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# Attitudes Towards the Use of Emoji/Emoticon in Emails

Info: 2977 words (12 pages) Essay
Published: 8th Feb 2020

## Abstract

Attitudes towards Emoji/Emoticon use in Emails will be assessed and experimented on with different predictors in this lab report. There were 1407 participants, and the experimenters were under-graduate students. Results suggested that there is an overall positive attitude towards emoticon use in emails, as well as positive attitudes to emoticon use for people with higher levels of extraversion and younger participants.

Attitudes Towards the use of Emoji/Emoticon in Emails

This report will be analysing and discussing Attitudes towards the use of Emoji/Emoticons in emails. Electronic communication is highly prevalent in todays society, including the use of emoticons. This development has created implications for how humans communicate with one another, via emails either personally or through business (Goldman, 2017).

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Research has suggested that the use of emoticons in emails is useful and welcomed, giving an added layer to online mail (Huang, Yen, Zhang, 2008). Email is seen as important in the workplace, however, research has suggested that the use of emoticons in work-related emails is sometimes acceptable in some scenarios, though in most it is inappropriate and taboo (Skovholt, Gronning, Kankaanranta, 2014). However, there is not a lot of relevant information towards this topic, therefore, sound conclusions cannot be made as of yet. Research has also suggested that younger participants of similar studies have more positive attitudes towards emoticons in emails, they also scored a higher level of technology self-efficacy which was positively correlated with the use of emoji’s (Prada, Rodrigues et al., 2018). Personality is seen to play a large role in the use of emoticons in emails, and similar studies have also suggested that extraversion is the personality trait most likely to use emoticons in emails (Marengo, Gianotta, Settanni, 2017). Therefore, these findings link to this reports analysis on this topic.

The first research point that will be discussed throughout the report is, what are peoples’ attitudes towards the use of emoji/emoticons in emails, and which variables are able to predict people’s attitudes towards the use of them. The predictors are as follows: extraversion, technology self-efficacy, business context and age.

Four hypotheses were created for this experiment. Hypothesis one: People with a higher rate of extraversion are more likely to have a positive attitude towards emoji/emoticon use in emails. Hypothesis two: People with lower technology self-efficacy will have a more positive attitude toward emoji/emoticon use in emails. Hypothesis three: People have a more negative attitude towards emoticon use in business emails. Hypothesis four: People who are older will have a higher positive attitude towards emoji/emoticon use in emails.

Method

Participants

1407 participants (561 Males, 824 Females, 21 Other, 1 missing) took part in an online/in-person survey. Experimenters were part of a Griffith University, 3003PSY class who administered four surveys (two online, two in-person) to family and friends who were over 18. No one was compensated for their time. The age range was 18 to 81 (M= 31.44, SD= .57).

Measures

Seven predictors were measured in this survey. The psychometric properties were reliable, however, this experiment was only created for the Griffith University survey experiment. The sub-scales used throughout the measure was Attitudes towards Use of Emoji/Emoticon in Emails scale (reliability/Cronbach’s alpha equalled .92). Measured using a 7-point-scale, 1 = strongly disagree to 7 = strongly agree, an example of the type of question asked in the survey was, ‘Emoji/emoticons help communicate feelings in emails.’ The source of this sub-scale was created by 3003PSY students. Frequency of use was also a sub-scale, also scored on 7-point-scale. Personality was the third sub-scale, specifically extraversion was looked at  (reliability/Cronbach’s alpha equalled .83 for extraversion). Agreeableness, Neuroticism and Openness also included. Was scored using a 7-point-scale, 1 = strongly disagree to 7 = strongly agree, example of this is ‘Am the life of party?’ This was based off a pre-existing measure, the mini-IPIP6 measure of personality, which is reliable and distributes an important range over six main personality dimensions (Sibley, Luyten et al., 2011). Conservatism is the following sub-scale, which was a 5-point-scale. Then, Technology Self-efficacy, (reliability/Cronbach’s alpha equalled .87), it was a 5-point-scale, where 1 = strongly disagree to 5 = strongly agree, an example of a question asked, was ‘I am comfortable using Technology.’ Followed by both business and personal context. Which was a 2-point-scale, 1 = yes and 2 = no, an example of business context is, ‘Using Emoji/Emoticon in emails is appropriate for business emails?’ Other information that was reported was demographics of the participant.

