their features
I Endogeneity: self-selection into exposure makes effectestimation through purely observational data pretty muchimpossible
Filter Bubbles
Filter Bubbles= communicative spaces in which “content is selected byalgorithms according to a viewer’s previous behaviors” (Bakshy et al.
2015) , thereby providing “content an individual is likely to agreewith” (Flaxman et al. 2016).
I Homophily on social media platforms is a thing, ...
I ... but there is a fair chance that users get confronted withattitude-discordant contents.
I Unexplored: Effects of Filter Bubbles on perception of politicalinformation. Why is that?
I Idiosyncratic information environments: unobservable fromoutside and hard to generalize their features
I Endogeneity: self-selection into exposure makes effectestimation through purely observational data pretty muchimpossible
Televised Debates and Filter Bubbles
Televised Debates and Filter Bubbles
Televised Debates and Filter Bubbles
RQ1:Do the subjects “accurately“ perceive the tone of the filter bubblethey are in?
I Identifying the tone of filter bubble = highly complex taskI Different modes of information processing possible (Schulz &
Roessler 2012)
I quasi-statistical senseI looking-glass perception
Televised Debates and Filter Bubbles
RQ1:Do the subjects “accurately“ perceive the tone of the filter bubblethey are in?
I Identifying the tone of filter bubble = highly complex task
I Different modes of information processing possible (Schulz &
Roessler 2012)
I quasi-statistical senseI looking-glass perception
Televised Debates and Filter Bubbles
RQ1:Do the subjects “accurately“ perceive the tone of the filter bubblethey are in?
I Identifying the tone of filter bubble = highly complex taskI Different modes of information processing possible (Schulz &
Roessler 2012)
I quasi-statistical senseI looking-glass perception
Televised Debates and Filter Bubbles
RQ1:Do the subjects “accurately“ perceive the tone of the filter bubblethey are in?
I Identifying the tone of filter bubble = highly complex taskI Different modes of information processing possible (Schulz &
Roessler 2012)
I quasi-statistical sense
I looking-glass perception
Televised Debates and Filter Bubbles
RQ1:Do the subjects “accurately“ perceive the tone of the filter bubblethey are in?
I Identifying the tone of filter bubble = highly complex taskI Different modes of information processing possible (Schulz &
Roessler 2012)
I quasi-statistical senseI looking-glass perception
Televised Debates and Filter Bubbles
Televised Debates and Filter Bubbles
Televised Debates and Filter Bubbles
RQ2:Do the biased information environments influence the perceptionof the candidates’ performances?
I Televised debates are highly complex → need for heuristics
I Pre-existing attitudes towards candidates/partiesI Viewers geared by other users’ opinions (social influence
theory):
I Political attitudes in general (Levitan & Verhulst 2016) andcandidate evaluation in televised debates shown to besusceptible to social influence
I Social influence can occur in computer-mediatedcommunication spaces (see Maruyama et al. 2017)
Televised Debates and Filter Bubbles
RQ2:Do the biased information environments influence the perceptionof the candidates’ performances?
I Televised debates are highly complex → need for heuristics
I Pre-existing attitudes towards candidates/partiesI Viewers geared by other users’ opinions (social influence
theory):
I Political attitudes in general (Levitan & Verhulst 2016) andcandidate evaluation in televised debates shown to besusceptible to social influence
I Social influence can occur in computer-mediatedcommunication spaces (see Maruyama et al. 2017)
Televised Debates and Filter Bubbles
RQ2:Do the biased information environments influence the perceptionof the candidates’ performances?
I Televised debates are highly complex → need for heuristics
I Pre-existing attitudes towards candidates/parties
I Viewers geared by other users’ opinions (social influencetheory):
I Political attitudes in general (Levitan & Verhulst 2016) andcandidate evaluation in televised debates shown to besusceptible to social influence
I Social influence can occur in computer-mediatedcommunication spaces (see Maruyama et al. 2017)
Televised Debates and Filter Bubbles
RQ2:Do the biased information environments influence the perceptionof the candidates’ performances?
