research using empirical data to investigate the effects of today’s news on young citizens:...
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Research using empirical data to investigate the effects of today’s news
on young citizens:
Effects of Social Media News Recommendations on Media Trustand
Effects of Childhood News Media Habits on Young Adult Participation
Rosanne SchollDownload this presentation at tinyurl.com/datajourn
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About Me
• Data analyst with economics background• Classes focus on data methods, mass
communication theory, digital skills acquisition, and critical thinking
• Research focus on effects of news on democratically important outcomes
• AEJMC division head, head of one of School’s 4 areas of study
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Media Effects
• Most of what we know about the effects of journalism regards the content of the news– Framing, bias, credibility, frequency
• Two papers today: effects of news delivery– From friends on social media– From parents during your adolescence
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NEWS RECOMMENDATIONS ON SOCIAL MEDIA: EFFECTS ON MEDIA TRUST
Study 1: Political Communication Research Group
With Jason Turcotte, Chance York, Jacob Irving, and Ray Pingree
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Use own facebook page
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Media Trust
• Will we trust media that we get this way?
• Will we seek out more political information when introduced to it via social media?
• Does who the recommendation comes from matter?
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Two Step Flow of Communication
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Opinion Leadership
• Please answer the following questions about Al Stavitsky, your Facebook friend:
[7 point Likert scale for agree/disagree with the following statements:]
– This person is well informed about politics and current events
– This person is honest about politics and current events
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Cues and Motivated Reasoning
• The recommendation of an opinion leader can act as a cue for the quality of the news source
• Do we interpret the political content to make it consistent with opinions about the friend’s politics?
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An experiment
• Manipulate whether participant reads a story that has been shared by a social media contact– Or the same story with no social recommendation
cue
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Choosing the friend
• Facebook API pulls 100 friends, picks one with recent interactions with the participant
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Stimulus
[Example of Social Recommendation Manipulation]
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Procedure
• Online experiment with undergraduates receiving extra credit for their participation
• 1) Facebook sign in• 2) Stimulus• 3) Outcome measures• 4) Opinion leader measures
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Trust in News Outlet
Model 1
Model 2 b (SE) b (SE)
Adjudication -0.03 (0.06) -0.02 (0.06) Polarization 0.06 (0.10) 0.07 (0.09) Story Context 0.08 (0.10) 0.08 (0.09) Recommendation 0.03 (0.10) -0.84* (0.35) Opinion Leader 0.13*** (0.04) 0.05 (0.05) Recommendation X Opinion Leader --- 0.19** (0.07) Constant 4.09*** (0.19) 4.43*** (0.23) N 364 364 R2 0.038 0.056 Note: ***p<.001, **p<.01, *p<.05
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Size of Effect of Social Recommend-ation on Trust in News Outlet
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Findings Summary
• When a quality opinion leader recommends an article, we trust the outlet more and look to it more in the future
• When a poor opinion leader recommends an article, we trust the outlet less and look to it less in the future
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Implications
• Social media amplifies the two step flow• Political news can be credited or discredited
by perceptions about the person sharing it
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Implications
• Social media enriches marketplace of ideas– Get political information from trusted sources
• Social media constricts diverse media content– Most friends similar, plus platforms further filter
dissonant news– Rare cross-cutting voices may be labeled “poor
opinion leaders”
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Implications
• More social media reach is not necessarily better
• Many sources, some are more deserving, people are doing something rational to use friends to figure out which to trust
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Ongoing
• Gathering more data: currently in the field• Effect of partisanship match between
participant and friend• Effects on other outcomes• Interaction with other manipulations
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EFFECTS OF CHILDHOOD NEWS MEDIA HABITS ON YOUNG ADULT PARTICIPATION
Study 2: Funded Research on Multigenerational Panel Data
With Chance York
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Socialization
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Socialization mechanisms
• Modelling• Defining• Other possibilities:
– Causal schema formation– Status inheritance– Genetic heritability
• “Impressionable years” of adolescence
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Youth Voting
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Expectations
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Data
University of Michigan’s Panel Study of Income Dynamics (PSID)
• 1997 and 2003 PSID main interviews: parent and child demographic characteristics
• 2002 Child Development Supplement: parent and adolescent behavioral and media use variables
• 2009 Transition to Adulthood Supplement: young adult measures
• N = 903 young adult respondents
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Modelling Youth Voter Turnout
• Weighted for national representation using CDS weights
• Logistic regression with MLE estimator • Control for demographics, student status,
employment status, children, 2009 media use
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B ZParent Characteristics Education 0.040 2.40* Income -0.001 -1.88† Volunteering 0.007 1.35 Donations 0.043 0.72 Newspaper Use 0.078 2.22* Talk About News with Child 0.206 2.21* Television Use 0.013 0.65 Talk About TV with Child 0.175 0.78Adolescent Media Use Newspaper 1.369 1.19 Television -0.034 -1.23 Internet -0.093 -1.28 Videogames -0.042 -0.84Young Adult Characteristics Female 0.197 0.92 Age 0.069 1.21 Black 1.152 3.63*** Hispanic -0.445 -1.24 Education 0.429 5.08*** Income 0.003 0.36 College Student 0.260 1.09 Employed 0.241 1.14 Children -0.248 -1.73 Read/Watch News 0.160 2.07* Entertainment TV 0.013 0.17Constant -9.477 -6.24***N 903Model Chi-Square 132.97***Pseudo R2 18.29%
† = p<.10, * = p<.05, ** p<.01, *** p<.001 (two-tailed)
Note: This analysis was weighted using PSID weights for national representativeness. A Hosmer and Lemeshow goodness of fit statistic (898.77, p = .32) based on unweighted estimates was not significant, suggesting the logistic regression model fit these data well.
Multivariate Logistic Regression Predicting Young Adult Voter Turnout
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Expectations
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Implications
• Parents can help train young people to vote, but not via regulating the behavior of teenagers
• Adolescents may be forming civic orientations that lie dormant until early adulthood, even while ignoring news for entertainment TV and video games
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THANK YOU!
@Rosanne Scholl or [email protected] this presentation: tinyurl.com/datajourn
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