Procedure

Research was gathered outside of experimenter’s labs. Four people were needed to do two online versions and two in-person surveys. The sequence is as follows: The student ID number of Griffith University student was recorded, as well as campus. The participant then completed survey questions to the best of their ability. Once questions related to the topic were completed they recorded their Year of Birth, Gender, Relationship Status and Education Level. There was 48 questions pertaining to the subject, either a 7-point-scale, 5-point-scale or yes-or-no scale rating was used. Once fully completed, online surveys were submitted and hard-copied versions were brought in by experimenters and the data was imputed in assigned computer lab; ready to be gathered together and analysed.

Results

A multiple regression was conducted using extraversion, technology self-efficacy, business context and age to predict attitudes towards the use of emoji/emoticons use in emails. Attitudes towards emojis questions 4, 8, 14 and 16 as well as the relevant extraversion questions 2 and 3 from personality were all reverse coded from a 7-point-scale where 1 = strongly disagree to 1 = strongly agree. Also, questions 2, 3, 4 and 5 were also reverse coded from a 5-point-scale in the technology self-efficacy, where 1 = strongly disagree to 1 = strongly agree.

Prior to analyses the data was examined and cleaned for evidence of data entry errors. The year of birth (YOB) was changed to record their reported age and the participants whose YOB was not provided to the survey was excluded. These participants were: 2, 3, 7, 10, 33 and 39. Inspection of the residual plots suggested that the assumption of normality was met, however, he assumption of homoscedasticity was violated. Therefore, the data was then examined for the presence of univariate and multivariate outliers. The data examined found four statistically significant univariate outliers in the business context boxplot, using the cut-off for p =.001. Removal of the univariate outliers did not alter the results; therefore, they were included in the final analysis. One statistically significant multivariate outlier was identified as having Mahalanobis’s Distance scores greater than 18.47, with the cut-off for p =.001 with four predictors. Therefore, this multivariate outlier was excluded from all of the final results.

After the exclusions conducted, a total of 1400 participants were therefore in the final analysis. The data was further examined for evidence of skew. Attitudes towards emoji/emoticons in emails, technology self-efficacy, business context and age were all found to have skewness to standard error ratios exceeding 3.29 in absolute value, with the cut-off for p =.001. Attitudes towards emoji use was moderately negatively skewed, it was then reflected and a logarithmic transformation was applied. As this transformation altered the nature of the results, reported results include reflected and transformed conservatism values, and should be interpreted accordingly. Technology self-efficacy was moderately positively skewed, and accordingly a transformation analysis was run, and continue to be reported with the transformation skew value. Business context was significantly negatively skewed, and it was then reflected and a logarithmic transformation was applied. As this transformation altered results, the analyses would continue to show reflected and transformed conservatism values. Age was also seen to be significantly positively skewed, therefore, the transformation analysis was run and would continue to be reported with the transformed skew value. Also, extraversion was negatively skewed, however it was not exceeding of 3.29 in absolute value, but was reflected, and further analyses will include the reflected values and be interpreted accordingly.

Table 1 displays the means, standard deviations and inter-correlations between attitudes towards the use of emoji/emoticons in emails, extraversion, technology self-efficacy, business context and age.Attitudes towards the use of emoji/emoticons in emails was significantly positively correlated with extraversion, and significantly positively correlated with technology self-efficacy. Furthermore, attitudes towards the use of emoji/emoticons was significantly negatively correlated with business context and also, age was significantly positively correlated with extraversion, and the business context was significantly negatively correlated with extraversion, and age was significantly positively correlated with extraversion as well.

