1. Research using empirical data to investigate the effects of today’s news on young citizens: Effects of Social Media News Recommendations on Media Trust and Effects of Childhood News Media Habits on Young Adult Participation Rosanne Scholl Download this presentation at tinyurl.com/datajourn

2. 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

3. 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

4. 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

5. Use own facebook page

7. 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?

8. Two Step Flow of Communication

9. 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

10. 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?

11. 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

12. Choosing the friend Facebook API pulls 100 friends, picks one with recent interactions with the participant

13. Stimulus [Example of Social Recommendation Manipulation]

14. Procedure Online experiment with undergraduates receiving extra credit for their participation 1) Facebook sign in 2) Stimulus 3) Outcome measures 4) Opinion leader measures

15. Trust in News Outlet Note: ***p<.001, **p<.01, *p<.05

16. Size of Effect of Social Recommend- ation on Trust in News Outlet

17. 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

18. Implications Social media amplifies the two step flow Political news can be credited or discredited by perceptions about the person sharing it

19. 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”

20. 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

21. Ongoing Gathering more data: currently in the field Effect of partisanship match between participant and friend Effects on other outcomes Interaction with other manipulations

22. EFFECTS OF CHILDHOOD NEWS MEDIA HABITS ON YOUNG ADULT PARTICIPATION Study 2: Funded Research on Multigenerational Panel Data With Chance York

23. Socialization

24. Socialization mechanisms Modelling Defining Other possibilities: –Causal schema formation –Status inheritance –Genetic heritability “Impressionable years” of adolescence

25. Youth Voting

26. Expectations

27. 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

28. 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

29. BZ Parent 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 0.78 Adolescent Media Use Newspaper 1.369 1.19 Television-0.034-1.23 Internet-0.093-1.28 Videogames-0.042-0.84 Young 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 0.17 Constant-9.477-6.24*** N903 Model Chi-Square132.97*** Pseudo R 2 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

30. Expectations

31. 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

32. THANK YOU! @Rosanne Scholl or rmscholl@gmail.comrmscholl@gmail.com Download this presentation: tinyurl.com/datajourn Some visuals in this presentation created with draw.io. Photos tagged as licensed for reuse via Google Image search.