After reading paper attached, write Your
General Discussion
section, this will be new in Paper V. Here, you will summarize
your results from BOTH studies and draw conclusions, but you will NOT use statistics
again. This section will evaluate both of your studies and see if (and how) they connect
and lead you to general conclusions. That is, your general discussion is the end of your
story, so make sure to tie it back to information that you presented throughout both of
your studies. You can also identify flaws in your study designs as well as propose new
directions for future research in this section.
APA format is mandatory and also this part should be two to three pages.
Runninghead:
F
ACEBOOK CO
N
SENSUS
1
FACEBOOK CONSENSUS
6
Facebook Consensus:
The Dynamics of Social Media Responses
Wendy Perez Ramos
Florida In
t
ernational 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 (Kundu & Cummins,
2
01
3
). The violation of rationality norms occurs when people allow social consensus to take precedence to facts (Kundu & Cummins, 2013). 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 (Kundu & Cummins, 2013). 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.
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 (Perfumi et al., 201
9
). 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 (Perfumi et al., 2019).
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, 201
8
). 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, 19
7
2). 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.
Study One
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.
Methods Study One
Participants
The students are selected randomly from Florida University for the study and the sample size is one hundred and forty for the study. Among
1
4
0
students
44.3
% were male and
5
2.1
% were female, total male respondent are (n=
62
) and female respondents are (n=
73
), only five participants did not mention their gender. Participants consist of a population of
40
%
Hispanic
American (n=
56
),
Asian American
s were
6.4
% (n=9),
Caucasian
s were
25
.7
% (n=
36
) and
Native Indian
s were 2.1% (n=3). While
African American
s were
17.1
% ( n=
24
) and Asian Americans who are almost 6.4% (n=9). See Appendices 1
Materials and Procedure
Based on the procedure used to this study, students had to look at the Facebook of a college student named Abigail. In this page, they would see a profile with a complete description of her. Also they see a demographic section which contains a long paragraph discussing an incident in which Abigail accidentally got an exam answer key during an exam and used it to get the best grade in the course. She feel ashamed about it and want some suggestions from her friends. The advices from Abigail’s friends varies, according to the level of understanding of her behavior. Some of her friend think that her conduct was corrected, while others said that she should be honest and tell her professor about her bad conduct.
Then, participants were given a series of statements in order to see their impressions towards Abigail and her cheating behavior as well as whether they agree with her friends advices. All the students have agreed to participate and got their questions sheet without noticing that each one was part of three different conditions. This was conducted in order to see if their feedback support the wrong behavior of Abigail, or if they are opposed this, or if they have a mixed feedback about it.
The participant proceeded to the second part of the study, which was made out of a series of questions, in order to rate their impressions towards Abigail’s behavior. They are asked to agree or disagreed with seven about Abigail, using a scale from 1 (strongly disagree) to 6 (strongly agree). These include , “Abigail’s behavior was wrong”, Abigail’s behavior was understandable”, “Abigail’s behavior was reasonable”, “Abigail’s behavior was unethical”, “Abigail’s behavior was immoral”, “Abigail’s behavior was appropriate”, and “Abigail’s behavior was unacceptable”.
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. In this part, statements were divided, for example statements 1 to 3 are related to the advice they would give Abigail (“I would advise Abigail to keep silent”, “I would try to comfort Abigail”, and “I would give Abigail the same advice that her friends gave her”). Statements 4 and 5 are based on how the participant would respond if they were in the same situation. Part four asked for the participant’s demographic information, including gender, age, ethnicity, their first language, and whether they were a student from 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, we were more involved on the perceived behavior of Abigail and the opinions of the participants if her behavior was wrong, understandable, or reasonable.
Results Study One
Using our study conditions (supported vs. opposed vs. mixed) and our independent variable, which was the impressions towards Abigail’s behavior, we use a chi-square. We saw that the chi square was significant, X2(4) =
14
7.04, p <
.001
. Most
Support
participants recalled seeing supportive friends comments (
8
2.2%
). Most
Oppose
participants recalled seeing oppositional friend comments (
81.4%
). Finally, most of the
Mixed
participants recalled seeing an average (81.1%). These findings indicate that participants saw our original study outcome manipulation as we intended. See Appendix 2.
