In recent years, a growing number of scholarly studies have identified a decline in public support for democracy. These studies contend that as support for democratic principles erodes, support for authoritarian policies and political leaders tends to grow, thereby facilitating attempts by people in power to dismantle democratic institutions. A case that most clearly exemplifies this trend is Israel's judicial reform. The reform, advanced by Prime Minister Benjamin Netanyahu and his allies as of January 2025, aimed to curtail the authority of the judiciary, including the Supreme Court, which has frequently acted as a check on government policies. Consequently, the reform attracted significant criticism both domestically and internationally for undermining the democratic foundations of the Israeli political system. Israeli society has experienced profound polarization, largely along lines of support for or opposition to Prime Minister Netanyahu. This polarization has deepened societal divisions and intensified debates concerning judicial reform and the state of democracy in Israel. Within this context, the present study employs a conjoint experiment to measure Israeli citizens' orientations toward democracy. The findings indicate that Netanyahu's supporters demonstrate comparatively lower support for judicial independence, a fundamental democratic principle. These results contribute to an understanding of public preferences regarding judicial reform in Israel and suggest that strong allegiance to a dominant political leader may play a role in diminishing support for democratic governance.

Since the early 2010s, quantitative text analysis has gained renewed prominence across the social sciences; yet the method remains both familiar and novel within the field of China studies. This article reviews this hybrid status by (1) tracing the Cold War origins of this method, the intellectual and geopolitical conditions that nurtured its first wave, and the factors behind its subsequent eclipse; (2) analyzing the method’s recent resurgence and the principal ways it has been redeployed in contemporary scholarship; and (3) discussing the method’s future potential along with unresolved theoretical, empirical, and data-access challenges. First, we show that quantitative text analysis was actively adopted under stringent data constraints during the Cold War, but that its popularity faded after the 1980s as the data environment changed. Second, drawing on publication data, we document a marked resurgence since the 2010s. We highlight recent studies that have deepened understanding of authoritarian governance in contemporary China, especially in the areas of censorship and information manipulation. Finally, we assess future prospects. We note opportunities for deeper integration with machine-learning techniques and an expanding range of research questions. At the same time, we identify key obstacles: tightening data regulations, the need to link quantitative findings with qualitative insights, and a persistent tension between this approach and traditional area-studies scholarship.