Since 1978, the government in China has implemented a reform and opening-up policy that has led to rapid economic development and significant improvements in people’s living standards and material conditions (Lu et al., 2019). However, during the process of social and economic transformation, social inequity issues have emerged, such as uneven social structure, an excessive wealth gap, and imbalanced urban–rural development (Camarero & Oliva, 2019). Such inequities disrupt perceived social equity, which refers to individuals’ relative cognition formed by comparing themselves with others or the social average, as well as their subjective judgment on the fairness of social resource distribution based on personal perceptions (Wooldridge & Gooden, 2009). In China, the government has introduced a series of policies to promote the construction of an equitable society (H. Zhang, 2023). However, the sense of social equity among Chinese residents remains uneven, with persistent internal disparities that are largely associated with factors such as unequal access to education and widening income gaps (Liu, 2024).

 

Chinese residents’ perception of social equity is influenced by a variety of factors, among which internet use is particularly important (Xu et al., 2024). According to The 54th Statistical Report on Internet Development in China (China Internet Network Information Center, 2024) as of June 2024, internet users in China numbered nearly 1.1 billion and the internet penetration rate had reached 78.0%. This means that the internet will inevitably bring changes to people’s social lifestyle and concepts, while, at the same time, residents’ sense of social equity is influenced by the internet (Li, 2024). On the internet, residents can freely and equally express their opinions and carry out activities such as safeguarding their rights; this fosters the concept of freedom and equality, which can enhance residents’ sense of social equity (Li, 2024). However, the internet also has the characteristic of anonymity and there is a lack of effective supervision. As a result, people may be guided by wrong signals, leading to a severe deviation of their sense of social equity from reality (Li, 2024). Therefore, the relationship between internet use and the sense of social equity has attracted widespread attention from researchers.

 

Research findings regarding the relationship between internet use and the sense of social equity have been inconsistent. Zhou et al. (2025) found that internet use can enhance the sense of social equity among older adults. J. Z. Zhang and Huang (2018) found that the internet can help to address imbalance in the distribution of educational resources, enabling high-quality educational resources to operate efficiently at a low cost and reducing educational inequity caused by factors like family background and regional location. Mao and Zeng (2017) found that internet use alleviates work inequity resulting from gender-based screening discrimination in recruitment, along with the disadvantages women have faced relative to men in terms of salary, promotion opportunities, career development, job assignment, and labor protection. Internet use effectively mitigates this gender-based discrimination by reducing information asymmetry, expanding employment channels, and weakening traditional gender stereotypes. However, in a study focusing on older adults in China, Xu et al. (2024) showed that using the internet more than three times a week reduced participants’ sense of social equity. Parkinson and Lauzon (2008) conducted a study at telecenters in Cali, Colombia, to explore the impact of internet access and use on social equity in the locality, and found that residents’ perception of social equity did not improve through use of telecenter services. Hargittai et al. (2019) found that use of the internet reproduced and amplified existing social inequity among older adults. Similarly, in a study of young adults, Bek and Aygün (2016) argued that internet use is not a tool to eliminate social imbalance; instead, it reproduces and reinforces existing social imbalance through class/ethnic disparities in access quality, digital skills, and usage scenarios. Therefore, further research is needed to examine the relationship between internet use and perception of social equity.

 

In the theory of structural determinism, Jasso (1980) posited that most of the sense of unfairness people perceive stems from comparisons with reference targets in social interactions. According to this theory, perception of social equity depends on the individual’s socioeconomic status—generally, the higher the socioeconomic status, the stronger the sense of equity, and vice versa (Manstead, 2018). According to Manstead (2018), individuals’ judgment of their own social class mainly depends on changes in their social status, that is, whether they have achieved social mobility. If upward social mobility is blocked, this indicates the existence of irrational economic and resource allocation in society, which, in turn, induces individuals to develop a sense of unfairness; conversely, if channels for upward mobility are relatively unobstructed, individuals will exhibit a more positive social mindset (Manstead, 2018). Luo and Liu (2022) found that internet use can enhance residents’ class identity. On the basis of this finding, I explored the potential mediating role of sense of class mobility between internet use and sense of social equity.

