We describe the first version of the Media Frames Corpus: several thousand news articles on three policy issues, annotated in terms of media framing. We motivate framing as a phenomenon of study for computational linguistics and describe our annotation process.

What drives candidates to "go negative" and against which opponents? Using a unique dataset consisting of all inter-candidate tweets by the 17 Republican presidential candidates in the 2016 primaries, we assess predictors of negative aff ect online. Twitter is a free platform, and candidates therefore face no resource limitations when using it; this makes Twitter a wellspring of information about campaign messaging, given a level playing-fi eld. Moreover, Twitter's 140-character limit acts as a liberating constraint, leading candidates to issue sound bites ready for potential distribution not only online, but also through conventional media, as tweets become news. We fi nd tweet negativity and overall rate of tweeting increases as the campaign season progresses. Unsurprisingly, the front-runner and eventual nominee, Donald Trump, sends and receives the most negative tweets and is more likely than his opponents to strike out against even those opponents who are polling poorly. However, candidates overwhelmingly "punch upwards" against those ahead of them in the polls, and this pattern goes beyond attacks against those near the top. Sixty of 136 dyads are characterized by lopsided negativity in one direction and only one of these 60 involves a clearly higher status candidate on the off ensive.

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In this paper we examine information exchange networks in legislative politics and challenge the idea that legislators seek objective information prior to voting on bills. We make the intuitive claim that legislators establish contacts with each other that stand to maximize the value of the information they trade. Additionally, we make the counterintuitive claim that legislators seek information from sources that are predictably biased for or against their preferred outcomes. We test the propositions derived from this argument in the context of the European Parliament, using tools from social network analysis and modeling the network dependence using a multilevel approach. This research makes two primary contributions to the field of legislative politics. First, we demonstrate both theoretically and empirically how legislators use social contacts to their strategic advantage in their pursuit of legislative information. Second, our analytical approach demonstrates how to appropriately account for interdependence of observations in network data. 3The process of lawmaking is an inherently social exercise and scholars have recently begun to use social network analysis to help explain some legislative behaviors (see for example, Fowler 2006). However, it is not yet clear how social networks among lawmakers contribute to legislative outcomes, policy formation, or pivotal activities such as voting. This paper seeks to begin to fill this gap by examining social networks in legislative politics as circuits of information exchange. Specifically, we are interested in examining if legislative offices establish connections amongst each other that maximize the value of the information they trade.We maintain that in an effort to make well-informed policy choices, legislators have incentives to pursue information from sources that are predictably biased; the social connections they establish to collect information about the legislation they enact reflect these incentives. Information provided by sources that are predictably biased allows legislators to compare the information they expect to receive, given the known bias of the source, to the information they actually receive. This is of great value to legislators as they seek to confirm the appropriateness of the policy positions they are predisposed to take toward a given policy proposal. If the information legislators expect matches the actual information they receive, their predispositions are confirmed; in contrast, if the source provides information that deviates from their expectations it is likely to trigger a re-evaluation of their initial policy positions.Prior authors have noted the value of "biased" information for legislators (see Kingdon 1981, 232;Calvert 1985); however, we offer that information has greater value to decision-makers if it is predictably biased. Such information is either in support of or in opposition to the position a legislator is predisposed to take, which means that legislators ought to seek information from both political allies and ...

For over a half century, various fields in the behavioral and social sciences have debated the appropriateness of null hypothesis significance testing (NHST) in the presentation and assessment of research results. A long list of criticisms has fueled the so-called significance testing controversy. The conventional NHST framework encourages researchers to devote excessive attention to statistical significance while underemphasizing practical (e.g., scientific, substantive, social, political) significance. I introduce a simple, intuitive approach that grounds testing in subject-area expertise, balancing the dual concerns of detectability and importance. The proposed practical and statistical significance test allows the social scientist to test for real-world significance, taking into account both sampling error and an assessment of what parameter values should be deemed interesting, given theory. The matter of what constitutes practical significance is left in the hands of the researchers themselves, to be debated as a natural component of inference and interpretation.