در آن سوی دیوار بزرگ آتش چه چیزی وجود دارد؟ انگیزش کاربران وب چینی برای دور زدن سانسور در اینترنت

Abstract Firewall bypassing is referred to as the behaviors of Internet users who resort to any software or proxy to get access to the websites or online resources that are blocked by the Great Firewall (GFW). Under the uses and gratification framework, a web-based survey (N = 319) was conducted to explore Chinese Internet users’ motivations of bypassing firewall in and outside Mainland China. The findings showed that Chinese Web users bypassed the firewall in China mainly for information and socializing, and bypassed outside China primarily for entertainment. Comparison between the motivations for bypassing GFW in and outside China was conducted among the participants who had experience in both cases. Theoretical and practical implications were discussed.

1. Introduction The past decade witnessed an exponential growth of worldwide Internet use. Statistics by Internet and Telecommunication Union or ITU (2011) showed that the number of Internet users has doubled between 2005 and 2010, the number in which year surpassed the two billion mark and reached 2.4 billion globally in 2012, accounting for 34.3% of the world population (Internet World Stats., 2012). Internet, particularly with the proliferation of social media, enables users to overcome the geographic limitation, and be connected with other users from all over the world. Consequently, united Internet users become an influential emerging power, and play an critical role in shaping the landscape of online participatory collaboration, online freedom of expression popular culture, social movements, etc. (Kahn and Kellner, 2004, MacKinnon, 2009, MacKinnon, 2012 and Shirky, 2011). Among many functions that Internet empowers users to perform, a unique one is online content sharing (Kaplan & Haenlein, 2010), which has attracted a large number of Web users from all over the world who use Internet as a platform to share content. During this process, video-sharing based social media, such as YouTube, have played an essential role in setting trends of popular culture online, creating celebrities, and providing a globally networked stage for individuals and organizations. Due to its globally available platform and the features of visual language, video messages from non-English speaking countries also enjoy the opportunity to attract the worldwide attention. For example, the music video Gangnam Style, from a South Korean signer PSY, has been viewed more than 1.48 billion times as of March 2012 (see Gangnam Style’s YouTube page, 2012) and become the most viewed video online. For another example, one Taiwanese pop song, Bobee, also got wider global reach due to its popularity on YouTube (CNN, 2011). Overcoming the language barriers and geographic limitation, these pop songs come to be a global cultural phenomenon. Not only the pop culture products, the regional user-generated content also received international interests. For example, the Bus Uncle, a six-minute Cantonese video clip of a heated quarrel between two men aboard a bus, was the most viewed video in May 2006 and caused a cultural sensation in East Asia (Guardian., 2006). However, none of these viral videos that later became the global web or cultural phenomena was from Mainland China, where reside 538 million Internet users (Internet World Stats, 2012). Why is that? One possible reason would be the fact that such worldwide popular video-sharing based social media, like YouTube, and other social networking sites (SNSs), such as Facebook and Twitter, are not available to Chinese users, due to the Internet censorship, which blocked more than 18,000 websites in Mainland China (Zittrain & Edelman, 2003). Much research have devoted to Internet censorship as a global issue as well as Internet censorship in China (Bamman et al., 2012, MacKinnon, 2009 and MacKinnon, 2012). Bamman, O’Connor, and Smith (2012) noticed that previous work suggested four dimensions of Internet censorship in China: network filtering, search filtering, chat censorship, and blog censorship. Among these four dimensions, network filtering based on IP and DNS filtering are usually referred to as the Great Firewall (GFW) that prevents Internet users in Mainland China from connecting to certain websites. Therefore, even though one Chinese TV singing competition show could easily receive more than 5 million views within one day online (see I Am a Singer’s Youku page, 2013), due to inaccessibility of YouTube, video clips from China usually do not reach out globally, let alone receive international attention. Internet