In order to support our hypothesis of Abigail’s behavior, we performed some other observations. 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,
1
35
) = 5.81, p = .005. The Tukey post hoc test was conducted demonstrating that participants were more likely to support the Abigail’s behavior in the opposed condition (M =
3.95
, SD = 0.95) than in the feedback supported condition (M = 3.33, SD = 0.73). However, the tests showed that there were no a big difference in the mixed condition (M = 2.80, SD = 0.
10
) compare to opposed condition. See Appendix 4.
Concluding, we ran an independent samples t-Test to check if the participants would give Abigail the same advice that her friends gave her, which the result was significant, t (
89
) = -0.335, p < .01. Participants tended 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 3.
Discussion Study One
Our observations were clear enough to prove that our hypothesis was correct. Participants in the support condition supported more the idea that the action of Abigail was understandable and appropriate, compared to the participants in the opposite condition, but not to mention that the participants in the condition mixed were divided at both ends. However, participants in supported and opposite conditions agreed that they would give Abigail the same advice her friends gave him.
Study Two
Despite the fact that people of any gender could be exposed to any kind of negative or pissing comments, the search and exchange of knowledge occur continuously on social media platforms, and individual users of social media receive information based on the pages to which they subscribe (Perfumi et al., 2019). However, the challenge of sharing and receiving information faces the challenge of spreading fake news by users who hide their identity. The situation of spreading false news, however, does not mean the absence of social norms on platforms. The perception of standards, however, varies based on several factors, some of which include the type of platform, anonymity, and the nature of relationships between friends (Perfumi et al., 2019).
For some reasons, social media is provided to inform the differences between the perspectives of men and women, Idemudia et al. (2017). That is why it should be noted that women have a predisposition to assume passive roles in the media. Idemudia et al. (2017) affirm that gender occupies a special place in the generation of an understanding of people’s decisions regarding the adoption and use of new technologies. On the contrary, men enjoy more time for the use of social networks, mainly due to the nature of their roles and social expectations. Therefore, the opinions of the majority are likely to influence women in determining an individual’s behavior on social media platforms.
According to Knobloch-Westerwick (
200
7) moral judgment is generally influenced by factors that can be considered irrelevant and insignificant in some way, an example is the influence of fury. In context, an action that a happy person can describe as morally correct may be viewed differently by the same person in a state of rage and anger. In turn, Knobloch-Westerwick (2007) also posits that “… gender differences have repeatedly emerged in mood management research.” There, the observation is that men do not meet the predictions of mood management, while women select messages according to the theory of mood management. The influence of the insignificant factors, mentioned above, on judgment tends to be high among women compared to men.
The evaluation of a morality judgment by gender members, therefore, would require one to consider the emotional situation they were in at the time they made the judgment. However, the factor that can increase women’s judgment confidence is that they have the ability to avoid feelings of anger and frustration with the help of distraction (Knobloch-Westerwick, 2007). Similarly, gender members are more likely to allow social consensus to take precedence at the expense of norms of rationality. Generally, conformity with social consensus creates room for error and confusion to reign over a group. To avoid confusion, women members of society should be encouraged to avoid taking a passive position, as is the case in the media sector.
Social Media users often tend to rate the acceptability of user behavior based on the comments they receive from other users. For example, comments unanimously support the user’s subsequent impact on participants to believe that the behavior of the recipient of the comments is acceptable, while the opposite is true. The claim, however, is that perceptions of a user’s behavior tend to be different between male and female people. By way of illustration, while women can quickly conclude that a user’s behavior, and posts therein, are acceptable based on the opinions and comments of other users, men may exhibit a different perspective. In this case, a sizeable population of men should not necessarily approve of a user’s behavior despite approving comments from a variety of users. Greenwood and Lippman (2010) state that the strongest gender differences exist, among other factors, in media representation, content and selective exposure patterns (Greenwood and Lippman, 2010).