 

The existing literature has two limitations I sought to address: First, the correlation between internet use and perception of social equity remains to be further verified; second, the mediating effect of sense of class mobility in the relationship between internet use and perception of social equity is yet to be confirmed. Therefore, I conducted this study based on responses drawn from the database of the 2021 Chinese General Social Survey (CGSS). My aim was to provide a reference for addressing the differentiation in Chinese residents’ perception of social equity in the internet era. My findings may provide a basis for formulating policies that balance internet development and construction of social equity in China.

The CGSS is the earliest continuous academic survey project in China in which data are systematically collected nationwide on various aspects of social phenomena and the behavioral habits of people (Han & Zhao, 2021). In this project more than 10,000 households in all provinces, autonomous regions, and municipalities selected via multistage stratified random sampling participate in a cross-sectional survey conducted directly under the authority of the Central Government of Mainland China on an annual or biennial basis (Han & Zhao, 2021). During the research-design and data-processing phases, I used the CGSS 2021 database, which comprises the latest publicly available national comprehensive social survey data. Since the CGSS 2021 is an open-source database, no further ethical review was required for this study. However, the CGSS 2021 received approval from the Scientific Research Ethics Committee of Renmin University of China, and all participants gave informed consent.

 

In the process of screening data obtained from 8,148 people, I excluded participants who had refused to answer or answered “Don’t know” for the items related to internet use and sense of social equity, resulting in 8,083 participants. The basic demographic information for the participants is shown in Table 1.

Investigators who administer the CGSS 2021 undergo 3 to 5 days of specialized training, covering questionnaire interpretation, interview skills, and equipment operation. Standardized operation of the survey is ensured through simulated interviews. Investigators communicate with village or neighborhood committees with letters of introduction, verify sampling maps and household lists, and confirm the survey scope. To ensure consistent understanding of items, investigators read the questions, respondents answer and investigators record their replies. In particular, core variables are recorded in strict accordance with scale options to avoid subjective guidance. The variables investigated in this study are set out below.

 

To assess participants’ sense of social equity (dependent variable), I used their response to the following question in the CGSS: “Generally speaking, do you think today’s society is or is not fair?” Responses are made on a 5-point Likert scale ranging from 1 = completely unfair to 5 = completely fair. The higher the score, the stronger the sense of social equity. Although residents’ self-rated sense of social equity is highly subjective, Xiao and Chen (2023) explained that if errors are random, selecting ordered data of subjective indicators as the explained variable will not lead to coefficient estimation bias. In other words, this kind of subjectively evaluated social equity is reasonable.

To assess frequency of internet use (independent variable), I used the CGSS 2021 question “Over the past year, how often have you used the internet (including mobile internet)?” Responses are made on a 5-point Likert scale ranging from 1 = never to 5 = very frequently. Surveys in which participants subjectively assess internet use have shown good reliability and validity and have been widely applied (Jiao, 2023; Kang, 2025).

To assess class mobility (mediating variable), I used two questions from the CGSS 2021: “Overall, in the current society, which social class do you think you are in?” and “When you were 14 years old, which social stratum do you think your family was in at that time?” For both questions a 10-point responses scale is used, where 1 = the lowest stratum and 10 = the highest stratum. I evaluated respondents’ sense of class mobility by subtracting the perceived class status at the age of 14 years from their current perceived class status. With reference to Li (2024), if the difference is negative or zero, a value of 0 is assigned; if the difference is positive, a value of 1 is assigned. Since socioeconomic status is measured by perceived social class, changes in socioeconomic status can be used to reflect the sense of class mobility.

