-The online interactions have become increasingly negative and aggressive, in particular when stereotyped topics are discussed. Based on extensive literature on aggression, the present study investigates the forms, the frequencies of the negative comments and the related both emotive and cognitive processes in response an offensive post toward Carola Rackete. A total of 1.249 comments on Twitter were analyzed by coding basic position toward the tweet, moral argumentation, underlying moral process, emotions and their intensity. Overall the results showed that online communication is largely denoted by negative tone and aggressive forms, even when a commenter would support the target of an aggressive communication. In particular, the gender aggression is carried out by the same women who became aggressive and much less prosocial than what one would expect l of aggression is relatively new, the phenomena of online aggression can be understood based on the traditional models developed in the extensive literature on aggression.
INTRODUCTION
Over the last years the online interactions have become
increasingly negative and aggressive (Pew Research Center,
2017). It is always more frequent to observe negative online
phenomena such as hate speech, flaming and trolls in
particular related to sensible ethical topics that can polarize
the public opinion. For instance, some of the most online
discussed topics concern immigration and stereotypes that
could lead to explicit forms of cyber-racism and
discriminations [1; 2]. Moreover, some groups are most
likely to became target of online aggression, as in the case
of girls and woman [
If this framework is typically applied to racists
discussions, recent studies have also shown that regardless
the ethical positions on discussions on ethical topics can be
characterized by a high degree of hostile emotions [
First based on social cognitive theory [
Moreover, the study of
stimulus-thought-emotion-reaction sequence for helping
versus aggressive response could be particularly interesting
in the case of stereotyped topic, as in the case of woman.
Several studies have attested that member of stereotypes and
prejudice can became more easily target of hate-motivated
aggression [3; 24]. In this case the aggression, usually acted
by multiple perpetrators, has be motivated not only by the
intent to hurt one victim but all member of victim’s social
category. Previous findings stressed the importance of
considering social category as well the gender of target and
agent of discriminatory and stereotyped forms of aggression
[
which are the emotional features of prosocial and proself stance toward an exhibition of a clear attack to woman image? Are the prosocial stances toward a woman public aggression featured by a third-party anger?
Specifically, in the present study we investigate the forms, the frequencies of the negative comments in response a post, and one of its comment, that intends to declare/exhibit an offensive message toward a specific woman who actively defend the right of a minority group (immigrants), and the women more in general. Based on above theoretical approaches and empirical studies, we expected to find aggressive comments also from commenters in defense of the attacked woman. We expected that both prosocial and proself stance will be featured by high levels of negative emotional activation.
II.
METHOD
The online communicative scenario relevant to this study is related to a message posted by Selvaggia Lucarelli, a popular Italian journalist and TV commentator, on July 2nd, 2019. The tweet was intended to condemn cruel and rude criticisms among women after the Sea-Watch case: at the end of June, the civil rescue vessel Sea-Watch 3, captained by Carola Rackete, entered the port of Lampedusa without permission with 42 migrants on board. (https://www.theguardian.com/world/2019/jun/29/sea-watch -captain-carola-rackete-arrested-italian-blockade) These facts have sparked heated debates in public opinion. The tweet was composed of text and an image. The image was a screenshot representing a dark humor meme shared by another woman on Facebook to insult Carola Rackete by making assumptions about her sexual habits. On the contrary, the text expressed indignation towards use of sexist hate speech online (with the aim of stigmatize this sexist conduct):
‘Donne che se la ridono condividendo ‘sta roba. Ho esaurito le parole.’
‘Women who laugh at sharing this stuff. I've run out of words.’
A total of 1.249 comments made in response to Selvaggia Lucarelli’s post, distributed from the 2nd to the 3rd of July 2019, were extracted through Twitter API. Authors can privately share extracted data, by guaranteeing commenters’ anonymity, in the interest of repeatability of analysis. All comments were manually filtered in order to better understand users’ point of view and exclude tweets that no longer exist. First of all, coders identified a level of agreement or disagreement with Lucarelli’s statement. In addition to this coding, the valence and intensity of emotions were examined considering both semantic and formal elements. Data coding carried out in this way led to the identification of basic position toward the tweet (pro and contro), moral argumentation/reasoning (aggressive, proself and prosocial), underlying moral process based on Bandura and Darley and Latanè models [27; 28] (see Table 1) and four emotions (joy, calm, anger and sadness) and their intensity (low vs high). Another control element in this investigation was the presence or absence of gender stereotypes in analyzed tweets.