I Televised debates are highly complex → need for heuristics
I Pre-existing attitudes towards candidates/partiesI Viewers geared by other users’ opinions (social influence
theory):
I Political attitudes in general (Levitan & Verhulst 2016) andcandidate evaluation in televised debates shown to besusceptible to social influence
I Social influence can occur in computer-mediatedcommunication spaces (see Maruyama et al. 2017)
Study Design
I Methodological innovation: Laboratory Live-Experiment onGerman televised debate 2017
I Between-subjects design with three different twitter wallscontaining real tweets
I Sample: 119 participants highly educated and rather young,balanced in gender
I Random assignment worked, but coincidental deviations inparty ID
Study Design
I Methodological innovation: Laboratory Live-Experiment onGerman televised debate 2017
I Between-subjects design with three different twitter wallscontaining real tweets
I Sample: 119 participants highly educated and rather young,balanced in gender
I Random assignment worked, but coincidental deviations inparty ID
Study Design
I Methodological innovation: Laboratory Live-Experiment onGerman televised debate 2017
I Between-subjects design with three different twitter wallscontaining real tweets
I Sample: 119 participants highly educated and rather young,balanced in gender
I Random assignment worked, but coincidental deviations inparty ID
Study Design
I Methodological innovation: Laboratory Live-Experiment onGerman televised debate 2017
I Between-subjects design with three different twitter wallscontaining real tweets
I Sample: 119 participants highly educated and rather young,balanced in gender
I Random assignment worked, but coincidental deviations inparty ID
Study Design
RQ1: Perception of the Filter Bubble tone
QuestionRecalling the tweets you could observe during the debate:Altogether, how was [Angela Merkel/Martin Schulz] portrayed inthose messages from your point of view?
1 = very negative; 5 = very positive
RQ1: Perception of the Filter Bubble tone
RQ2: Effects on candidate evaluation
QuestionAltogether, how did [Angela Merkel/Martin Schulz] perform duringthe debate?
1 = very bad; 5 = very good
RQ2: Effects on candidate evaluation
Conclusion
I Subjects are able to determine the tone of their filter bubblein a quasi-statistical manner; however: unexplained variationmerits further investigation
I Filter bubble effect only for Martin Schulz → effectscontingent on external factors (e.g. pre-existing knowledgeabout candidate)
I Implications: Filter Bubble effects opening ways to influencepolitical attitudes through organized collective actions onsocial media channels (”Hijacking the filter bubble”)
I Upcoming: Survey Experiment (positive vs. negative tweets)
Conclusion
I Subjects are able to determine the tone of their filter bubblein a quasi-statistical manner; however: unexplained variationmerits further investigation
I Filter bubble effect only for Martin Schulz → effectscontingent on external factors (e.g. pre-existing knowledgeabout candidate)
I Implications: Filter Bubble effects opening ways to influencepolitical attitudes through organized collective actions onsocial media channels (”Hijacking the filter bubble”)
I Upcoming: Survey Experiment (positive vs. negative tweets)
Conclusion
I Subjects are able to determine the tone of their filter bubblein a quasi-statistical manner; however: unexplained variationmerits further investigation
I Filter bubble effect only for Martin Schulz → effectscontingent on external factors (e.g. pre-existing knowledgeabout candidate)
I Implications: Filter Bubble effects opening ways to influencepolitical attitudes through organized collective actions onsocial media channels (”Hijacking the filter bubble”)
I Upcoming: Survey Experiment (positive vs. negative tweets)
Conclusion
I Subjects are able to determine the tone of their filter bubblein a quasi-statistical manner; however: unexplained variationmerits further investigation
I Filter bubble effect only for Martin Schulz → effectscontingent on external factors (e.g. pre-existing knowledgeabout candidate)
I Implications: Filter Bubble effects opening ways to influencepolitical attitudes through organized collective actions onsocial media channels (”Hijacking the filter bubble”)
I Upcoming: Survey Experiment (positive vs. negative tweets)
ReferencesI Bakshy E, Messing S, Adamic LA. 2015. Political science.
Exposure to ideologically diverse news and opinion onFacebook. Science (New York, N.Y.) 348 (6239):1130-32.
I Flaxman S, Goel S, Rao JM. 2016. Filter Bubbles, EchoChambers, and Online News Consumption. PUBOPQ 80(S1):298-320.
I Hahn, Kyu S., Hye-Yon Lee, Seyong Ha, Seulgi Jang, andJoonwhan Lee. 2017. “The Influence of “Social Viewing” onTelevised Debate Viewers’ Political Judgment.” PoliticalCommunication 42 (1): 1-19.
I Levitan LC, Verhulst B. 2016. Conformity in Groups. TheEffects of Others’ Views on Expressed Attitudes and AttitudeChange. Political Behavior 38 (2):277-315.
I Maruyama, Misa. 2017. “Social Watching a Civic Broadcast.”In the 2017 ACM Conference, eds. Charlotte P. Lee, StevePoltrock, Louise Barkhuus, Marcos Borges and WendyKellogg, 794-807.
References
I Schulz A, Roessler P. 2012. The Spiral of Silence and theInternet. Selection of Online Content and the Perception ofthe Public Opinion Climate in Computer-MediatedCommunication Environments. International Journal of PublicOpinion Research 24 (3):346-67.
I Vaccari C, Chadwick A, O’Loughlin B. 2015. Dual Screeningthe Political: Media Events, Social Media, and CitizenEngagement. Journal of Communication 65.