The Politics of Prioritization: Senators’ Attention in 140 Characters

Abstract

For decades US senators have maximized their limited resources to juggle policy, party politics, and constituents, but the rise of social media sheds new light on how they make these strategic choices. David Mayhew’s seminal study of Congress (1974) argues that lawmakers engage in three types of activities – credit claiming, advertising, and position taking, but equally important is understanding how lawmakers make strategic choices among these activities. Senators’ limited resources and attention forces them to prioritize and make trade-offs among these activities, and new media platforms, like Twitter, offer a window into that decision-making process. This article examines what influences senators’ decisions to publicly communicate these activities on Twitter. By using senators’ daily Twitter activity in 2013 and 2015 as a measure of their individual agenda, I find that senators are most likely to prioritize position-taking activities. Women and committee leaders allocate the most attention to policy positions, but attention to policy may come at a cost. When senators do choose to prioritize policy through position taking, they often make trade-offs that lead to decreased attention to advertising and credit claiming. These activities and the choices among them not only have implications for lawmakers’ behavior in Congress, but also the type of representation and information constituents can expect from their elected leaders.

Senate Representation on Twitter: National Policy Reputations for Constituent Communication

“…This offers support for my first hypothesis (H1) that among senators’ goals and activities in Congress, national policy or position‐taking is most often the primary or most frequently communicated priority. This matches research by Russell (2018) who finds increased levels of position‐taking online by senators. President Donald Trump most prominently uses Twitter for partisan politics; however, the Senate has a history of prioritizing policy for their public outreach online.…”

“…Position‐taking fosters politicians’ ultimate goal of reelection (Mayhew, 1974), and this research argues that it is the primary way senators connect with constituents in this digitized political environment. Policy priorities—or at least the appearance of policy attentiveness—are at the core of a senator's rhetorical agenda on Twitter (Russell, 2018), and because of this I expect national policy to play a primary role in a senator's constituent communication on social media.

Policy priority hypothesis (H1) : Senators are most likely to tweet about policy priorities relative to competing priorities of constituent service or party politics.

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“…One of the most common tradeoffs in normative models of representation is constituent service as an appropriator versus targeting a national audience as a policy statesman (Grimmer, 2013). And despite some surveys that show constituents care more about local issues than national policy problems (Doherty, 2015), senators are using Twitter to promote themselves as policymakers and spend most of their time in Washington highlighting legislative work (CMF, 2015; Russell, 2018). Public policy problems and state concerns are not necessarily mutually exclusive—members are routinely explaining how pending legislation will affect constituents back home (Arnold, 1992; Grimmer, 2013)—however, senators are spending more time tweeting about the Affordable Care Act and tax reform and less time advertising localized projects or engaging online with constituents.…”

What Drives U.S. Congressional Members’ Policy Attention on Twitter?

“…With a high-performing classifier, we can analyze what drives lawmakers' patterns of attention among a consistent set of policy topics on a much larger scale than possible by current content coding techniques. Senators' Twitter agendas are an ideal platform to address theoretically important questions about legislators' agenda-setting behavior and representation (Russell 2018), and the use of the machine learning classifier allows for for comprehensive analysis across a set of topics, from the Policy Agendas Project, that have been used over time to calculate policy attention across multiple policy outputs. By using all the tweets of lawmakers in Congress, the data allows us to use this coding scheme to test hypotheses common to inquiries of legislative activity and lawmaker homestyle.…”

“…The original set of labeled Tweet data from Russell (2017Russell ( , 2018 comprised 68,398 tweets. Of these tweets, 45,402 tweets were labeled with policy codes and 22,996 were labeled as notpolicy tweets.…”