On the other hand, users of social networks that are considered synonyms tend to ignore people’s opinions about their messages and / or publications on social networks. To support the point of view, Kasahara (2017) states that “women do not reveal themselves with sensitive information and data to strangers.” Similarly, the empiricist claims that, compared to men, women tend to hide their personal information and identities in online domains and on social media. The implication is that anonymous users may not feel a significant impact of cyber bullying.
Other
factors that may contribute to women’s more privacy situation include security, privacy, and social roles / pressures.
In general, social influence consists of some distinguishable and conceivable differences, some of which are normative social influence and informational social influence. The first refers to the influence to meet the expectations that people in society appreciate, while the second is the tendency to accept the information provided by people as evidence to support reality. When both cases apply to the context of a product, the information provided must be uniform in terms of product quality and must have a direct impact on the evaluation of consumers Knobloch-Westerwick (2007). In terms of gender, women tend to exhibit both variants, therefore, they provide uniform information on the evaluation of the factors of interest. Capacity is not in question and Knobloch-Westerwick (2007) states that women have a high tendency to ruminate compared to men. Interpersonal response orientations refer to the ways in which people commonly respond to others. Women generally exhibit the ability to balance orientations compared to men. However, social influence in his case operates in environments devoid of strong regulatory pressures.
According to the aforementioned reports, there are significant differences between gender in the use and presence on social networks. That is why we wanted to evaluate the probability that misbehaviors named in social networks, such as Facebook, are more accepted, depending on the gender that publishes it. If we test a study related to gender and its support through social networks, we could predict that participants who read unanimously supportive feedback will rate the Facebook user’s conduct as more acceptable than participants who read mixed feedback.
More specifically, participants in the unanimously supportive condition will more strongly agree with supportive survey statements (“Abigail’s / Adam’s behavior was understandable,“ Abigail’s / Adam’s behavior was reasonable ”,“ Abigail’s / Adam’s behavior was appropriate ”,“ I would advise Abigail / Adam to keep silent ”, and“ I would try to comfort Abigail / Adam ”) in comparison to the mixed condition.
Method Study Two
Participants
Two hundred students from Florida University were inducted to participate in study two for the study and the sample size is one hundred and forty for the study. Among 200 students
41
% were male and
56
.5
% were female, total male respondent are (n=
82
) and female respondents are (n=
113
), only three participants considered their gender as other. Ages ranged from a minimum of 14 to a maximum of 83. Participants consist of a population of 6
1.5
% Hispanic American (n=
12
3), African Americans were 19% (n=
38
), Caucasians were 14% (n=
28
) and Native Indians were 0.5% (n=1). While some participant of others race were 4% ( n=8). See Appendix 6.
Materials and Procedure
Participants were asked verbally or otherwise, to participate in an online study with the purpose to conduct a research. Once the participant agreed to participate, he or she was directed to the survey developed through Qualtrics software. In order to follow standardized guidelines participants were notified of the risk and benefits of participating in the study before the attempted to the research material. Once they confirmed their approval, they were able to continue with the survey, which consisted of four sections.
In section one of the study, participants were manipulated without noticing that each one was part of three different groups “Support”, “Oppose”, and “Mixed”. All of them were given a series of statements in order to see their impressions towards Abigail and her cheating behavior as well as whether they agree with her friends advices. While reading each statement, they were asked to agree or disagreed using a scale from one (strongly disagree) to six (strongly agree).
In section two of the study, participants read one of two scenarios of a Facebook owner who cheat in an exam. These scenarios were identical to the one we used for study one, but in this case we changed the gender for Facebook owner to a male. In this study, however, we omitted the oppose condition, due to facts that it did not has a big difference compare with the supported condition. Similar to study one, participants continued with section two of the study, which asked them to rate their impressions of the Facebook owner’s test-taking behavior. Once they completed the seven statements, they proceed with the third part of the study, which once again, it was similar to our prior study. They now were asked to rate twelve statements about how they could advise the Facebook owner, how they would respond if they mistakenly received the answer key from the professor, and then generally rate the Facebook owner.
