The Dynamics of Social Media




The Dynamics of Social Media Responses

Wendy Perez Ramos

Florida International University


The Dynamics of Social Media Responses

Moral judgment is commonly swayed by irrelevant factors, whereby people tend to arrive at the judgment(s) about different actions as being wrong if they are predisposed to fury prior to the making of moral judgment. On the contrary, the bias for positive emotions makes unacceptable actions at times appear acceptable. In the context, dilemmas that came before the prevalent one influence the permissibility of the unwarranted actions. The violation of rationality norms occurs when people allow social consensus to take precedence to facts. In like manner, accepting conformity creates room for error and confusion to spread reign a group, whereas the making of independent decisions as well as resistance to conform tends to be socially constructive (Kundu & Cummins, 2013). In this case, resistance to conformity may be considered both moral and rational, as it is commonplace for people’s behaviors to be frequently judged based on whether the persons involved relied on their moral principles or they simply complied. Conformity is, however, considered illogical if a person holds the belief that social consensus should be awarded less weight in the decision in comparison to one’s beliefs and values. In a nutshell, conformity can possibly be an outcome of a rational process, whereby the concerned people chose to follow their beliefs and the truth at the expense of a lie.

Cyber bullying, which is the intense harassment of social media users by malicious persons, causes massive suffering to the victims and can be devastating when compared to traditional bullying. It is notable that public situations with behaviors that can clearly be observed to encourage conformity, whereby individuals toe the line when they experience pressure. With cyber bullying on the rise, potential advocates are encouraged to confirm through either supporting the bully or keeping quiet (Anderson et al., 2014). While challenging a bully is not an easy undertaking, as it is seen to deviate from the social norm, a bystander faces the dilemma of facing the criminal or doing nothing about it. It is notable that the former may potentially attract criticism from society and many people may not stand such criticism, hence the decision to adopt the ostrich approach. Usually, bystander’s intervention takes the form of dissenting to the views of the bully. Of importance to note is that modeling dissenting behavior can encourage bystanders to offer support to the victim to reduce the impact of the heinous acts.

The seeking of knowledge continuously takes place on various social media platforms, whereby the determinants of the messages obtained by an individual are the pages followed and the friends that one has. Unfortunately, the platforms are responsible for the spread of fake news, whereby some players hide their identities and post content to reinforce their positions. Notably, social norms exist on the platforms but people’s perception of the values vary for a number of reasons, which include platform type, anonymity, and the nature of relationships between friends (Perfumi et al., 2019). Moreover, conformity to social norms in the context of social platforms varies significantly from that of face to face, while social influence therein may be categorized into norms-oriented social influence and information-oriented one. Remarkably, it would be necessary to create a distinction between the two aspects. The implication is that online users who feel that they are anonymous may experience the temptation to disregard the opinions that they could be exposed to. The other implication may be the motive of the users of online platforms. Where the intention is communication at the expense of conformity to social norms, the communicators tend to disregard the norms completely, while they may consider them in other cases.

Moral dilemmas entail the determination of whether to accept harm in a bid to prevent bigger catastrophes, and decision-makers who reject harm are often viewed as warm, moral, trustworthy, and empathetic. The concepts originated in philosophy, an example of related sub-disciplines being utilitarian philosophy, which considers the impartial maximization of the greater good. In the context, decision-making systems focus on the action at hand against myriad factors, which include long-term goals, adherence to moral rules, and the application of moral grammar. Usually, people really care about individual moral reputation and dilemma decisions have an impact on standing (Rom & Conway, 2018). Furthermore, past research indicates that people can be considerably accurate when assessing how peers view them with self and social ratings converging when the traits in question involve public behaviors. As an illustration that people care about their presentation to others, many persons tailor public images to values and preferences that are perceived as being generally acceptable. In this case, some people are forced to conform to pressure for the rejection of harm than accepting it. In case of an opportunity to establish warmth through social interactions, it is commonplace for people to exhibit other qualities such as competence.

Social influence consists of some distinct, conceivable differences, one of which is normative social influence. The variant describes the influence to adhere to certain expectations that are other people cherish. The second process is informational social influence, which is the tendency to accept information, which is provided by people, as evidence for the support of reality. When both cases apply to the context of a product, the information provided should be uniform in terms of product quality and should possess a direct impact on the evaluation of consumers (Cohen & Golden, 1972). Interpersonal response orientations refer to the modes in which people commonly respond to others. Usually, people exhibit a balance between orientations and will be flexible based on the demands of various situations. The bottom line, however, is that an individual will show preference to some given orientation. In a nutshell, social influence operates in situations that do not exhibit strong normative pressures, while no noticeable difference exists between high and low uniformity treatment groups.

