@article{ADMIN,
      recid = {2},
      title = {Modeling Framing in Immigration Discourse on Social Media},
      address = {2023-01-26},
      number = {ADMIN},
      note = {The linked GitHub repository contains materials for the  NAACL 2021 paper Modeling Framing in Immigration Discourse  on Social Media.
<ul>
 <li>dataset.zip contains the full  set of tweet IDs used for analysis. Human-annotated data  for training frame detection models is located in the  annotated_data folder, and machine-predicted frame labels  are located in the predicted_data folder. </li>
  <li>codebook.pdf contains guidelines for frame annotation.  It includes detailed descriptions of issue-generic policy,  immigration-specific, and episodic/thematic frames. </li>
  <li>code/ contains all code for data collection, assessing  annotations, and building and evaluating models </li>
  <li>notebooks/ contain Jupyter notebooks for framing  analyses, including regressions and plots </li>
</ul>},
      abstract = {The framing of political issues can influence policy and  public opinion. Even though the public plays a key role in  creating and spreading frames, little is known about how  ordinary people on social media frame political issues. By  creating a new dataset of immigration-related tweets  labeled for multiple framing typologies from political  communication theory, we develop supervised models to  detect frames.},
      url = {http://socialmediaarchive.org/record/2},
}