1. Introduction
Sending information through emails, chat, and short messages becomes an essential skill for everyone who lives in the digital world today. On the other hand, social networking services (SNS) such as Facebook and Twitter have also become an important socializing tool recently. Through an online survey, I wanted to find out if there is any correlation between the numbers of emails a person sends a day and his or her daily social-networking activity in Japan.
2. Hypothesis
Before Carrying out the survey, I hypothesized that there was a strong correlation between the numbers of emails a person sends a day and his or her daily social-networking uses. More specifically, it was assumed that the more the person uses social networking services, the more he or she would send emails. Besides this main hypothesis, it was also expected that women send more emails than men do as is often said. As a result, it was assumed that the most-often email senders would be female SNS users and the least-often email senders would be male non-SNS senders.
3. Survey method
78 Japanese Internet users were participated in the survey as the sample population of ordinary Japanese Internet users. The survey asked them five questions about sending emails and SNS uses including some basic personal information such as gender and age. It was a six-page, web-based survey all in Japanese. Not only did I ask my friends and acquaintance to participate in the survey through email, but also posted the link to the inquiry on several online bulletin boards asking anyone to participate. I used the data received from July 19 to 23 for this analysis. All the questions were answered correctly without any unanswered ones, but there are some doubts that some of the participants did not answer the questions honestly (I'll discuss this issue later in this article).
4. Data description
4-1. Sample distribution: gender
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| Chart 4-1 |
4-2.Sample distribution: Age
In the second question, I asked the age range of the respondent. More than one third (36%) of the participants are in their teens, the 18% of them are in their twenties, another 18% are in their thirties, and 14% are in their forties. It can be assumed that most of the teens probably came from the online bulletin boards that I posted the link to my inquiring message, most of the twenties are my TUJ friends, and the thirties and forties are my old friends who are close to my age. The mean is 30.8 years old and the standard deviation is 9.08. However, there is a strong possibility that two outliers (age ranges 71-80 and 81-90) are false answers because there is no friend of mine who use the Internet on a daily basis over age 71 and the main users of the online bulletin board that I posted on are high school and college students. As a result, the mean without these outliers is 25.7 years old and the standard deviation without them is 9.66.
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| Chart 4-2 |
4-3. Result data: Emails/messages sent by a mobile phone per day
Next, I asked the respondents how many times a day they usually send emails to their friends and family through their mobiles (not for business purposes). The chart below is fairly skewed to the right. More than 60% of them send less than five emails a day. Since I did not give any options for the emails more than 31, it is difficult to know the distribution within that range. It could have been easier to identify outliers if more detailed ranges were given. The mean is 6.1 mails and the standard deviation is 10.41.
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| Chart 4-3 |
4-4. Result data: Emails/messages sent by PC per day
Next, I asked the respondents how many times a day they usually send emails to their friends and family through their PCs (not for business purposes). The chart below is strongly skewed to the right. More than 85% of them send less than five emails a day, which is less than that through a mobile phone. Again, since I did not give any options for the emails more than 31, it is difficult to know the distribution within the range more than 31. It could have been easier to identify outliers if more detailed options were given. Due to the less emails and bigger empty gap between the data than those in the third question, the mean becomes less and the standard deviation is much larger than those the mobile phone case. The mean is 4.1 mails and the standard deviation is 18.85.
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| Chart 4-4 |
4-5. Result data: Activity on SNS
In the last question, I asked whether the respondent regularly (at least more than once in two weeks) uses any SNSs such as Facebook and Twitter. According to the result, more than 60% said no (more detailed analysis will be shown in the next paragraph). It may weaken the basis of my hypothesis (the more one sends emails, the more he or she would participates in SNSs).
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| Chart 4-5 |
5. Statistical analysis
5-1. Gender difference in sending emails
I assumed earlier that female Internet users would send more emails than males. The following results show the same tendencies as I expected. The mean of the emails sent through a mobile phone is 4.6 in male users, whereas 11.8 in female users. In the case of sending emails through PC, the mean in males is 2.4 and that in females is 7.8. Both comparisons show that females send emails more than double or triple than males do. Since I did not give detailed ranges over 31, the same problem I referred earlier occurred again in the distribution of the data. It makes the standard deviation in each category larger (especially in males since there are big empty gaps between the data chunk and outliers as seen in the Chart 5-1).
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| Table 5-1 |
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| Chart 5-1 |
5-2. Comparison between SNS users and non-SNS users
There are some age differences seen in SNS users. Chart 5-2a shows the tendency of practicing social networking activity in each age range. It clearly shows that the younger a user is, the more he or she joins SNS (Non-SNS users do not show that kind of trend). The mean of the SNS users is 26.7, whereas that of non-SNS users is 33.2. However, as I mentioned earlier, there is a high possibility that most of the answers in the age ranges of 71-80 and 81-90 seem false. If these outliers are excluded, both means become almost the same (20.0 in SNS users and 20.8 in non-SNS users). The standard deviations without the outliers are 4.26 in SNS users and 5.94 in non-SNS users. Only a little difference is seen in ratio between male and female SNS users (Chart 5-2b and 5-2c). They are almost in the similar ratio (36% in males and 40 in females). Even though, it still implies that females are a little more active in using SNS than males.
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| Chart 5-2a |
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| Chart 5-2b |
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| Chart 5-2c |
5-3. Correlation between sending emails and SNS use
Here is the main purpose of this survey, the correlation between sending emails and SNS use. I tried to establish a correlation between them. It turned out that they have a negative association (Chart 5-3). All of the pairs between mobile and PC users and SNS and non-SNS users have a negative association between each other. Against my expectation, the results do not indicate that the SNS users send more emails than non-SNS users. The linear regression lines barely show that non-SNS users are less likely to send emails than SNS users both in mobile and PC (Chart 5-3), but the data does not strongly indicate that the SNS users actually send more emails than non-SNS users (Table 5-3). In addition to this, the undivided ranges over 31 emails prevent me again from predicting an appropriate Y value from the X value on the regression line.
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| Table 5-3 |
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| Chart 5-3 |
6. Conclusion
My survey analysis showed that there is a very low correlation between emails sent per day and SNS activity of an Internet user. On the other hand, the expectation that a female sends more emails than a male is proven. It indicates that women are more communicative than men as is usually said. As often referred in the chapters above, the options in the answers were not set appropriately so that it generated often outliers in the charts. It can be also said that one's SNS use should have been asked not only yes or no, but also how often he or she usually participates in the services. By evaluating more actual involvement in SNSs, I could have made much clearer regression lines in order to demonstrate the correlation between sending emails and SNS use. The sample population I used was also not reliable because some of the respondents are totally anonymous and do not know me at all, which might have allowed them to answer the questions irresponsibly. This survey taught me a lot about the important points in designing a survey.
