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Abstract
Researchers have long known that the terms used in questions posed to respondents shape the answers they give. Processes underlying these differences have generally been attributed to respondents' interpretations of the questions (i.e., what do the terms lead them to focus on) and examined as a framing effect. Yet evidence that people often answer questions they do not fully understand means it is also possible that some of this difference may stem from respondents' ability to parse what the questions are asking about (i.e., do they comprehend the question). In three online survey experiments, we manipulate wordings for policy attitude questions about the DREAM Act, Trump's trade disputes, and the Affordable Care Act to assess how both question comprehension and interpretation depend on the wordings selected. We find that reported attitudes vary as a joint function of both processes. By comparing response patterns and simulating individuals' "informed responses" across wordings, we can disentangle differences due to incomplete understandings (and misunderstandings) from those attributable to partisan interpretations. Evidence that individuals with greater topical knowledge better recognize the similarity of different wordings confirms that some of the wording effect is associated not just with framing, but also with comprehension.

It is a platitude of communication and public opinion research that responses to survey questions to a great extent depend on the words used in those questions. This idea, however, was not always well supported in empirical studies. We argue that the inconsistent findings from prior research might stem from the fact that different groups of individuals have varying sensitivity to the influences of question wording variations. With an online survey experiment testing participants' attitudes toward the foreign trade disputes under the Trump administration, we found that the impact of changes in question wording on inducing different responses was moderated by participants' actual topical knowledge. Referring to the issue as "Trump's trade war" significantly reduced its favorability compared to describing it as "the trade war" without mentioning Trump, but only among participants who were unknowledgeable about tariffs and international trade issues. The normative implications of attaching political and partisan cues to polling questions were discussed.

Previous studies have identified various individual factors explaining news avoidance, but the understanding of how these factors function within the broader political information environment is limited. This study, leveraging a large-scale cross-national survey, reveals that the relationships between individual news interests, news trust, and news avoidance differ across countries with varying levels of press freedom. In nations where the press is strong and free, personal preferences minimally influence individuals' active avoidance of hard news. News avoidance is not solely a product of individual-level attributes. Rather, the impact of these individual factors is significantly shaped by the overarching political information environment.

While research on flagging misinformation and disinformation has received much attention, we know very little about how the flagging of propaganda sources could affect news sharing on social media. Using a quasi-experimental design, we test the effect of source flagging on people's actual sharing behaviors. By analyzing tweets ( N = 49,126) posted by 30 China's media accounts before and after Twitter's practice of labeling state-affiliated media, we reveal the corrective role that flagging plays in preventing people's sharing of information from propaganda sources. The findings suggest that the corrective effect occurs immediately after these accounts are labeled as state-affiliated media and it leads to a long-term reduction in news sharing, particularly for political content. The results contribute to the understanding of how flagging efforts affect user engagement in real-world conversations and highlight that the effect of corrective measures takes place in a dynamic process.

How do people form their attitudes toward complex policy issues? Although there has long been an assumption that people consider the various components of those issues and come to an overall assessment, a growing body of recent work has instead suggested that people may reach summary judgments as a function of heuristic cues and goal-oriented rationalizations. This study examines how well a component-based model fits Americans' evaluations of the Patient Protection and Affordable Care Act of 2010, an important and highly contentious piece of legislation that contained several constituent parts. Despite strong partisan disagreement about the law, we find that Democrats and Republicans both appear to evaluate the law as a function of their beliefs and what the law would do as well as their confidence in those beliefs. This finding implies that correcting misperceptions and increasing awareness of the components of legislation have the potential to change attitudes.