In general, we predict that participants who read unanimously supportive feedback will rate the Facebook user’s conduct as more acceptable than participants who read unanimously oppositional feedback, with those who read mixed feedback falling between these extremes.

More specifically, participants in the unanimously supportive condition will more strongly agree with supportive survey statements (“Abigail’s behavior was understandable, “Abigail’s behavior was reasonable”, “Abigail’s behavior was appropriate”, “I would advise Abigail to keep silent”, and “I would try to comfort Abigail”) and more strongly disagree with oppositional survey statements (“Abigail’s behavior was wrong”, “Abigail’s behavior was unethical”, “Abigail’s behavior was immoral”, and “Abigail’s behavior was unacceptable”) compared to participants in the unanimously oppositional condition, with participants in the mixed condition falling between these extremes. However, participants in both the unanimously supportive and unanimously oppositional conditions will strongly agree that they would give Abigail the same advice that her friends gave her.



The students are selected randomly from Florida University for the study and the sample size is one hundred and forty for the study. Among 140 students 44.3% were male and 52.1% were female, total male respondent are (n=62) and female respondents are (n=73), only 5 participants did not mention their gender. Participants consist of a population of 40% Hispanic American (n=56), Asian Americans were 6.4% (n=9), Caucasians were 25.7% (n=36) and Native Indians were 2.1% (n=3). While African Americans were 17.1% ( n=24) and Asian Americans who are almost 6.4% (n=9). See Appendices 1 and 2.

Materials and Procedure

According to procedure and methods of the study, students were selected randomly they supposed and opposed their reviews towards Abigail’s behavior which was either wrong or right. All the students have agreed to participate and they are part of the three documents which was given to them. According to the current situation Abigail has scored high marks in exam all students has failed but she got good marks in the exam as she used answer keys to answer the sheets. She got high marks in the exam her professor has planned to curve the grade. Each document shows the initial situation (if feedback supported her behavior, opposed and mixed) which led to study at different stage.

In the opposed condition, Abigail can avoid this mistake and she can score bad as other students got bad marks. But she has sued answer keys to answer the questions and score really good marks in exam. All of the respondent’s feedback is that she cannot have those grades and she should drop it and few respondents said that you don’t intend to cheat as professor should check while giving mark sheets to students and some called her dishonorably lucky to have those grades.

After analyzing the situations portrayed over, the participant proceeded to the rest of the study, which was made out of a series of questions for participants, in order to rate their impressions towards Abigail’s behavior. The questions were based on how wrong they thought the Abigail’s behavior was (1 = strongly disagree), the causal role of the Abigail and either her behavior was wrong (1= strongly disagree and 6= strongly agree), their thoughts on how much control the Abigail behavior was understandable and controllable (1= strongly disagree and 6= strongly agree), the nature of Abigail (1 = strongly disagree, 6 = strongly agree), how much her behavior was unethical (1 = strongly disagree, 6 = strongly agree), Abigail’s behavior was immoral (1 = strongly disagree, 6 = strongly agree), and how much Abigail’s behavior was appropriate (1 = strongly disagree, 6 = strongly agree), how much Abigail’s behavior was unacceptable (1 = strongly disagree, 6 = strongly agree). Part three of the questions were based on how would participants advise Abigail and how they would respond if they mistakenly received the answer key. The questions include if participant could advise Abigail to keep silent (1 = strongly disagree, 6 = strongly agree), if they could try to comfort Abigail (1 = strongly disagree, 6 = strongly agree), if they could give Abigail the same advice that her friends gave her (1 = strongly disagree, 6 = strongly agree), if they received the answer, they would keep silent (1 = strongly disagree, 6 = strongly agree), if they received the answer, they would confess (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems warm (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems good-natured (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems confident (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems competitive (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems sincere (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems moral (1 = strongly disagree, 6 = strongly agree), if they think Abigail seems competent (1 = strongly disagree, 6 = strongly agree). Part four asked for the participant’s demographic information, including gender, age, ethnicity, their first language, and whether they were a student at Florida International University. Concluding the study, the participants were asked to respond what feedback did Abigail’s friends give her in general.

We had several dependent variables in our study, but despite of these, our main objective involved the perceived behavior of Abigail and the opinions of the respondents, the number of statements that participants could create and the verification of manipulation regarding whether Abigail should tell to the teacher and she should lower her grades. We also anticipate that participants in the support condition would generate more statements of support than opposite or mixed statements



Using our study condition (supported vs. opposed vs. mixed) as our independent variable and whether participants recalled whether the Abigail should drop her grades, we ran a manipulation check in which we saw an big reaction, X2(4) = 147.04, p < .001. Participants in the support and oppose conditions said that Abigail received a mixed feedback (15.6% and 16.3%, respectively) while few participants in the mixed condition said that she received supported feedback (82.2%). Phi indicates that participants did support Abigail’s behavior no matter that her action was wrong. See Appendices 3 and 4.