I drew on previous studies (Li, 2024; Mei et al., 2020), to select five control variables: age, gender, place of residence, level of education, and subjective health perception. I calculated respondents’ age by subtracting their year of birth from 2021. Gender was coded as 1 = man and 0 = woman. Area of residence was coded as 1 = urban and 0 = rural. Regarding level of education, I recoded and assigned values according to educational background: no education, private tutoring/literacy classes, and primary school were integrated into the category of 1 = primary school and below; 2 = junior school; vocational school, general school, technical secondary school, and technical school were grouped into 3 = senior school; junior college (adult higher education) and junior college (regular higher education) were combined into 4 = junior college; and undergraduate (adult higher education), undergraduate (regular higher education), and postgraduate and above were merged into 5 = undergraduate and above. To assess subjective health perception, I used the CGSS 2021 question “How would you describe your current physical health status?” Responses are rated on a 5-point Likert scale ranging from 1 = very unhealthy to 5 = very healthy.

I used SPSS 21.0 and Amos 16.0 software for data processing and statistical analysis. For descriptive statistics, mean values and standard deviations were employed for continuous variables, and frequencies and percentages were used for categorical variables. I used a Spearman correlation analysis to examine the relationships among internet usage, sense of class mobility, and sense of social equity. Next, I tested the correlation between sense of social equity as the dependent variable and internet use as the independent variable both before and after controlling for relevant variables. Finally, I performed a path analysis to examine the potential mediating effect of sense of social mobility in the correlation between internet use and sense of social equity. Missing values in this study were imputed using the linear interpolation method. A significance level of α = .05 was set as the critical value for this study.

Descriptive statistics for participants’ internet usage, sense of social equity, and sense of class mobility are detailed in Table 2.  

Results in Table 3 show that internet usage was significantly and negatively correlated with sense of social equity, and significantly and positively correlated with sense of class mobility. Sense of social equity was significantly and negatively correlated with sense of class mobility.

Table 4 shows that without incorporating relevant control variables, there was a significant negative correlation between internet usage and sense of social equity. After incorporating relevant control variables, the correlation remained significant and negative. In addition, age had a significant positive correlation with sense of social equity, so that older people had a stronger sense of social equity. Compared with women, men had a stronger sense of social equity. Compared with rural residents, urban residents had a weaker sense of social equity. In addition, compared with people whose education level was primary school or below, those with an education level of junior college or above had a stronger sense of social equity. Subjective perception of good health had a significant positive correlation with sense of social equity.

I examined the mediating role of sense of class mobility in the correlation between internet use and sense of social equity. The results indicated the model had a good fit to the data, goodness-of-fit index = .989, normed fit index = .947, comparative fit index = .967, incremental fit index = .988, root-mean-square error of approximation = .071. The path analysis results (see Table 5) revealed that internet use had a significant positive predictive effect on perceived social mobility, perceived social mobility had a significant negative predictive effect on sense of social equity, and internet use had a significant negative predictive effect on sense of social equity. Therefore, sense of class mobility played a partial mediating role in the relationship between internet use and sense of social equity.

I found a significant negative correlation between frequency of internet usage and sense of social equity among Chinese residents. This is consistent with the findings of some previous studies (Xu et al., 2024; J. Z. Zhang & Huang, 2018) but contradicts the conclusion by Zhou et al. (2025) that internet use enhances sense of equity among older adults by facilitating their political participation.

 

In terms of information-dissemination characteristics, anonymity and regulatory loopholes make the internet not only a platform for equality of expression and rights protection (Li, 2024) but also a source of information that is biased. During China’s socioeconomic transition period, issues of inequity, such as social structural imbalance and a widening wealth gap, have been amplified online through public opinion (Guo, 2023). People who are frequently exposed to such information are more likely to form social perceptions that deviate from reality, thereby reducing their sense of equity (Jussim, 1991). In contrast, Zhou et al. (2025) found that older adults may primarily use the internet to access government information and participate in political activities, and the particularity of scenarios of their information exposure led to a different conclusion than that I obtained in this study.

