Research

Published Papers

• The National Network of U.S. State Legislators on Twitter
  Political Science Research and Methods
  Ishita Gopal, Taegyoon Kim, Nitheesha Nakka, Jeffrey Harden, Frederick Boehmke, Bruce Desmarais
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  Abstract

  A lot of attention has been paid to studying the online activity of the members of the United States Congress. This scrutiny has not been extended to state legislators. Very few studies exist which catalogue why state legislators connect and communicate with one another online in the ways they do. Inspired by this question and building on studies which have analyzed online communication of members of national legislatures, this paper aims to systematically analyze state legislator relationships in the online environment. We collect original data for 4000+ legislators and study patterns of connection and communication of state legislators on Twitter. The results from this study will help better understand what motivates tie formation in the online environment and if these patterns of connection conform to or can predict offline relationships. We test the impact of variables such as party affiliation, state, chamber, cohort, gender, and policy area focus on the organization of these online networks. We look at three main types of networks that can arise due to participation on Twitter - follower, retweets and mentions. We also aggregate the ties to infer dynamics between states.
• Attention to the COVID-19 Pandemic on Twitter: Partisan Differences among U.S. State Legislators
  Legislative Studies Quarterly 2022
  Taegyoon Kim, Nitheesha Nakka, Ishita Gopal, Bruce Desmarais, Abigail Mancinelli, Jeffrey Harden, Hyein Ko, Frederick Boehmke
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  Abstract

  Subnational governments in the United States have taken the lead on many aspects of the response to the COVID-19 pandemic. Variation in government activity across states offers the opportunity to analyze responses in comparable settings. We study a common and informative activity among state officials—state legislators’ attention to the pandemic on Twitter. We find that legislators’ attention to the pandemic strongly correlates with the number of cases in the legislator’s state, the national count of new deaths, and the number of pandemic-related public policies passed within the legislator’s state. Furthermore, we find that the degree of responsiveness to pandemic indicators differs significantly across political parties, with Republicans exhibiting weaker responses, on average. Lastly, we find significant differences in the content of tweets about the pandemic by Democratic and Republican legislators, with Democrats focused on health indicators and impacts, and Republicans focused on business impacts and opening the economy.

Working Papers

• The Racial and Gender Divide in Toxic Online Messaging Towards Politicians
  Nitheesha Nakka
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  Abstract

  Research on American politicians show that high profile minority politicians, and Republicans often face significantly higher rates of uncivil speech online. I expand on this research by examining the intersectional experience of gender and race at the state legislator level. Previous studies investigate behaviors towards federal representatives; however, local politicians have more day-to-day interactions with constituents which poses a greater risk to both online and offline violence. For this study, I use the Google Perspective API, a machine learning model that evaluates text to produce a continuous measure of toxicity; therefore, capturing the most authentically toxic tweets. Furthermore, this study encapsulates tweets mentioning legislators across all fifty states posted during the month of January 2021. In this way I capture the racial and gender biases in toxicity towards legislators during a notably violent exchange of political power in American history. I use a binomial logistic regression and ultimately do not find any evidence of a relationship between legislator identity and online toxicity directed towards them. There is a participatory effect in that legislators who tweet toxic tweets are more likely to receive toxic tweets in return. In sum, this study uses state-of-the-art methodology to detail how online toxicity towards subnational political elites is shaped.
• Racial and Gender Biases in State Legislators Twitter Endorsements: A Network Analysis
  Nitheesha Nakka
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  Abstract

  Endorsements contribute to electoral success both in gaining a seat in office and legislative success once in office. And for candidates for local office, who ostensibly do not have an extensive political resume to precede them, an endorsement from an existing legislator with an established political career is an important campaign resource. But how do legislators decided to distribute this resource? And how does identity play a role in allocating endorsements? To explore these questions further I analyze the network of Twitter endorsements of state legislators and the racial and gender biases within these networks. My project contributes to the extant literature by revealing how endorsements flow between state elected officials and uncovering any biases in these flows. Using Network Analysis on a dataset of legislators’ endorsementrelated tweets from all fifty states I do no find evidence or co-gender endorsement patterns but do find significant evidence of co-racial endorsement patterns amongst legislators and state legislative candidates. This research allows us to understand how elites shape descriptive representation in state political office.
• The study of short texts in digital politics: Document aggregation for topic modeling
  Nakka, Nitheesha, Ömer F. Yalçin, Bruce Desmarais, Sarah Rajtmajer, Burt Monroe
  