censorship, particularly the GFW, has long been a controversial issue in the application of Information and Communication Technology (ICT). Individuals upholding the policy maintain that it helps to unify ideology and stabilize the society (Krochmal, 1998), while users against it assert that censorship deprives them of the freedom of expression and the right to acquire online information (Zhou, 2008). To cope with the Internet block and obtain the online resources needed, there are a great number of Web users who resort to various types of software and applications to bypass China’s GFW (Interactive Intelligence, 2008, Mathieson, 2006 and Shi, 2010) so as to be exposed again to a great deal of knowledge and information from the blocked foreign websites, and benefit from the latest ICT. Stimulated by the significance of ICT development in the digital age, Internet censorship and the GFW scaling in China have received a lot of research interests. Prior studies have paid attention to how network filtering prevents access to online information in China (MacKinnon, 2012), how censorship is conducted on blogging platform (MacKinnon, 2009), and how deletion based on key terms filtering is practiced on Chinese social media (Bamman, O’Connor, & Smith, 2012). With previous research mainly focusing on how Chinese Web users’ online behaviors were passively affected by the Internet censorship from the censorship mechanism perspective, how Chinese Web users actively manage to bypass the restriction on their Internet access has been insufficiently studied. Given the importance of Internet censorship, some important questions arise: who are they? Why do they bypass the GFW? Do they bypass the GFW for the sake of Internet freedom or some other concerns? And what are their motivations for bypassing the Internet censorship? On the other side, due to copyrights and licensing concerns, most of the movies, TV shows, and video clips involving possible copyrights and license issues on Chinese content-sharing social media are also blocked to international IP addresses. It seemed that the GFW not only prevents Chinese Web users from having free access to online information in China, but also stops Internet users who reside outside China from enjoying an open cyberspace. To copy with such a situation, some Chinese Web users who travel or reside outside China utilize various types of software and online applications to circumvent the network filtering to enjoy the needed resources again as they were in China. The interesting phenomenon leads to some more questions: Why do this group of Chinese Web users put extra efforts to get access to the information and content that are only provided within China? What are their motivations for bypassing the GFW outside China? This study thus aims to advance the existing knowledge on Internet censorship by investigating Chinese Web users’ active online behavior of bypassing the GFW on an individual level, as well as underlying motivations driving their online media consumption as it relates to bypassing the censorship.

4. Results 4.1. Sample characteristics 319 participants (N = 319) completed the online survey, with the mean age being 23.64 (SD = 3.36) and 62.6% being female. All of the respondents were Chinese students currently studying in the United States, who had been, on average, living in the U.S. for 28.11 months (SD = 20.09) and using the Internet for 132.49 months (SD = 32.02). 4.2. Descriptive statistics Among all the participants, 185 (58.0%) bypassed firewall in China while 176 (55.2%) did outside China. As presented in Table 1 and Table 2, the results of the descriptive analysis showed that the Chinese international students in the United States reported a medium level of frequency in bypassing the firewall in China (M = 2.64, SD = 1.91) but a higher level of frequency in bypassing the firewall outside China (M = 3.19, SD = 2.33) on average. They hold slightly negative attitude towards the GFW (M = 3.12, SD = 1.61), with adequate knowledge of censorship (M = 3.99, SD = 1.93), but limited number of software usage (M = 1.24, SD = 1.20). Table 1. Zero-order correlations between the variables included and scale-relevant information of GFW bypassing in China. α Mean SD 1 2 3 4 5 6 1. Bypass frequency in China 2.64 1.91 1.00 2. Entertainment .82 3.61 1.65 .35⁎⁎⁎ 1.00 3. Info seek .86 5.08 1.65 .33⁎⁎⁎ .38⁎⁎⁎ 1.00 4. Socializing .86 3.29 1.54 .44⁎⁎⁎ .58⁎⁎⁎ .40⁎⁎⁎ 1.00 5. Self-status .87 3.06 1.41 .34⁎⁎⁎ .63⁎⁎⁎ .46⁎⁎⁎ .77⁎⁎⁎ 1.00 6. Seek for uniqueness .88 2.86 1.54 .24⁎⁎ .52⁎⁎⁎ .45⁎⁎⁎ .61⁎⁎⁎ .70⁎⁎⁎ 1.00 ∗ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001. Table