Section four of the study asked for some demographic information about the participants, including their gender, age, race/ethnicity, their first language, whether they were a student from Florida International University and their relationship status. Concluding the study, the participants were asked to respond what feedback did Facebook owner’s friends give her in general and what they think the gender of the Facebook page’s owner was.
Although of the several dependent variables we had, our main objective was to perceive the behavior of the Facebook owner and the opinions of the participants if his/her behavior was wrong, and if the participants would give them the same advise that their friends gave them.
Results Study Two
We pay closely attention whether the wrong behavior of the Facebook owner received supported or mixed feedback. Using our condition as our independent variable, we ran a manipulation check We saw that the chi square was not significant, X2(2) = 35.20, p < .001. Most Support participants recalled seeing supportive friends comments (
61
%). While, most of the Mixed participants recalled seeing an average (71%). Phi showed a small effect, due to the fact that we eliminated our opposed condition, doing that participants showed more interest in this study. See Appendix 7.
In order to test our first dependent variable, we ran a 2 X 2 factorial ANOVA with our Comment Condition (Supportive vs. Mixed), and Facebook Cheater Gender (
Male
vs.
Female
) as our independent variables and the perceived of their behavior was wrong as our dependent variable. Our results depicted that there is not a significant main effect for comment condition on the wrong behavior, F(1,
196
) = 1.18, p > .05, meaning that there was not differences between the
Mixed Comments
(M =
4.0
0, SD = 1.36) and
Supportive Comments
(M =
4.21
, SD = 1.
37
). Analyzing our Gender Condition results, we can say there was no main effect, F(1, 196) =
.067
, p >.05, with Male Facebook cheater (M =
4.08
, SD = 1.37) not differing from
Female Facebook Cheater
(M =
4.13
, SD = 1.36). See Appendix 8.
Since there was no effect between (Supportive vs. Mixed comments and Male vs Female Gender) and the dependent variable, we exanimated the interactions between them. Simple tests showed that there was no interaction of Gender and the scenario condition, F(1,
98
) = .13, p > .05, with no differences between Male Cheater (M =
4.16
, SD = 1.
50
), and Female Cheater (M =
4.26
, SD = 1.23). Simple tests also showed there was no interaction with Comment Condition, F(1, 98) = .34, p > 0.5, depicting once again no difference between Supportive Comments (M = 4.16, SD = 1.50) and Mixed Comments (M = 4, SD = 1.23). See Appendix 9.
For our second dependent variable, we did another 2 X 2 ANOVA with our same independent variables Comment Condition (Supportive vs. Mixed), and Facebook Cheater Gender (Male vs. Female), but now our dependent variable now was “I would give them the same advise that their friends gave them”. Results demonstrated a significant main effect for the comment condition for giving the same advice, F(1, 196) = 5.12, p < .05. Participants seems to have Mixed comments in regards they would give the same advise that the Facebook owner’s friends gave them (M = 3.95, SD = 1.64) than support the idea of giving them the same advise that their friends gave them (M = 3.
46
, SD = 1.40). However, there was not a significant main effect for the gender condition, F(1, 196) = .0
53
, p > .05, with Male Facebook cheater (M =
3.73
, SD = 1.56) not showing a big difference compared to the Female Facebook Cheater (M =
3.6
8, SD = 1.52). See Appendix 10.
Discussion Study Two
Our observations demonstrated that our predictions were wrong. Participants in the support and mixed conditions think that the Facebook owner’s behavior was wrong. Even when we manipulated the gender of the Facebook owner and performed some other simple test there was no interaction between our independent variables and dependent variable. However, our observations for our second variable “I would give them the same advise that their friends gave them” participants had more mixed feedback than supportive.
