Fig 1.
Average proportions of positive, neutral, and negative emotions prior to each observed tweet.
The Baseline model (left) discounts for the effect of emotional contagion by means of a reshuffling strategy. The three bars (Negative, Neutral, and Positive) respectively show the average proportions of emotions prior to posting a negative, neutral, or positive tweet. For each negative tweet posted, on average its author was previously exposed to about 4.34% more negative tweets than expected by the Baseline model. For each positive tweet posted, on average its author was previously exposed to about 4.50% more positive content. Note how the distribution of emotions before posting a neutral tweet almost perfectly matches that of the Baseline model. The numbers inside the columns represent the exact proportions ± the standard errors. Error bars represent standard errors.
Fig 2.
Distributions of positive and negative stimuli before positive and negative responses.
The four quadrants show the probability distributions of a negative response prior to a negative (bottom left) or positive (bottom right) stimulus, or a positive response prior to a negative (top left) or positive (top right) stimulus.
Fig 3.
Relationship between stimulus and response valence in Twitter.
The emerging linear relationship (R2 = 0.975) suggests that there is a strong correlation between stimuli and responses in terms of valence (difference between positive and negative sentiments in the set of tweets).
Fig 4.
Measurement of emotional contagion on users’ content posted on Twitter.
The main plot shows the number of users as function of the fraction of their tweets affected by emotional contagion. The inset shows the cumulative distribution. About 80% of the users have up to 50% of their tweets affected by emotional contagion, while the remainder 20% of users exhibits effects of emotional contagion on more than 50% of the posts they produce.
Fig 5.
Different extent of emotional contagion on the two groups of scarcely and highly susceptible users.
Highly susceptible users are significantly less inclined to adopt negative emotions than the scarcely susceptible ones, but equally likely to adopt positive emotions. In general, the likelihood of adopting positive emotions is much greater than that of negative emotions.