options Table 2. Zero-order correlations between the variables included and scale-relevant information of GFW bypassing outside China. α Mean SD 1 2 3 4 5 6 1. Bypass frequency outside China 3.19 2.33 1.00 2. Entertainment .77 5.42 1.35 .35⁎⁎⁎ 1.00 3. Info seek .88 3.85 1.84 .25⁎⁎ .32⁎⁎⁎ 1.00 4. Socializing .95 3.20 1.75 .17⁎ .37⁎⁎⁎ .77⁎⁎⁎ 1.00 5. Self-status .92 2.86 1.52 .03 .31⁎⁎⁎ .74⁎⁎⁎ .85⁎⁎⁎ 1.00 6. Seek for uniqueness .96 2.61 1.60 .11 .29⁎⁎ .60⁎⁎⁎ .74⁎⁎⁎ .85⁎⁎⁎ 1.00 ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001. Table options When scaling the firewall in China, these participants (N = 185) were highly motivated in terms of information seeking (M = 5.08, SD = 1.65) while gained medium gratifications in entertainment (M = 3.61, SD = 1.65), socializing (M = 3.29, SD = 1.54), self-status (M = 3.06, SD = 1.41) and need for uniqueness (M = 2.86, SD = 1.54). Different from the motives for bypassing the firewall in China, the respondents (N = 176) conducted outside China mainly for entertainment (M = 5.42, SD = 1.35) and then for information seeking (M = 3.85, SD = 1.84). The other motivations—socializing (M = 3.20, SD = 1.75), self-status (M = 2.86, SD = 1.52) and need for uniqueness (M = 2.61, SD = 1.60)—were more or less at the same level. 4.3. Statistical analysis To answer the first two research questions, four regression analyses were conducted with demographic variables controlled. RQ1: What are Chinese Web users’ motivations for bypassing the GFW in and outside Mainland China respectively? As shown in Table 3, the logistic regression analysis results showed that among 319 respondents, 185 reported they bypassed the GFW in China while 134 did not. It was found that age was positively associated with Chinese Internet users’ bypassing behavior (B = .17, SE = .05, odds ratio = 1.18, p < .01), which means that, for each one-year increase in the age, the Chinese Web users were about 1.18 times more likely to bypass the Internet censorship, with other variables in the model being controlled. Also, there was a negative association between attitudes towards Internet censorship and Chinese Internet users’ bypassing behavior (B = −.20, SE = .09, odds ratio = 0.82, p < .05), which indicates that, for each one-unit increase in the favorable attitudes towards Internet censorship, there was approximately four-fifths (0.82) of a chance that the Chinese Web users would bypass the GFW, after controlling other variables in the model. Moreover, the use of bypassing software was positively associated with Chinese Internet users’ bypassing behavior (B = 3.56, SE = .40, odds ratio = 35.03, p < .001), which shows that, for each one-unit increase in the use of scaling software and applications, the Chinese Web users were about 35.03 times more likely to bypass the Internet censorship, when other variables were controlled in the model. In other words, compared to Chinese Internet users who did not bypass the GFW in China, those who bypassed were older, held more negative attitudes towards the Internet censorship, and enjoyed a higher level use of scaling software/applications. Surprisingly, knowledge of Internet censorship was not a significant factor predicting whether Chinese Internet users would bypass the GFW in China or not. Table 3. Summary of logistic regression analyses (N = 319). DV1: Bypassing behavior in China DV2: Bypassing behavior outside China B SE B Odds ratio B SE B Odds ratio Model 1 Age .08 .04 1.08⁎ −.02 .04 .98 Gender −.04 .24 .96 .04 .24 1.04 Time in US −.01 .01 .99 Model 2 Age .17 .05 1.18⁎⁎ −.02 .04 .98 Gender −.11 .31 .90 .02 .26 1.03 Time in US −.00 .01 1.00 Attitude towards Internet censorship −.20 .09 .82⁎ .05 .08 1.05 Knowledge about censorship −.10 .08 .90 −.05 .07 .95 Bypassing software use 3.56 .40 35.03⁎⁎⁎ 1.91 .28 6.78⁎⁎⁎ Note. DV: Dependent variable. ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001. Table options With regard to the frequency of bypassing Internet censorship behavior among the 185 respondents who bypassed the GFW in China before, the hierarchical analysis showed that, as shown in Table 4, a linear combination of age and gender jointly explained 8% of the variance in the participants’ frequency of bypassing the firewall in China [(F change (3, 173) = 4.88, p < .01, ΔR2 = .08)]. It was found that male Internet users conducted significantly more firewall-scaling behaviors in China than female counterparts (t = 2.36, p < .05, β = .15), and age was not a significant predictor of bypassing firewall behaviors in China. After controlling the demographic variables, it is found that the five motivations