References
Cohen, J. B., & Golden, E. (1972). Informational social influence and product evaluation. Journal of Applied Psychology, 56(1), 54.
Greenwood, D. N., & Lippman, J. R. (2010). Gender and media: Content, uses, and impact. In Handbook of gender research in psychology (pp. 6
43
-669). Springer, New York, NY.
Idemudia, E. C., Raisinghani, M. S., Adeola, O., & Achebo, N. (2017). The effects of gender on the adoption of social media: An empirical investigation. Retrieved from https://www.researchgate.net/publication/319130
49
6_The_Effects_of_Gender_On_Social_Media_Adoption_The_Effects_of_Gender_On_The_Adoption_of_Social_Media_An_Empirical_Investigation
Kasahara, G. M. (2017). Gender Differences in Social Media Use and Cyberbullying in Belize. Retrieved from https://p
df
s.semanticscholar.org/0379/2756cb77f4f637c3
133
cf34eb9702bcceeb5
Knobloch-Westerwick, S. (2007). Gender differences in selective media use for mood management and mood adjustment. Journal of Broadcasting & Electronic Media, 51(1), 73-92.
Kundu, P., & Cummins, D. D. (2013). Morality and conformity: The Asch paradigm applied to moral decisions. Social Influence, 8(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 behavior, 92, 230-237.
Rom, S. C., & Conway, P. (2018). The strategic moral self: Self-presentation shapes moral dilemma judgments. Journal of Experimental Social Psychology, 74, 24-37.
Appendices
Appendix 1: Demographics – Study One
Race |
|||||||||||||||||||||||||||
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
||||||||||||||||||||||||
Valid | Caucasian | 36 | 25.7 | ||||||||||||||||||||||||
Hispanic | 56 |
40.0 |
65.7 |
||||||||||||||||||||||||
Native Indian | 3 | 2.1 |
67.9 |
||||||||||||||||||||||||
African American | 24 | 17.1 |
85.0 |
||||||||||||||||||||||||
Asian American | 9 | 6.4 |
91.4 |
||||||||||||||||||||||||
Other | 12 |
8.6 |
100 .0 |
||||||||||||||||||||||||
Total |
140 |
Gender (1 = M, 2 = F) |
|||||||||
Male | 62 | 44.3 |
45 .9 |
||||||
Female | 73 |
52.1 |
54.1 |
||||||
135 |
96.4 |
||||||||
Missing |
System |
5 | 3.6 | ||||||
Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Attention Check (1 = Support, 2 = Oppose, 3 = Mixed) Crosstabulation |
|||||||||||||||||||||||||||||||||||||||||
Attention Check (1 = Support, 2 = Oppose, 3 = Mixed) | |||||||||||||||||||||||||||||||||||||||||
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 | 35 | 43 | |||||||||||||||||||||||||||||||||||||||
2.3% |
81.4% |
16.3% |
|||||||||||||||||||||||||||||||||||||||
Mixed | 4 |
39 |
48 |
||||||||||||||||||||||||||||||||||||||
10.4% |
8.3% |
81.3% |
|||||||||||||||||||||||||||||||||||||||
40 | 53 |
136 |
|||||||||||||||||||||||||||||||||||||||
31.6% |
29 .4% |
39.0% |
Appendix 2: Crosstabs and Chi-Square – Study One
Chi-Square Tests |
|||||||||||||||
Value |
df |
Asymptotic Significance (2-sided) |
|||||||||||||
Pearson Chi-Square |
147.039a |
.000 |
|||||||||||||
Likelihood Ratio |
142.630 |