  Abstract

  Statistical topic modeling is widely used in political science to study text. Researchers examine documents of varying lengths, from tweets to speeches. There is ongoing debate on how document length affects the interpretability of topic models. We investigate the effects of aggregating short documents into larger ones based on natural units that partition the corpus. In our study, we analyze one million tweets by U.S. state legislators from April 2016 to September 2020. We find that for documents aggregated at the account level, topics are more associated with individual states than when using individual tweets. This finding is replicated with Wikipedia pages aggregated by birth cities, showing how document definitions can impact topic modeling results.
• Digitally Accountable Public Representation (DAPR)
  Cassandra Yuehong Tai, Nitheesha Nakka, Sarah Michele Rajtmajer, Kevin Munger, Yu-Ru Lin, Bruce A. Desmarais
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  Abstract

  We introduce the Digitally Accountable Public Representation (DAPR) Database, an innovative archive that systematically tracks and analyzes the online communications of federal, state, and local officials in the U.S. Focusing on X/Twitter and Facebook, the database includes Tweets and Facebook posts dating back to 2020, offering a rich historical perspective on digital political discourse by elected officials in the states. Along with the raw data, we develop and include key measures that quantify relevant features of online communications. These include specialized measures of misinformation dissemination, the use of toxic language by officials, and the expression of anti-vaccination attitudes. In addition to presenting and describing the contents of the DAPR database, we introduce a dedicated R package, enabling users to download and analyze data in bulk, tailored to their specific research needs. We also provide an interactive digital dashboard, designed for a broader audience to explore and interpret the data in a user-friendly online environment. Lastly, we describe our model for expanding and sustaining the DAPR database going forward, including the addition of new officials and platforms, and the collection of social media data in the post-API era.
• Understanding Asian Hate in State Legislatures: An Electoral Connection
  Nitheesha Nakka, Cassandra Yuehong Tai, Isaac Pollert, Lingyu Fuca
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  Abstract

  Recent work in digital politics has begun to explore the role of race and ethnicity in digital communications. This research, however, has not fully addressed how lawmakers interact with their Asian constituents and the broader Asian population. We take up this task by analyzing more than 3 million tweets posted by state legislators between 2020 and 2021, investigating state lawmaker messaging targeting Asian ethnic groups. This dataset encapsulates the Covid-19 pandemic which was a particularly contentious time period for Asian and Asian-subgroup populations in the US. As such we test whether the proportion of Asian populations affects politicians’ online political rhetoric. This work identifies tweets directed towards these communities and employs a state-of-the-art anti-Asian hate speech classifier. We find approximately 25,102 tweets that target Asian ethnic groups specifically. In an initial descriptive analysis of these targeted messages, 5,852 were classified as counter-hate speech, significantly outnumbering the 79 identified as actual hate speech. We also find that anti-hate speech is significantly associated with the proportion of Asian population at the state level and public ideology at the district level. Our findings contribute to the understanding of how state lawmakers address Asian communities, in addition to shedding light on the rise in extreme speech from elected officials.
• Economic Conditions, Economic Perceptions, and Media Coverage of the United States Economy
  Pablo Barberá, Amber Boydstun, Suzanna Linn, Ryan McMahon, Jonathan Nagler, Nitheesha Nakka
  
  Abstract

  We examine two aspects of media coverage of the economy. First, we look at what objective economic indicators drive the content of media coverage of the economy. Second, we look at the impact of media coverage of the economy on economic perceptions. We pay special attention to whether media coverage is driven by changes in mean family income and other aggregate measures, or changes in more dissaggregate measures such as the change in mean income of the bottom or top income quintile. And we compare the impact of objective economic indicators on media coverage across media sources: the New York Times, the Washington Poast, the Wall Street Journal, and USA Today. We examine the impact of this media coverage of the economy on economic perceptions using the index of Consumer Sentiment, as well as other available survey data. We examine in particular whether the effect of media coverage on economic perceptions varies by: the income level of the individual; and the nature of the media outlet. Our analysis covers media coverage and public perceptions of the economy in the United States over a fifty year period.