jointly explained 25% of the variance of Chinese Internet users’ behaviors of bypassing the firewall at home [(F change (5, 168) = 12.18, p < .001, ΔR2 = .25)]. Particularly speaking, information seeking (t = 2.57, p < .05, β = .20) and socializing (t = 3.32, p < .01, β = .37) were found to be significant predictors of Chinese Web users’ firewall-scaling behaviors in China, with socializing explaining more variance in the dependent variable than information seeking. In contrast, entertainment, self-status and need for uniqueness turned out to be non-significant in predicting the Chinese Web users’ firewall-scaling frequency in China. Table 4. Summary of hierarchical regression analyses. DV1: Bypassing frequency in China DV2: Bypassing frequency in the US ΔR2 B SE B β ΔR2 B SE B β Model 1 .08⁎⁎ .02 Age −.06 .05 −.09 −.02 .05 −.03 Male .43 .29 .11 −.41 .32 −.10 Time in US −.00 .01 −.04 Model 2 .25⁎⁎⁎ .24⁎⁎⁎ Age −.03 .05 −.04 .02 .05 .04 Male .60 .26 .15⁎ .16 .30 .04 Time in US −.01 .01 −.10 Entertainment .15 .10 .13 .48 .11 .32⁎⁎⁎ Info seek .23 .09 .20⁎ .40 .13 .37⁎⁎ Socializing .45 .14 .37⁎⁎ .29 .17 .25 Self-status −.07 .16 −.05 −1.07 .23 −.80⁎⁎⁎ Uniqueness −.06 .11 −.05 .38 .17 .30⁎ Note. NIN = 185. NOUT = 176. DV: Dependent variable. ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001. Table options As shown in Table 3, the logistic regression analysis results showed that among 319 respondents, 176 reported they bypassed the GFW outside China before while 143 did not. It was found that the use of bypassing software and applications was positively associated with Chinese Internet users’ bypassing behavior outside China (B = 1.91, SE = .28, odds ratio = 6.78, p < .001), which means that, for a one-unit increase in the use of scaling software and applications, the Chinese Web users were 6.78 times more likely to bypass the Internet censorship when they were outside China, with other variables being controlled. In other words, compared to Chinese Internet users who did not bypass the GFW outside China, the group who did bypass the Internet censorship outside China enjoyed a higher level of use of scaling software/applications. Age, attitudes towards Internet censorship, and knowledge about Internet censorship all turned out to be non-significant factors influencing whether Chinese Internet users would bypass the Internet censorship outside China or not. With regard to the frequency of bypassing Internet censorship behavior among the 176 respondents who bypassed the GFW outside China, the hierarchical analysis showed that a linear combination of the demographic variables—age, gender, and time studied abroad—controlled in the regression analysis jointly explained only 2% of the participants’ behaviors of bypassing the GFW outside China since none of the control variable is statistically significant [(F change (3, 166) = .82, p > .05, ΔR2 = .02)]. However, the motivations explained 24% of the total variance [(F change (5, 161) = 10.35, p < .001, ΔR2 = .24)], with entertainment (t = 4.31, p < .001, β = .32), information seeking (t = 3.22, p < .01, β = .37), self-status (t = −4.75, p < .001, β = −.80) and seek for uniqueness (t = 2.32, p < .05, β = .30) being significant predictors of the firewall bypassing behaviors outside China. Only socializing turned out to be non-significant in predicting the dependent variable. RQ2: Are there difference in Chinese Web users’ motivations for bypassing the GFW in and outside China? Five paired sample t-tests (2-tailed) were implemented as shown in Table 5 to test the third research question. In the paired sample t-test, only the cases (N = 122) of bypassing the GFW both in and outside Mainland China were analyzed. It was found that the Chinese Web users enjoyed a higher level of motivations including information seeking (MIN = 5.36, MOUT = 3.43, t(121) = 11.21, p < .001), socializing (MIN = 3.50, MOUT = 2.80, t(121) = 4.90, p < .001), self-status (MIN = 3.24, MOUT = 2.54, t(121) = 6.16, p < .001), and uniqueness (MIN = 3.18, MOUT = 2.28, t(121) = 5.88, p < .001) when bypassing the firewall in China than when bypassing outside China. The Chinese Web users when bypassing the firewall in China only enjoyed significantly a lower level of entertainment seeking (MIN = 3.83, MOUT = 5.27, t(121) = −9.61, p < .001) than when bypassing outside China. 1 Table 5. Summary of paired t-test results. U&G Bypass firewall t-Value df p-Value In China In US Entertainment 3.83 5.27 −9.61 121 .000 Info seek 5.36 3.43 11.21 121 .000 Socializing 3.50 2.80 4.90 121 .000 Self-status 3.24 2.54 6.16 121 .000 Uniqueness 3.18 2.28 5.88 121 .000 Note. N = 122.