Table 1: Means, Standard Deviations and Intercorrelations between Attitudes towards emoji/emoticons use in emails, Extraversion, Technology Self-efficacy, Business Context and Age.

 1 2 3 4 5 Attitudes towards emoji/emoticons used in emails (reflected) – Extraversion (reflected) 0.103 – Technology self-efficacy (transformed and reflected) 0.110 0.084 – Business context (reflected) -0.335 -0.101 -0.032 – Age (transformed) 0.035 0.065 0.350 0.046 M 3.60 0.77 2.12 1.12 3.36 SD 1.03 1.36 0.90 0.32 0.38

Table 2 shows the unstandardized and standardised regression coefficients, as well as the squared semi-partial correlations, and

. R for the model was found to be significantly/moderately different from zero, F(4, 47) = 50.20, p = .001 Overall, the model accounted for 12.6% of variability in attitudes towards emoji/emoticon use in emails. Examination of the B, β values and the

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${\mathit{sr}}^{2}$

values suggests that Business was the strongest predictor. Business accounted for -32.7% of unique variance in attitudes towards emoji/emoticons used in emails, with more business context individuals reporting less positive attitudes. Technology self-efficacy then further accounted for 8.9% of unique variance regards to attitudes towards emoji/emoticon usage in emails. By contrast, therefore, extraversion accounted for 6.5% but not at a significant level and age accounted for 1.4%, again not at a significant level of unique variance in terms of attitudes towards emoji/emoticon use in emails.

Table 2: Multiple Regression of Extraversion, Technology Self-Efficacy, Business Context and Age

 B SE B β ${\mathit{sr}}^{2}$ Extraversion 0.047 0.019 0.062 0.065 Technology Self-efficacy 0.102 0.030 0.089 0.089 Business context -1.023 0.079 -0.326 -0.327 Age 0.039 0.072 0.014 0.014

Note. ${R}^{2}$

= 0.126

Discussion

The experiment achieved the research aims, answered the research questions and from the outcomes shown from this experiment, showed that people have a positive attitude towards emoji/emoticon use in emails.

Hypothesis one is supported, that people which a higher level of extraversion are more likely to have a positive attitude towards emoticons in emails. Therefore, people with higher levels of extraversion are more likely to use emoticons than others. These results can also be linked with the findings of other studies, such as Marengo, Gianotta and Settanni (2017). Therefore, the results of this experiment support both the current theory and hypothesis one.

Hypothesis two was not supported, in that the results actually showed that people with a higher level of technology self-efficacy was seen to be more likely to use emoji/emoticons in emails. From the results gathered, it also corroborates with other sources being suggestive of the same conclusions.

Hypothesis three was supported, in that people have a more negative attitude towards emoji/emoticon use in business context emails. Outside studies support the findings in that emoji’s in business emails in viewed negatively. This replicates and supports previous research.

Hypothesis four was also not supported. The results are suggestive of people of a younger age are more likely to use emoticons in emails, this also corroborates with other reliable sources. Therefore, hypothesis four was not supported, and showed opposite results.

The sample size was large but was not a limitation to the data. However, data cleaning was necessary for these analyses. Generalizability of results could be argued to be fairly accurate as people with different descriptives partook in this survey experiment. Some issues to this experiment could have included, wrongly input data, or the participants not understanding questions correctly or answering in a standardised way. However, with a large sample size, this might have evened out. Implications of this study suggest that there is an overall positive attitude towards emoticon use in emails. And further research should delve into other personality types as well as deeper into technology self-efficacy and emoticon use.

## References

• Sibley, C. G., Luyten, N., Purnomo, M., Moberly, A., Wootton, L. W., Hammond, M. D., … & McLellan, L. (2011). The Mini-IPIP6: Validation and extension of a short measure of the Big-Six factors of personality in New Zealand. New Zealand Journal of Psychology, 40(3), 142-159.

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