Table 2 Relationship between sentiment and content classification among all 232 pieces of misinformation analysed
Real life stories | Conspiracy theories | Health Tips | Scientific/epidemiologic data | Virtual scams | Warnings | Politics | Total | |||
|---|---|---|---|---|---|---|---|---|---|---|
Sentiment | Negative | Frequency | 75 | 9 | 0 | 13 | 1 | 6 | 43 | 147 |
% | 65,2% | 90,0% | 0,0% | 40,6% | 11,1% | 85,7% | 76,8% | 60,5% | ||
Adjusted Residual | 1,4 | −1,9 | −4,8 | −2,5 | −3,1 | 1,4 | 2,8 | |||
Neutral | Frequency | 25 | 1 | 9 | 11 | 5 | 1 | 9 | 61 | |
% | 21,7% | 10,0% | 64,3% | 34,4% | 55,6% | 14,3% | 16,1% | 25,1% | ||
Adjusted Residual | −1,1 | − 1,1 | 3,5 | 1,3 | 2,1 | -,7 | −1,8 | |||
Positive | Frequency | 15 | 0 | 5 | 8 | 3 | 0 | 4 | 35 | |
% | 13,0% | 0,0% | 35,7% | 25,0% | 33,3% | 0,0% | 7,1% | 14,4% | ||
Adjusted Residual | -,6 | −1,3 | 2,3 | 1,8 | 1,6 | −1,1 | − 1,8 | |||
Total | Frequency | 115 | 14 | 32 | 9 | 7 | 56 | 243 | ||
% | 100,0% | 10 | 100,0% | 100,0% | 100,0% | 100,0% | 100,0% | 100,0% | ||