 

In terms of group differences in internet usage, the intergroup analysis I performed showed that the frequency of internet usage increased as the level of education increased, and the rate of internet usage was significantly higher for urban residents than for rural residents. However, the sense of social equity of urban residents was significantly weaker than that of rural residents. In combination with structural determinism (Jasso, 1980), social comparison is the core source of individuals’ perception of equity, and the internet has greatly expanded the scope of such comparisons. Groups with high-frequency usage of the internet, such as those with a high educational level and those who live in an urban location, are more likely than are those who live in rural areas to be exposed to information about resource allocation differences across regions and social classes. This access to extensive comparison makes them more sensitive to social inequity, ultimately weakening their sense of social equity (Xu et al., 2024).

The results of the path analysis indicated that an individual’s sense of class mobility played a significant mediating role in the relationship between their internet usage and sense of social equity. On the one hand, internet usage positively predicted sense of class mobility, which aligns with the conclusion of Luo and Liu (2022) that use of the internet enhances individuals’ class identity and further expands the dimensions of its impact. By integrating information on educational resources and career opportunities, the internet provides people with channels to perceive the possibility of class mobility (Cartier et al., 2005). In the past, people living in rural areas and those with a low level of education had great difficulty accessing skills training and entrepreneurship support. The internet has made these services much more convenient and accessible, so that even people living in rural locations and those with a low level of education can learn about paths to achieve upward mobility, such as skills training and entrepreneurship support, thereby strengthening their perception of class mobility. On the other hand, I found that sense of class mobility had a significant negative predictive effect on sense of social equity. This paradoxical result can be explained with reference to structural determinism. When people perceive opportunities for class mobility, they will pay more attention to the obstacles that impede the mobility process, such as institutional constraints like unequal distribution of educational resources and regional development gaps (Robinson, 2011). This cognitive gap between availability of opportunities and difficulty of realization makes them more likely to attribute their difficulty in achieving upward class mobility to unfair social distribution, thereby having a negative impact on their evaluation of social equity (Robinson, 2011).

This study makes two main theoretical contributions: First, it addresses contradictions in existing research and emphasizes the role of the information environment and user group heterogeneity in the relationship between internet usage and sense of social equity. Second, structural determinism highlights that social comparison is the core source of the sense of equity, and the results of this study showed that how frequently the internet was used indirectly predicted sense of social equity by enhancing sense of class mobility, which constitutes a specific verification and extension of this theory in the digital age.

 

The conclusions of this study provide targeted implications for the construction of social equity in China in the internet era. First, to avoid misleading the public into forming a perception of fairness that deviates from reality, dissemination and amplification via the internet of information related to social equity that is not objective and in which social injustice is exaggerated should be reduced, and supervision should be strengthened. Second, the obstacles to class mobility highlighted by the data on frequency of internet usage should be addressed, such as the uneven distribution of educational resources and regional development gaps. The design of relevant systems should be further improved, such as provision of balanced education and coordinated regional development, and the actual threshold for mobility should be lowered. Finally, for groups with high-frequency internet usage, the transparency of interpretation of policies related to people’s livelihood should be strengthened, and positive guidance should be provided on issues related to social equity to reduce cognitive biases caused by extensive social comparison.

This study has some limitations. First, cross-sectional data cannot reveal the causal temporal sequence between variables. Future studies could adopt a longitudinal tracking design to clarify the causal chain among variables. Second, the method of measurement of core variables I used was relatively simplistic: Sense of social equity was assessed with a single item, and the internet usage measure did not distinguish between specific content types, which may affect the refinement of research results. Therefore, future research could optimize measurement tools and subdivide internet usage scenarios and dimensions of social equity.

This study used data from the CGSS 2021 and found a significant negative correlation between frequency of internet usage and sense of social equity among Chinese residents. Additionally, sense of class mobility played a significant mediating role in this relationship. This research provides empirical support for understanding the logic of formation of Chinese people’s perception of social equity in the digital era.

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