Advancing theory in media exposure and effects requires contending with an increasing level of complexity and contingency. Building on established theoretical concerns and the research possibilities enabled by large social datasets, we propose a framework for mapping information exposure of digitally situated individuals. We argue that from the perspective of an individual's personal communication network, comparable processes of "curation" are undertaken by a variety of actors-not only conventional newsmakers but also individual media users, social contacts, advertisers, and computer algorithms. Detecting the competition, intersection, and overlap of these flows is crucial to understanding media exposure and effects today. Our approach reframes research questions in debates such as polarization, selective and incidental exposure, participation, and conceptual orientations for computational approaches.

Using large Twitter datasets collected during the 2012 U.S. presidential election, we examined how partisanship shapes patterns of sharing and commenting on candidate fact-check rulings. Our results indicate that partisans selectively share fact-checking messages that cheerlead their own candidate and denigrate the opposing party's candidate, resulting in an ideologically narrow flow of fact checks to their followers. We also find evidence of hostile media perception in users' public accusations of bias on the part of fact-checking organizations. Additionally, Republicans showed stronger outgroup negativity and hostility toward fact checkers than Democrats. These findings help us understand "selective sharing" as a complementary process to selective exposure, as well as identifying asymmetries between partisans in their sharing practices.

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While survey research has been at the heart of social science for decades and social scientific research with digital trace data has been growing rapidly in the last few years, until now, there are relatively few studies that combine these two data types. This may be surprising given the potential of linking surveys and digital trace data, but at the same time, it is important to note that the collection and analysis of such linked data are challenging in several regards. The three key issues are: (1) data linking including informed consent for individual-level studies, (2) methodological and ethical issues impeding the scientific (re)analysis of linked survey and digital trace data sets, and (3) developing conceptual and theoretical frameworks tailored toward the multidimensionality of such data. This special issue addresses these challenges by presenting cutting-edge methodological work on how to best collect and analyze linked data as well as studies that have successfully combined survey data and digital trace data to find innovative answers to relevant social scientific questions.

This study extends past research on the relationship between news use and participation by examining how youth combine news exposure across an array of media devices, sources, and services. Results from a national survey of U.S. youth ages 12 to 17 reveal four distinct news repertoires. We find that half of youth respondents are news avoiders who exhibit the lowest levels of participation. The other half of youth respondents are characterized by one of three patterns of news use, each distinct in how they seek out (or avoid) using new media platforms and sources for news, and in their levels of participation.

We conducted two experiments to explore how moderation, response rate, and message interactivity affected people's intent to participate in a web-based online community. In our first experiment, 62 participants observed either a moderated or an unmoderated online community and answered questions about their intent to participate in the community. The participants who viewed the moderated community reported significantly higher intent to participate than participants who viewed the unmoderated community. In our second experiment, 59 participants observed a different online community in which we manipulated both the rate (in time) of posted comments and the interactivity of each comment. We derived our manipulation of interactivity from Rafaeli's (1988) definition of interactivity as message contingency. Participants reported significantly greater intent to participate in an online community featuring interactive messages, but only when response rate was slow. These results indicate that both structural features of interfaces and content features of interactions affect people's intent to participate in online communities.

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