||||||||||||||
62.028 |
Appendix 3: T-test and statistics – Study One
Independent Samples Test |
||||||||||||||
Levene’s Test for Equality of Variances |
t-test for Equality of Mean s |
|||||||||||||
F |
Sig. |
t |
Sig. (2-tailed) |
|||||||||||
Part III: I would give Abigail the same advice that her friends gave her |
Equal variances assumed |
.759 |
.3 86 |
-.335 |
89 |
.739 |
||||||||
Equal variances not assumed |
-.334 |
87.697 |
Group Statistics |
|||||||||||||||||||||
N | Mean |
Std. Deviation |
Std. Error Mean |
||||||||||||||||||
Part III: I would give Abigail the same advice that her friends gave her | 46 |
4.3478 |
.70608 |
.10411 |
|||||||||||||||||
4.4000 |
.78044 |
.11634 |
Appendix 4: ANOVA and Descriptive Statistics – Abigail’s behavior was wrong – Study One
ANOVA |
|||||||||||||||
Part II: Abigail’s behavior was wrong |
|||||||||||||||
Sum of Squares |
Mean Square |
||||||||||||||
Between Groups |
9.434 |
2 |
4.717 |
5.811 |
.004 |
||||||||||
Within Groups |
107.970 |
133 |
.812 |
||||||||||||
117.404 |
Descriptive |
||||||||||||
Part II: Abigail’s behavior was wrong | ||||||||||||
Std. Error |
95% Confidence Interval for Mean |
Minimum |
Maximum |
|||||||||
Lower Bound |
Upper Bound |
|||||||||||
3.3261 |
.73195 |
.10792 |
3.1087 |
3.5434 |
2.00 |
6.00 |
||||||
41 |
3.9512 |
.94740 |
.14796 |
3.65 22 |
4.2503 |
1.0 0 |
||||||
49 |
3.7959 |
. 99 957 |
.14280 |
3.5088 |
4.0830 |
|||||||
3.68 38 |
.93256 |
.07997 |
3.52 57 |
3.8420 |
Multiple Comparisons |
||||||
Dependent Variable: Part II: Abigail’s behavior was wrong |
||||||
Tukey HSD |
||||||
(I) Condition (1 = Support, 2 = Oppose, 3 = Mixed) |
(J) Condition (1 = Support, 2 = Oppose, 3 = Mixed) |
Mean Difference (I-J) |
95% Confidence Interval | |||
– .62513* |
.19352 |
– 1.0838 |
– .1665 |
|||
– .46983* |
.18497 |
.033 |
– .9083 |
– .0314 |
||
.62513* | .1665 | 1.0838 | ||||
.15530 |
.19070 |
.695 |
– .2967 |
.6073 |
||
.46983* | .0314 | .9083 | ||||
-.15530 |
-.6073 |
.2967 |
Appendix 6: Demographics – Study Two
Statistics |
||||||
What is your age? |
What is your gender? |
What is your race/ethnicity? – Selected Choice |
||||
199 |
198 |
|||||
28.61 |
1.60 |
2.41 |
||||
Median |
2 4.00 |
|||||
Mode |
22 | |||||
17.701 |
.521 |
1.183 |
||||
14 | ||||||
221 |
6 |
Demographic – What is your gender? |
||||||
82 |
41.0 |
41.4 |
||||
113 | 56.5 |
57.1 |
98.5 |
|||
1.5 | ||||||
99.0 |
||||||
1.0 | ||||||
200 |
Demographic – What is your race/ethnicity? |
|||
28 |
14.0 |
14.1 |
|
123 |
61.5 |
62.1 |
76.3 |
.5 |
76.8 |
||
38 |
19.0 |
19.2 |
96.0 |
Others–Please specify |
8 | 4.0 |
Appendix 7: Crosstabs and Chi Square – Study Two
Comment Condition (1 = Support, 2 = Mixed) * Without looking back, what general feedback did the Facebook owner’s friends give them? Crosstabulation |
|||||||||||||
Without looking back, what general feedback did the Facebook owner’s friends give them? | |||||||||||||
The feedback supported their behavior |