Another tests were performed in order to support our hypothesis of Abigail’s behavior. In this case, the first One-Way ANOVA test showed big differences among our independent variable, the scenario conditions (supported, opposed, or mixed) and our dependent variable, showed that Abigail’s behavior was wrong, F(2,135) = 5.811, p = .005. Suddenly, the Tukey post hoc test was conducted supporting our hypothesis by demonstrating that participants were more likely to support the Abigail’s behavior in the opposed condition (M = 3.9512, SD = 0.94740) than in the feedback supported condition (M = 3.3261, SD = 0.73195). However, the tests showed that there were no a big difference in the mixed condition (M = 2.7959, SD = 0.99957) compare to opposed condition. The number of participants who supported the idea that Abigail’s behavior was wrong, attracted us since the results in a one-way ANOVA test revealed that the participants shared a mixed opinion, which in turn demonstrated that they were more opposed to Abigail’s behavior. F (2, 135) = 5.811, p< 0.01. with all of this data, we can said that these results indicate that Abigail’s behavior was not appropriate and blame as wrong. See Appendices 7 and 8.

Concluding, we ran an independent samples t-Test with the help of another dependent and independent variable to check if the participants would give Abigail the same advice that her friends gave her, which the result was extremely significant, (89) = -0.335, p < .01. Participants tempted to support more giving the same advice (M = 4.35, SD = 0.71) rather than opposed that decision (M = 4.40, SD = 0.78). See Appendix 5 and 6.


We predicted that the participants would feel responsible for Abigail’s behavior, somehow they remained in her position giving a mixed opinion of what they believed if their action was correct or incorrect. On the one hand, a large majority of the participants supported the idea that what Abigail had done is wrong, others supported the idea that Abigail should hide his irresponsibility; this led to behavior standards according to students giving an irrelevant statement that their conduct was neither good nor bad.

For many reasons, We cannot determine the acceptance of the participation, we fear a great variant of age that could affect the result of our study, for this reason, we would have to do a deeper study to determine the appropriate advice that Abigail can be given and if her behavior really was wrong.
























Anderson, J., Bresnahan, M., & Musatics, C. (2014). Combating weight-based cyberbullying facebook with the dissenter effect. Cyberpsychology, Behavior, and Social Networking17(5), 281-286.

Cohen, J. B., & Golden, E. (1972). Informational social influence and product evaluation. Journal of Applied Psychology56(1), 54.

Kundu, P., & Cummins, D. D. (2013). Morality and conformity: The Asch paradigm applied to moral decisions. Social Influence8(4), 268-279.

Perfumi, S. C., Bagnoli, F., Caudek, C., & Guazzini, A. (2019). Deindividuation effects on normative and informational social influence within computer-mediated-communication. Computers in human behavior92, 230-237.

Rom, S. C., & Conway, P. (2018). The strategic moral self: Self-presentation shapes moral dilemma judgments. Journal of Experimental Social Psychology74, 24-37.













Appendix 1: Race

  Frequency Percent Valid Percent Cumulative Percent
Valid Caucasian 36 25.7 25.7 25.7
  Hispanic 56 40.0 40.0 65.7
  Native Indian 3 2.1 2.1 67.9
  African American 24 17.1 17.1 85.0
  Asian American 9 6.4 6.4 91.4
  Other 12 8.6 8.6 100.0
  Total 140 100.0 100.0  


Appendix 2: Gender

Gender (1 = M, 2 = F)
  Frequency Percent Valid Percent Cumulative Percent
Valid Male 62 44.3 45.9 45.9
  Female 73 52.1 54.1 100.0
  Total 135 96.4 100.0  
Missing System 5 3.6    
Total 140 100.0    





Appendix 3: Condition and Attention Check Crosstabulation


Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Attention Check (1 = Support, 2 = Oppose, 3 = Mixed) Crosstabulation
  Attention Check (1 = Support, 2 = Oppose, 3 = Mixed) Total
  Feedback supported her behavior Feedback opposed her behavior Feedback was mixed  
Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support Count 37 1 7 45
    % within Condition (1 = Support, 2 = Oppose, 3 = Mixed) 82.2% 2.2% 15.6% 100.0%
  Oppose Count 1 35 7 43
    % within Condition (1 = Support, 2 = Oppose, 3 = Mixed) 2.3% 81.4% 16.3% 100.0%
  Mixed Count 5 4 39 48
    % within Condition (1 = Support, 2 = Oppose, 3 = Mixed) 10.4% 8.3%
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