Table 1 Relationship between content classification and type of rumour among all 232 pieces of misinformation analysed
Real life stories | Conspiracy theories | Health Tips | Scientific/epidemiologic data | Virtual scams | Warnings | Politics | Total | |||
|---|---|---|---|---|---|---|---|---|---|---|
Type of rumour | Satire or Parody | Frequency | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 |
% | 0,0% | 0,0% | 0,0% | 0,0% | 11,1% | 0,0% | 0 | 0,4% | ||
Adjusted Residual | -,9 | -,2 | -,2 | -,4 | 5,1 | -,2 | -,5 | |||
Misleading, imposter, manipulated content | Frequency | 5 | 1 | 1 | 14 | 0 | 2 | 3 | 26 | |
% | 4,3% | 10,0% | 7,1% | 43,8% | 0,0% | 28,6% | 5,4% | 10,7% | ||
Adjusted Residual | −3,0 | -,1 | -,4 | 6,5 | −1,1 | 1,6 | −1,5 | |||
Fabricated content | Frequency | 44 | 7 | 13 | 17 | 8 | 5 | 36 | 130 | |
% | 38,3% | 70,0% | 92,9% | 53,1% | 88,9% | 71,4% | 64,3% | 53,5% | ||
Adjusted Residual | −4,5 | 1,1 | 3,0 | ,0 | 2,2 | 1,0 | 1,8 | |||
False connection or false context | Frequency | 66 | 2 | 0 | 1 | 0 | 0 | 17 | 86 | |
% | 57,4% | 20,0% | 0,0% | 3,1% | 0,0% | 0,0% | 30,4% | 35,4% | ||
Adjusted Residual | 6,8 | −1,0 | −2,9 | −4,1 | −2,3 | −2,0 | -,9 | |||
Total | Frequency | 115 | 10 | 14 | 32 | 9 | 7 | 56 | 243 | |
% | 100,0% | 100,0% | 100,0% | 100,0% | 100,0% | 100,0% | 100,0% | 100,0% | ||