A Chi Square analysis [χ2(1296)= 87,4; p< .001] pointed out how commenters who openly support the main tweet are featured by negative emotions, mainly anger (49,3%) and sadness (35,1%), while commenters against the main tweet express their positions in an angry (66,5%) or happy way (19.9%).
Rarely commenters in support of the journalist Lucarelli expressed their opinion by using a prosocial argumentation but they are mainly aggressive (63,5%); while people against the act of public stigmatization express their comment with a proself (56,3%) or aggressive act (33,5%) but in a very less extent compared to the pro position [χ2(1296)= 162; p< .001].
In particular when we consider the processes emerging from the commenters words we unexpectedly found that people who support Lucarelli act of public indignation for the sexist tweet report a greater percentage of dehumanization (26%)- more than the unsupportive commenters (9,9%) - and guilt attribution (21,8%) toward the woman who make fun of Carola. In this sense the woman became another victim in the ‘pro’ commenters. Another frequent process activated by the Lucarelli supporters is the responsibility displacement (10,7%), when commenters tend to attribute the responsibility of this ‘cultural level’ to politicians as in the case ‘Il fatto che il ministro del food blogging non condanni mai questa violenza verbale e scritta, di fatto, la sdogana’; on the other side commenters in favour of Lucarelli assume to themselves the shame of belonging to the female genre (Mi vergogno di essere donna...’: ‘I am ashamed of being a woman ’) A minimal part of the coded processes are devoted to principle recalling, women who ask if it is possible to denounce. Differently the commenters against the Lucarelli public act are mainly focused to the guilt attribution to the journalist or to Carola (25,7%) or to labelling euphemistically the indignation act as a political strategy toward the vice minister Matteo Salvini or comparing to the deviant act of the woman to the Carola ‘aggression‘ to Italian law (Ma che cosa stai dicendo??? Ora speronare una nave della guardia di finanza è un’azione giustificata; Transl: ‘But what are you saying ??? Now ramming a finance guard ship is justified ’). The difference between pro and agianst position are significant to the chi square analysis [χ2(697)= 164; p< .001]. The difference between Pro and Against the denouncing tweet of Lucarelli is very close to the gender difference, in the sense that women tend to dehumanize or attribute guilt or on the other hand assuming their responsibilities’ or recall to a legal principle.
When we consider the expressed emotions with respect
to the moral stances we can report several significant
differences [χ2(1296)= 189; p< .001] in the sense that the
aggressive one as we could expect is featured by anger
(59,8%) similarly to the proself one (49,1%) and differently
from part of prosocial stance that is featured mainly by
sadness (63,2%) but also anger (29,2%). But a tendency that
characterized the aggressive and the proself is the presence
of good percentages of joy (18,8% and 12,3% respectively)
that signal how the aggression and not supportive toward
women (against the aggression) is expressed by derision,
irony and ridicule that can be considered an indirect act of
aggression [
The present study confirmed how online communication
can be largely denoted by negative tone and aggressive
forms in most of the case, even when a commenter would
support the target of aggressive communication. The
denounce of an aggressive behavior towards a victim only
partly stimulates users’ sorrow or other deactivated
emotional states that could lead to a supporting scenario for
the victim of the aggression (Carola Rackete). Instead both
supporters and unsupporters of the journalist’s denounce
commented being mainly angry. Anger, that, as in other
studies, was associated with a series of aggressive
cognitions that feed the vicious cycle of aggression. In
particular, we saw that users who support the sexist
denounce on their side attribute the blame and dehumanize,
and they are more aggressive and less prosocial than
expectations. Pro sexists denounce people even get more
enraged than against ones, in which, on the contrary,
positive emotions emerged accompanied by acts of ridicule
or derision, presumably deriving from the attempt to use
humor to diminish and defend one's own social image [29;
30; 31]. The proself unexpectedly dehumanize less and
mostly focus on behavior with ‘euphemistic labeling’ and
‘advantageous comparison’, dampening the force of the
public denounce through lower emotional activation. On the
social network the gender aggression is carried out by the
same women who became aggressive and much less
prosocial than what one would expect. The high occurrence
of dehumanization mechanisms could be explained by the
fact that the Lucarelli’s post focused not only on sexist
attack against Carola Rackete, but also on woman who
made that attack. Thus, it is possible that dehumanization is
also related to the fact that this specific woman represents a
member of a "political" outgroup [