@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}, }