A series of persuasive events. Sequencing effects of negative and positive messages on party evaluations and perceptions of negativity

Figures & data

Figure 1. Experimental setup.

Figure 2. Coefficients plot – The effects of messages sequence on perceptions of negativity.

Notes: Dependent variable measures the extent to which respondents believe that politics in Denmark is characterized by attacks, and varies between 0 ‘very low’ to 10 ‘very high’. Sequences of messages are unique combinations of positive (P) or negative (N) messages; the order of the messages is reflected in the sequence acronym (e.g., ‘PPN’ means two positive messages followed by a negative one). Confidence intervals are presented at both 95% (outer limits, pale gray) and 90% (inner limits, dark gray). See Table A1 for full models.

Figure 3. Volume effects of negative messages. Comparing exposure to one and three negative messages, by issue.

Notes: (a) N(control) = 330; N(t1) = 102; N(t3) = 42. Differences: (Control vs. t1: d = 0.01, p = 0.47) (t1 vs. t3: d = 0.25, p = 0.09), (b) N(control) = 360; N(t1) = 103; N(t3) = 45. Differences: (Control vs. t1: d = 0.11, p = 0.15) (t1 vs. t3: d=0.49, p = 0.00), (c) N(control) = 298; N(t1) = 115; N(t3) = 41. Differences: (Control vs. t1: d = 0.06, p = 0.27) (t1 vs. t3: d = 0.14, p = 0.23), (d) N(control) = 327; N(t1) = 120; N(t3) = 42. Differences: (Control vs. t1: d = 0.03, p = 0.38) (t1 vs. t3: d = 0.23, p = 0.11), (e) N(control) = 300; N(t1) = 108; N(t3) = 41. Differences: (Control vs. t1: d = 0.08, p = 0.25) (t1 vs. t3: d = 0.02, p = 0.46), (f) N(control) = 332; N(t1) = 109; N(t3) = 45. Differences: (Control vs. t1: d = 0.34, p = 0.00) (t1 vs. t3: d = 0.02, p = 0.44).

Figure 4. Volume effects of positive messages. Comparing exposure to one and three positive messages, by issue.

Notes: (a) N(control) = 330; N(t1) = 118; N(t3) = 13. Differences: (Control vs. t1: d = 0.07, p = 0.26) (t1 vs. t3: d = 0.46, p = 0.07), (b) N(control) = 360; N(t1) = 119; N(t3) = 14. Differences: (Control vs. t1: d = 0.07, p = 0.25) (t1 vs. t3: d = 0.22, p = 0.22), (c) N(control) = 298; N(t1) = 92; N(t3) = 17. Differences: (Control vs. t1: d = 0.25, p = 0.02) (t1 vs. t3: d = 0.14, p = 0.30), (d) N(control) = 327; N(t1) = 92; N(t3) = 16. Differences: (Control vs. t1: d = 0.06, p = 0.31) (t1 vs. t3: d = 0.08, p = 0.38), (e) N(control) = 300; N(t1) = 93; N(t3) = 9. Differences: (Control vs. t1: d = 0.19, p = 0.04) (t1 vs. t3: d = 0.59, p = 0.15), (f) N(control) = 332; N(t1) = 96; N(t3) = 11. Differences: (Control vs. t1: d = 0.38, p = 0.00) (t1 vs. t3: d = 0.01, p = 0.48)

Figure 5. Coefficients plot – The effects of messages sequence on evaluation Liberals (top panel) and Social-Democrats (bottom panel) in last experiment.

Note: Dependent variable measures how respondents evaluate the Liberals (top panel) and Social-Democrats (bottom panel) performance at handling the issue at stake, depending on which issue was framed the last of the three experiments. Both variables vary between 0 ‘very bad’ and 10 ‘very well’. For the control group, the dependent variable is the average of the respondents’ evaluation of the Liberals performance on the three issues. Sequences of messages are unique combinations of positive (P) or negative (N) messages; the order of the messages is reflected in the sequence acronym (e.g., ‘PPN’ means two positive messages followed by a negative one). Confidence intervals are presented at both 95% (outer limits, pale gray) and 90% (inner limits, dark gray). See Tables A2 and A3 for full models.