COM 674

```{r setup, include=FALSE} knitr::opts_chunk$set(echo = FALSE) knitr::opts_knit$set(root.dir = './') source("resources/preamble.R") f <- function (x) {formatC(x, format="d", big.mark=',')} bold <- function(x) {paste('{\\textbf{',x,'}}', sep ='')} gray <- function(x) {paste('{\\textcolor{gray}{',x,'}}', sep ='')} wrapify <- function (x) {paste("{", x, "}", sep="")} p <- function (x) {formatC(x, format='f', digits=1, big.mark=',')} ```## Weekly Dad Joke Bro, can you hand me that leaflet? Brochure ## Housekeeping > - Project proposal feedback session? ## Course feedback > - Sharing/comparing code > - Solutions? > - Feedback > - Screencast? > - Synchronous exercises in class > - More lecture ## Solution sharing Chapter 7: 1,2,3 Baby names: 1, 2, 3 ## Paper discussion Margolin, D. B., Hannak, A., & Weber, I. (2018). Political Fact-Checking on Twitter: When Do Corrections Have an Effect? Political Communication, 35(2), 196–219. > - Lots of evidence that people don't act like "intuitive scientists" > - Misinformation doesn't change opinions > - Rumors propagation happens even in the face of corrections > - Key question of their study: > - What are the social conditions that encourage retraction/opinion change? ## Hypotheses > - H1: People are more likely to accept corrections from friends > - H2: People are more likely to accept corrections from those embedded in same group (larger shared audience) > - RQ: How do audience sizes affect likelihood to accept corrections? ## Paper discussion > - Method > - Twitter "garden hose" to identify tweets where: > - "Snopee" shares misinformation > - "Snoper" shares link to correction > - "Snopee" responds > - Coded the content of the correction and response > - Regression to predict when a correction was accepted > - H1 was accepted; no strong effect for others. ## Questions > - What were some strengths of the research design? Weaknesses? > - What is the next study you would design to complement this study? > - How much do you think the context influenced the results? ## Project proposal feedback session? ## Principles for this week > - Jupyter Notebooks > - Dictionaries > - Tuples ## Team problem Day 2 challenges - #7 ## Homework > - Jupyter notebook + problems from book