Unknown |
||||||||||||
Comment Condition (1 = Support, 2 = Mixed) | Supportive Comments | 61 | 29 | 10 | |||||||||
% within Comment Condition (1 = Support, 2 = Mixed) |
61.0% |
29.0% |
10.0% |
||||||||||
% within Without looking back, what general feedback did the Facebook owner’s friends give them? |
70.9% |
71.4% |
|||||||||||
% of Total |
30.5% |
14.5% |
5.0% |
||||||||||
Mixed Comments | 25 | 71 | |||||||||||
25.0% |
71.0% |
4.0% |
|||||||||||
29.1% |
28.6% |
||||||||||||
12.5% |
35.5% |
2.0% |
|||||||||||
86 | 100 | ||||||||||||
43.0% |
50.0% |
7.0% |
|||||||||||
35.281a |
|
36.400 |
|
12.088 |
.001 |
N of Valid Cases |
Appendix 8: ANOVA Their Behavior Was Wrong – Study Two
Descriptive Statistics |
||||||||||||||||||||
Dependent Variable: Their behavior was wrong |
||||||||||||||||||||
Facebook Cheater Gender (1 = Male, 2 – Female) |
||||||||||||||||||||
Male Facebook Cheater |
4.16 |
1.503 |
50 | |||||||||||||||||
Female Facebook Cheater | 4.26 |
1.226 |
||||||||||||||||||
4.21 |
1.365 |
|||||||||||||||||||
4.00 |
1.229 |
|||||||||||||||||||
1.485 |
||||||||||||||||||||
1.356 |
||||||||||||||||||||
4.08 |
1.368 |
|||||||||||||||||||
4.13 |
1.361 |
|||||||||||||||||||
4.11 |
Tests of Between-Subjects Effects |
||||||||||||
Source |
Type III Sum of Squares |
|||||||||||
Corrected Model |
2.455a |
.818 |
.438 |
.726 |
||||||||
Intercept |
3370.205 |
1803.134 |
||||||||||
CommentCondition |
2.205 |
1.180 |
.279 |
|||||||||
GenderCondition |
.125 |
.067 |
.796 |
|||||||||
CommentCondition * GenderCondition |
||||||||||||
Error |
366.340 |
196 |
1.869 |
|||||||||
3739.000 |
||||||||||||
Corrected Total |
368.795 |
a. R Squared = .007 (Adjusted R Squared = -.009)
Appendix 9: Simple Tests – Their Behavior Was Wrong – Study Two
a. Facebook Cheater Gender (1 = Male, 2 – Female) = Female Facebook Cheater
1.690 b |
1.690 |
.912 |
.342 |
||||
1705.690 |
920.370 |
||||||
181.620 |
98 |
1.853 |
|||||
1889.000 |
|||||||
183.310 |
99 | ||||||
a. Facebook Cheater Gender (1 = Male, 2 – Female) = Female Facebook Cheater | |||||||
b. R Squared = .009 (Adjusted R Squared = -.001) |
a. Comment Condition (1 = Support, 2 = Mixed) = Mixed Comments
Tests of Between-Subjects Effects |
|||
5.684E-14 b |
5.684E-14 |
1.000 |
|
1600.000 |
861.538 |
||
182.000 |
1.857 |
||
1782.000 |
|||
a. Comment Condition (1 = Support, 2 = Mixed) = Mixed Comments | |||
b. R Squared = .000 (Adjusted R Squared = -.010) |
Dependent Variable: I would give them the same advice that their friends gave them |
|
3.52 |
1.542 |
3.40 |
1.262 |
3.46 |
1.403 |
3.94 |
1.570 |
3.96 |
1.714 |
3.95 |
1.635 |
3.73 |
1.563 |
3.68 |
1.523 |
3.71 |
1.539 |
Appendix 10: ANOVA I would give them the same advice that their friends gave them – Study Two
12.375a |
4.125 |
1.761 |
.156 |
2745.405 |
1171.768 |
||
12.005 |
5.124 |
.025 |
|
.053 |
|||
.245 |
.105 |
.747 |
|
459.220 |
2.343 |
||
3217.000 |
|||
471.595 |
a. R Squared = .026 (Adjusted R Squared = .011)