Method
Sampling
To fulfill the goals of this study, a survey was conducted in spring at Tsinghua University covering both undergraduate and graduate students, excluding international students. We handed out 721 questionnaires and had 521 respondents. The response rate was 73.1%. For sampling procedure, first, whole lists of student dorm in three categories (bachelor, master and doctoral students) were made. Second, according to the proportion of numbers of students in three categories, the number of sample dorms for each category was calculated. Third, a sample size of 141 dorms were randomly selected, composing of 53 for the category of bachelor, 55 for master, and 33 for doctoral students. Once the dorms were selected, we handed questionnaire to all students in that dorm. Each sample dorm was visited almost 4 times unless we collected all answered questionnaires in that dorm before the fourth visit.
Measures
Political Participation
Political participation is measured with references of several western scholars’ works but combined with Chinese students’ character of political participation behavior. This study emphasizes the concept of political participation is behavior not attitude. Three levels of political participation is considered, a) political participation related with gathering controversial information or news, b) civil participation with an focus on caring about public life, c) in comparison with previous categories, more radical political participation behaviors. A specific list of three forms of political participation is described as following
Table 1 Factor Analysis of Behaviors of Political Participation
| Factor Loadings | |||
| a)Info- participation | b)Civil participation | c)Radical participation | |
| Talking about political news with others | .823 | ||
| Reading political news | .775 | ||
| Forwarding or sharing political news | .671 | ||
| Making suggestion on development of your organization | .625 | ||
| Listening to speech of political content | .560 | .509 | |
| Donation | .468 | ||
| Commenting on news events | |||
| Organizing activities for charity | .760 | ||
| Community service | .686 | ||
| Making a complaint for public interest | .577 | ||
| Giving a speech on a topic of public interest | .564 | ||
| Forwarding an email about public affair | .561 | ||
| Taking part in online petition | .481 | ||
| Wearing clothes with an political meaning | .777 | ||
| Protesting | .762 | ||
| Taking part in an assembly | .564 | ||
| Contact media for public affair | .400 | .553 | |
| Boycotting | .465 | ||
| Extraction Method: Principal Component Analysis, explaining 48.1% variance.
Rotation: Varimax with Kaiser Normalization A. Rotation converged in 5 iterations |
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Respondents were asked how often they have done these behaviors in the past 12 months. The frequency of conducting behaviors is measured in 5 points. “5” stands for “most frequent” and “1” stands for “never have done”. The results of factor analysis show KMO>7, sig=0, and it explained 48.1% variance. Through factor analysis, we extract information of political participation and group these indicators in three dimensions: information participation, civil participation and radical participation. Later we will use these grouped indicators to build structural equation model.
Intensity of SNS use
Intensity of SNS use is considered in two dimensions, time spent on SNS and frequency of SNS use. In the survey, Renren.com is the representative of SNS, not only because Renren has all typical functions of SNS but also it is the most popular SNS website among college students in China. We can see from Table2, 86.1% students are users of Renren. Then Students were asked how often they log on to Renren and how much time they spent on it every day. The descriptive statistics is for intensity of SNS use is Table3.
Table 2 Renren membership
| Are you a user of Renren.com | ||
| Frequency | Proportion | |
| No | 69 | 13.1 |
| Yes | 454 | 86.1 |
| Missing | 4 | .8 |
| Total | 527 | 100.0 |
Table 3 descriptive statistics of Intensity of SNS use
| Note | Min | Max | Mean | SD | |||
| Time spent on Renren every day | 1=less than 10 minutes
6=over 4 hours |
1 | 6 | 2.49 | 1.299 | ||
| Frequency of logging to Renren | 1=less than once a day 5=over 7 times a day | 1 | 5 | 2.72 | 1.210 | ||
Purpose of SNS Use and Internet Use
To measure the purpose of students’ use of SNS and the Internet, I firstly listed several activities can be done at these platforms and let them choose the frequencies of doing these activities from a scale of 1 to 5. Then adopting factor analysis to extract common features of these activities, we can summarize their purpose in three dimensions for each types of use.
Table 4 Factor Analysis of Purpose of SNS use
| Factor Loadings | |||
| Networking | Self expression | Entertainment | |
| Read friends’ updates | .817 | ||
| Post an article | .783 | ||
| Sharing | .497 | .498 | |
| Upload a picture | .839 | ||
| Leave a message | .592 | .424 | |
| Online chat | .400 | .578 | |
| Playing games | .876 | ||
| Refreshing updates | .740 | ||
| Changing status | .610 | .435 | |
| Extraction Method: Principal Component Analysis. Explaining 62.4% variance
Rotation: Varimax with Kaiser Normalization A. Rotation converged in 5 iterations. |
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Table5 Factor Analysis of Purpose of Internet Use
| Factor Loadings | |||
| Acquiring info | Self expression | Entertainment | |
| Writing emails | .786 | ||
| Reading news from portals | .705 | ||
| Reading news using RSS | .563 | ||
| Visiting forums and BBS | .565 | ||
| Online music | .567 | ||
| Online games | .818 | ||
| Visiting social networking sites | .464 | ||
| Working on a blog | .754 | ||
| Online purchasing | .542 | ||
| Forwarding emails | .571 | ||
| Micro-blogging | .825 | ||
| Extraction Method: Principal Component Analysis. Explaining 50.4% variance
Rotation: Varimax with Kaiser Normalization A. Rotation converged in 4 iterations. |
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It is indicated from Table 4 and 5 that students usually practice the main function of these platforms, seeking information on the internet and networking on SNS respectively. These platforms provide them with opportunities to express themselves by commenting, posting pictures and for entertainment.
Sociodemographics
The variables included gender (male = 66.3%), age (M = 22.72, SD = 3.16), family monthly income per person (ranging from 1=below 118 USD to 5=over 2212 USD, M=2.89, SD=1.25), and GPA (ranging from 1=top 20% to 4=bottom 20%, M=2.17, SD=0.89).
Other variables
Political attitude include political knowledge and political interest. Both are self assessed by respondents in the questionnaire in a scale of 1 to 5. Participation skills are measured by asking questions from no.18-no.23. Every positive answer will be marked 1 point, so the scale is based on the sum of the positive answers from 0 to 6.