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The advancement of Internet technology has provided a great impetus to alleviate poverty and promote economic progress. However, studies on the negative impact that the development of the Internet may have on individual perceptions are still rare. This paper uses data from the China Family Panel Studies (CFPS) in 2018 to construct multiple econometric models to empirically study the impact of Internet use (ITU) on the perception of the poor–rich gap (PPRG) and its mechanism in China. The instrumental variable (IV) model and Heckman model are used to solve potential endogenous problems. The research found that ITU has aggravated the PPRG of residents, and the test results are still robust after considering various endogenous sources. Additional analysis shows that the degree of dependence on the Internet is one of the transmission mechanisms of ITU on the impact of the PPRG, and its mediating effect accounts for 32.12% of the total effect. Another test result of the impact mechanism shows that the Internet media expands the reference group of residents through virtual areas and aggravates the PPRG of residents. Some test results from the perspective of heterogeneity show that: the effect of urban residents’ ITU on PPRG is higher than that of rural residents. ITU of residents in economically developed areas has a significantly higher effect on the PPRG than residents in economically underdeveloped areas. The impact on ITU by residents of different age groups on aggravating the PPRG show an obvious increasing linear law. Our research provides an ITU interpretation path for the impact of PPRG from sociological theory and provides a new entry point for the impact of the Internet and subjective well-being.

In the digital age, it is critical to understand the nexus between digital technology (DT) and land rent-out behavior (LRB). It has implications for reducing the rate of land abandonment to achieve sustainable agricultural development. A large dataset (n = 5233) dating from 2016 and coming from the China Family Panel Studies (CFPS) is used to explore the impact of DT on LRB by applying several econometric models, also including the “Recursive Bivariate Probit (RBP) model” and “Chain Multiple Mediation effect (CMM) model”. We provide empirical evidence that the DT’s information sharing effect positively impacted LRB, while an opposite effect is observed by the “digital divide (DT_GAP)” i.e., information exclusion that negatively impacted LRB. We further test the effect of two other variables, namely “digital information dependence” and “non-farm jobs” supposed as mediating factors of DT and DT_GAP in influencing LRB, respectively in a positive and negative way. In particular, the variable “nonfarm jobs” plays a mediating role conditional on the variable “digital information dependence” as a mediating variable at the first level. In addition, statistical tests reveal that the impact of DT and the DT_GAP on LRB is not significant in terms of regional preferences but is significant in terms of age of householder and household income level.

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